Factors Blog

Sales intelligence tools provide marketing and sales teams with relevant data to refine outreach and targeting workflows and performance. Leveraging sales intelligence tools help drive pipeline by discovering high-intent target accounts (with reverse IP-lookup account identification), surfacing relevant contact data (phone numbers, mail IDs, etc), enriching account profiles (firmographics and technographics), and/or reporting GTM metrics and KPIs. In short, sales intelligence tools provide insights to support better marketing and sales efforts. 

Needless to say, sales intelligence relies crucially on accurate, up-to-date data to be of any value. Workflow automations, integrations, UI, customer support, and pricing plans are other factors you should consider when evaluating a sales intelligence tool. 

While there’s no shortage of sales intelligence solutions out there, it can be challenging to pick one that aligns with your requirements and budget. The following article reviews the top 8 sales intelligence tools for your consideration. 

Sales Intelligence - Account Level

Depending on the nature of your business, your total addressable market may be very, very large. Especially for SMEs with limited resources, it wouldn’t make sense to go after each and every account in your TAM. Instead, it's important to identify and prioritize those ICP accounts that showcase the most buying intent with your brand. 

Account intelligence tools use reverse IP-lookup to do just that: identify and qualify anonymous, high-intent companies that are already engaging with your brand but are yet to convert. Account intelligence tools deanonymize traffic to reveal account names, firmographics, technographics and more. 

With account intelligence tools, you may target warm accounts as opposed to cold, brand-unaware ones. This, unsurprisingly, results in more conversions than ever before. Here are 4 robust account intelligence platforms for your consideration:

1. Factors.AI

Factors is an AI-fuelled account intelligence solution built upon strong analytics and attribution foundations for B2B teams. Factors provides a wide range of features including account identification, account scoring, workflow automations, multi-touch attribution and more. 

Features

• Account identification - discover anonymous accounts interacting with your brand
• Account enrichment - enrich accounts with firmographics and technographics
• Analytics & attribution - KPI reporting, funnels, path analysis, multi-touch attribution and more
• Journeys & scoring - Bird’s eye view of customer journeys and account scoring based on cross-channel engagement 
• Workflow automations - Configure real-time alerts, trigger-based emails, CRM updates and more based on intent signals

Benefits

• Data-accuracy - Factors works with industry-leading data partners including 6sense and Clearbit to deliver accurate account identification match rates of up to 64%. This includes firmographics and technographics such as geos, industry, revenue range, employee headcount, etc. 
• Holistic scoring - Deep-rooted collaborations with LinkedIn and G2 in addition to website engagement ensures that accounts are scored holistically across the most common channels
• Robust analytics - Given that Factors is built upon strong analytics and attribution foundations, it provides unmatched granularity in terms of reporting and reporting techniques — so you can make data driven decisions, effortlessly 

Limitations

• Contact-level data: At the moment, Factors does not provide contact-level data such as email IDs or phone numbers. Instead, users will have to integrate this data from a contact database provider like Apollo or ZoomInfo. 
• Native integrations: At the moment, Factors provides native integrations with the most popular B2B ad platforms, CRMs, MAPs, CDPs, and more. That being said, it misses out on integrations with lesser used platforms like Zoho. Note that data may still be pushed from Factors to nearly any other tool in the webhooks (Zapier, Make.com, etc). 

Pricing

Factors pricing is based on the number of accounts identified (or volume of monthly website traffic). Factors does offer a free trial and a free plan. Learn more about Factors pricing here: www.factors.ai/pricing

2. Clearbit

Clearbit is an industry-leading sales and marketing intelligence platform that helps teams gain deeper insights into their customers, enhancing marketing efforts and sales strategies. Through a suite of APIs, Clearbit integrates with existing systems, providing real-time identification and enrichment data. 

Features

• Reveal - Clearbit identifies anonymous website visitors using IP-lookup. Given that every tool on this list does this, data accuracy and pricing are two important considerations when differentiating between alternatives. 
• Enrichment - Clearbit also provides firmographics from over 250 data sources. This includes technologies, headcount, revenue, location, contact information, and more.
• Capture - like Leadfeeder Contacts, identifies best-fit contacts from companies visiting your website to reach out to with retargeting campaigns or outbound efforts

Benefits 

• Intuitive UI - Clearbit is a well-established platform with an intuitive, accessible user interface making it easy to plug and play for most teams.
• Strong integrations - Clearbit provides deeper, two-way integrations with CRMs, Internals comms, and other everyday GTM platforms as compared to other tools on this list. 
• Contact database - In addition to account level data, Clearbit also provides a contact database to streamline the outreach process by recommending relevant people to get in touch with. 

Limitations

• Pricing - While Clearbit boasts an impressive database, it’s definitely a more premium product. Pricing starts at around $12,000 annually for its more basic plans. This might be inaccessible for early-stage SME teams.

Pricing

Clearbit does not openly reveal its pricing but estimates place it starting at about $12,000-$20,000 a year. Learn more about Clearbit pricing by connecting with their sales team. 

3. Leadsquared

LeadSquared CRM is a sales and marketing automation platform to boost sales productivity and revenue outcomes. Salespeople can sell a lot faster and smarter by using LeadSquared's customizable workflows, reminder systems, and lead scoring features. The tool also provides complete visibility into the prospects activities and preferences in a single view, for a more personalized selling experience. 

Features

- Automated Lead Management: Capture, distribute, and track leads at every stage of the sales funnel. 

- Reports and Analytics: In-depth reports for managers to analyze sales performance, forecast sales, and manage the team's targets. 

- Segmented User Lists: Assign customers to lists based on various parameters such as demographics, preferences, etc. Businesses can set up trigger-based communication for every list to personalize communication. 

- Mobile CRM: Track field sales activities and interactions as your sales reps get through the day. The Mobile CRM also allows them to upload documents and lead data from their phone. 

- Built-in-dialer: Set up one-click calls to prospects, manage call logs, recordings, and notes by integrating with IVR solutions. 

Benefits

- Completely customizable: LeadSquared is a good fit for businesses of all sizes, no matter how complicated their workflows are. The product and workflows can be customized to solve specific business challenges. 

- Integrations: All your data can be centralized on the CRM because it can be easily integrated with most of the popular tools. 

- Security: LeadSquared is compliant with all the laws and regulations related to data security. So, businesses never have to worry about the data they add on the platform.

Limitations 

Initial training: Users who are new to using a CRM might require training while setting up complex automation and reporting.

Pricing

LeadSquared offers three plans based on the features businesses may require. Here are the specifications of these plans:

4. Leadfeeder/Dealfront

Leadfeeder [Now Dealfront] is another popular account intelligence solution that’s been around for quite some time. It has recently rebranded itself as Dealfront — a Europe-centric GTM intelligence platform. This has resulted in several former customers looking for Leadfeeder Alternatives. That being said, it’s still a comprehensive solution depending on your use-case. 

Features

• Account identification - As with other tools on this account intelligence list, Leadfeeder identifies the names of the companies visiting your website. 
• Leadfeeder Contacts - As with Clearbit, Leadfeeder also provides contact-level data based on the accounts visiting your website 

Benefits

• Europe-centric data - If you’re looking for Europe-focused sales intelligence, Leadfeeder may be the best choice for you, given that it especially specializes in European geographies. 

Limitations

• Shacky integrations - While Leadfeeder provides a wide range of integrations, users often find discrepancies and inaccuracies in terms of data synchronization. 
• Poor customer success - Several users complain about Leadfeeder’s poor customer success, claiming it to be pushy and unhelpful.

Pricing

As with most other tools on this list, Leadfeeder pricing is based on the volume of data consumed. Leadfeeder does offer a free plan. Leadfeeder pricing starts at about $150. 

5. Albacross

Finally, we arrive at Albacross. Albacross is another leading sales intelligence tool. The Sweden-based platform works with 10,000+ companies to provide data enrichment, sales alerts and intent signals.

Features

• Account Identification: Albacross identifies anonymous accounts, firmographic information and visitor intent. Albacross features one of the largest proprietary first-party databases in the world.
• Personalization: Albacross natively integrates with popular personalization tools such as Optimizely and VWO to customize website content based on who’s visiting the site. 
• Display ads: Albacross can also launch and monitor display ads within the platform itself. The software partners with several publicists such as The New York Times and Daily Mail to distribute account-level targeted ads. 

Benefits

• Experimenting: Albacross  offers the unique benefit to experiment and run A/B tests in conjunction with visitor identification and intent data. 
• Customer success: Several reviews rave about Albacross’s stellar customer success management. Given that Albacross is considered to be an involved, enterprise-level tool, it’s essential to have this level of support to get the most value out of the product. 

Limitations

• Rigid firmographics and filters - Albacross lacks agility when it comes to filters and breakdowns. Reviews reveal that, unlike other tools on this list, Albacross is currently unable to filter identified companies based on firmographics such as name or size. As a result, users seem to find sorting and reporting somewhat challenging.
• Buggy integrations: Multiple reviews claim that Albacross’s integrations, especially with CRMs like Salesforce, could do with some work. Given that visitor identification is primarily used to support ABM, this can be a major drawback to B2B teams. 
• Limited documentation and resources make users overly reliant on customer success teams

Sales Intelligence - Contact Level

Identifying in-market accounts is a fantastic start to optimizing GTM performance. But once you have a set of target accounts, you also need to know who to reach out to within those accounts for the best chance of conversions. You need phone numbers, email IDs, and LinkedIn profiles to get in touch with the relevant stakeholders and move forward with outreach and targeting. 

This next set of sales intelligence tools helps with just that: Identifying relevant contacts and their contact information from your target accounts using enormous contact databases. 

6. Apollo

Apollo is a sales intelligence and engagement platform. It is an end-to-end sales solution platform with over 265 million contacts. It provides access to rich  buyer data, analytical insights and automated and personalized workflows for outreach.

Features

• Enrich: Apollo helps search and enrich lead data leveraging their extensive B2B database.
• Prospect: Using over 65 data attributes, Apollo helps you build lists and filter leads with precision 
• Engage: automated sequencing across channels like LinkedIn, SMS, email, etc with AI-powered hyper personalisation. 

Benefits 

• Powerful Search Tool: The search capabilities are robust, allowing you to fine-tune our searches for targeted sales prospecting.
• Great Support: The customer support team has been responsive and helpful whenever we've had questions or needed assistance.

Limitations

Surface-level LinkedIn Integration: No cross-platform automation available with LinkedIn

Steep learning curve: The numerous customizations and variables can be overwhelming for beginners

Pricing 

Apollo.io has user based pricing model with a basic plan that starts at $49 dollars/user per month:

7. Slintel 

Slintel is an advanced sales intelligence software that provides valuable technographic data and helps enhance leads by offering precise details about prospects, including email addresses and contact information. 

Features

• Buyer enrichment: rich database which provides additional information about their leads and prospects, such as company size, location, and industry ‍
• Buyer intent tracking: Slintel has a valuable indicator to signify a lead’s readiness to purchase.

• People Profiles: Slintel’s database also provides detailed information about the individuals within a company, including their job titles, responsibilities, and contact information.

Benefits 

• Technographic filtering: Slintel features unique filters based on understanding the technologies that their leads and prospects are using. 
• API suite: Slintel’s API offers range of integrations that help connect with your teams’ current operating system, workflow, and technological infrastructure

Limitations 

No mobile credits: Slintel has overlooked an important outbound channel by not providing mobile credits in any of their plans.

Pricing 

Slintel has tiered pricing and prices for each plan vary based on the number of leads and users, as well as the duration of the subscription.

8. LinkedIn Sales Navigator 

LinkedIn Sales Navigator is a popular sales intelligence that enables professionals to expand their network, find potential customers, and engage in effective lead generation. It offers advanced search capabilities, personalized insights, and seamless integration with other sales tools for enhanced prospecting and relationship building.

Features

• Search Feature: The Sales Navigator advanced search function gives reps the power to more narrowly target their ideal leads and discover relevant connections.
• Automated Lead Generation: The Lead Recommendations feature suggests relevant leads based on your sales preferences, search history, profile views, and past saved leads.
• Real-time updates: Sales Navigstor provides real-time updates on their leads and accounts, including job changes, company updates, and news mentions.
• Customized Lists: Users can create and save customized lead and account lists for targeted outreach.

Benefits

• Lead Tracking and Notes: Users can save leads and accounts, add notes, and track interactions, helping them stay organized and keep a record of their sales activities.
• InMail Credits: users get a certain number of InMail credits with a sales navigator subscription, which allow them to send direct messages to LinkedIn members even if they are not connected. 

Limitations 

• Cost: LinkedIn Sales Navigator is a premium service and can be relatively expensive, especially for individual users or small businesses. The cost may be a barrier for some users.
• Learning Curve: The platform has a steeper learning curve and it may take time to fully understand and utilize all its features effectively.
• Limited InMail Credits: While Sales Navigator provides limited InMail credits. If users exhaust their credits, they may need to purchase additional ones, which is costly.

Pricing

LinkedIn Sales Navigator offers three pricing tiers: Core, Advanced, and Advanced Plus:

9. Lusha

Lusha is a lead generation and data enrichment tool that aims to help companies generate qualified leads and maximize conversions. It helps manage business leads, company contacts, and B2B databases fo better sales prospecting. 

Features 

• Team: Lusha lets you add team members and create different groups within the application to facilitate collaboration.
• Technology Filter: Lusha's Technographic filters that give businesses the ability to target companies based on the technology stack they are using.
• Salesforce Data Enrichment: Lusha's Salesforce Data Enrichment feature automatically enriches Salesforce records with accurate contact and company data.
• Intent: Lusha allows you to filkter prospects based on their behavioral signals

Benefits

• High Accuracy: Lusha claims the highest accuracy rate in the entire industry, claiming 81% accurate emails and phone numbers to their users for cold outreach.
• User-friendly interface: The platform interface is intuitive and easy to navigate for beginners.
• Chrome extension: Lusha’s chrome extension is a value add that makes it easy to get the contact information from the browser directly.
• Responsive customer support: The customer support team is extremely responsive and friendly, helping improve the user experience.

Limitations 

Data Security: there are reports of outrage from customers that accuse Lusha of selling their personal information to third parties. 

Pricing 

Much like most softwares on this list, Lusha has a usage based pricing model with 4 plans- free, pro, premium and scale:

In conclusion, your ideal sales intelligence tool should offer a comprehensive suite of features that empower you to not only identify potential customers but also to understand their buying decisions. It should automate workflows, personalize communication, and enable more effective outreach. The tool should be dynamic, relying on real-time data and signals to connect with the right buyers at the right time.

As you pick your sales intelligence tool, understand the role of technology in your broader GTM strategy. Look for a tool that can seamlessly integrate with your existing systems, enabling a cohesive and efficient approach to lead generation and customer engagement. Let your sales intelligence tool become a strategic partner in your business's success- schedule a demo with Factors.ai

Revenue forecasting is critical for any business, especially when it comes to B2B SaaS. The immense speed of progress in this industry requires keeping up with trends, continuously experimenting with fresh channels, and adjusting budget allocation based on future predicted revenue. 

Accurate revenue forecasts help organizations make data-driven growth decisions.

This comprehensive guide will cover everything you need to know about revenue forecasting models.

What is Revenue Forecasting?

Revenue forecasting is the process of predicting future revenue for a company using historical performance data, predictive modeling, and qualitative insights. Revenue forecasts provide an estimated projection of the total revenues expected in a future period.

Forecast time horizons can range from next month to next quarter to five years from now. Short-term forecasts may focus on immediate sales pipeline conversion, while long-range forecasts take a broader market-based approach.

With revenue forecasting, the goal is to provide the most accurate prediction of future revenue based on current insights. These reports can also be improved by leveraging attribution data so you know exactly what functions of marketing or sales bring in real revenue.

Revenue forecasting helps answer questions like:

• How much revenue can we expect to generate in the next quarter/year?
• How will seasonality trends and new product launches impact revenue?
• How quickly are we expected to grow over the next 5 years?

When done right, revenue forecasting can power key business functions:

• Financial planning: Building P&L statements, budgets, valuation
• Sales planning: Setting quotas, territory mapping, compensation
• Marketing planning: Demand generation budgeting, growth modeling
• HR planning: Hiring goals, resource allocation across teams
• Manufacturing planning: Inventory needs, capacity expansion
• Executive planning: Strategy setting, investment decisions

While revenue forecasting attempts to predict future revenues, it differs from a revenue projection which is typically more aspirational. Let’s understand the differences. 

Revenue Forecasting vs. Revenue Projections vs. Sales Forecasts

These three terms are used quite often when it comes to budgeting and strategic planning but they mean different things. 

• Revenue Forecasts model the actual monetary revenue expected based on sales forecasts, historic performance, market conditions and statistical modeling. It provides the most likely, evidence-based scenario.
• Revenue Projections are what leadership desires to happen—an optimistic target rather than a data-driven expectation. Projections represent an aspirational revenue goal.
• Sales Forecasts predict expected sales bookings and pipelines based on leading indicators like open opportunities. They are an input into revenue forecasts.

Now, let’s understand the types of revenue forecasts that you may come across. 

Key Types of Revenue Forecasts

There are also different types of revenue forecasts based on methodology and time span:

• Short-term vs. Long-term - Short-term forecasts focus on immediate pipeline conversion, while long-term forecasts take a broader market-based view.
• Top-down vs. Bottom-up - Top-down forecasting starts with macro assumptions and allocates them across business units. Bottom-up rolls-up forecasts built from ground realities.
• Operational vs. Financial - Operational forecasts model near-term revenue streams. Financial forecasts take a holistic P&L view including costs and expenses.
• Deterministic vs. Probabilistic - Deterministic forecasts provide a single expected outcome. Probabilistic forecasts model a range of outcomes and probabilities.

Now, let's examine some key business uses and benefits of revenue forecasting. 

Why is revenue forecasting important?  

Accurate revenue forecasts can be the difference between success and failure for a business. Here are a few ways forecasting powers planning across the organization:

1. Budgeting with Realistic Precision

For finance teams, the single biggest use of forecasts is to build organization-wide budgets.

Budgets dictate how much gets spent on everything from R&D investments to marketing programs and payroll. Without reliable revenue forecasts, budgets devolve into guesswork.

For example, assume a company's revenue was $5M last year. Now the CFO needs to build next year's budget.

With intelligent forecasts, finance can model that based on new product launches, a 10% industry growth rate, and sales team expansions, revenues are likely to reach around $7.5M next year.

The CFO can now budget for expenses accordingly - say $1M for new engineering hires, $500K for more marketing, $150K for sales operations software etc.

Without forecasts, the CFO is flying blind. Maybe she pads the budget with a 20% increase to $6M. But if actual revenues only end up at $5.5M, suddenly there's a multi-hundred thousand dollar budget shortfall, requiring drastic cuts.

Conversely, if revenues actually reach $8M but budgets are based on last year's numbers, the company is now missing key growth opportunities due to under-investment. 

‍2. Optimize Operations Management

Beyond budgets, forecasts guide operational decisions across departments:

• Sales: Forecasts feed territory assignments, quota setting, compensation planning, and capacity modeling whereas under-forecasting leaves money on the table.
• Marketing: Forecasts dictate digital and outbound campaign budgets and funnel targets where bad forecasts can waste spending and lead to missed opportunities.
• Product: Prioritizing the roadmap requires expected revenues from new features so bad forecasts can result in misplaced priorities.
• HR: Hiring and workforce planning requires expected growth rates and flimsy forecasts risk talent shortages or bloat.

Across the board, teams depend on forecasts to optimize operational management for future success amid constraints.

3. Fuel Strategic Decisions

Forecasts also provide the quantified confidence executives need to drive growth through major strategic moves:

• Funding rounds: Forecasts build credibility on growth potential to establish valuations. Weak forecasts undermine bids for capital.
• M&A valuation: Pre-transaction due diligence depends on target revenue forecasts. Bad forecasts lead to overpayment or lost deals.
• Market expansion: Breaking into new regions or verticals requires quantifying addressable revenues and investment payback.
• New product prioritization: High-impact opportunities are identified by revenue potential under constrained resources.
• Executive recruitment: Attracting star senior talent requires painting a compelling growth.

Creating reliable revenue forecasts empowers executives to place decisive strategic bets amid uncertainties, as opposed to shooting blind.

4. Track Performance to Plan

Revenue forecasts also provide a scorecard against which actual results can be monitored. Comparing real revenue performance vs. forecasted expectations then allows deviations to be easily flagged. With this information at hand, teams can course-correct before small misses snowball into major disasters.

Without forecasts as the reference point, there is no way to reliably track progress against potential. Revenue actuals in a vacuum don't reveal whether performance is on-target or off-course.

What are the types of revenue forecast models?

Now that we understand the fundamentals of revenue forecasting, let's examine some of the most common revenue forecasting models and techniques.

Broadly, forecasting approaches can be divided into two families:

• Quantitative models take a data-driven statistical approach to identifying trends and patterns in historical data that can be used for future predictions.
• Qualitative models incorporate expert perspectives, market analyses and contextual business insights to predict future revenues.

There are four common forecasting models namely linear regression, time series, bottom-up, and top-down. The best way to perform revenue forecasting is by combining multiple models to benefit from each of them.

Let's explore some of these popular models.

1. Linear Regression Models

Linear regression analyzes historical data to model how changes in key variables impact revenue. 

Regression provides a data-backed view into drivers of revenue growth and contraction. 

However, regression models are only as good as the input data. They may miss complex real-world dynamics that are not reflected in historical data. Approaching them as helpful guiding tools rather than absolute truth is important.

Key Benefits

• Quantifies the relationship between revenue drivers and outcomes
• Calculates the impact of each variable on revenues
• Models complex interactions between multiple variables
• Provides data-driven revenue projections

How It Works

Simple linear regression uses one variable, often time, to predict revenue.

For example, it can help a business quantify how much additional revenue every $1 increase in marketing spend has historically generated. This insight can be used to forecast revenue under different scenarios.

 Multiple linear regression incorporates additional factors simultaneously like marketing spend, sales activities, market dynamics etc.

The model examines historical data to calculate coefficients measuring each variable's unique relationship with revenue. These insights feed the predictive model to forecast expected revenue under different scenarios.

Considerations

• Regression modeling requires large volumes of accurate historical data
• Predictive power diminishes beyond modeled relationships
• Difficult to model nonlinear variable interactions

Regression provides a data-backed view into drivers of revenue growth and contraction. It brings statistical rigor to projecting the top and bottom-line impact of decisions around pricing, hiring, product launches, geographical expansion and more. 

However, these models are only as good as the input data. They may miss complex real-world dynamics that are not reflected in historical data. Approaching them as helpful guiding tools rather than absolute truth is important.

2. Time Series Forecasting

Time series analysis detects historical patterns in data over time. This helps tease out seasonal and cyclical trends from broader growth trajectories and random noise.

It decomposes revenue time series into:

• Trend - Overall upward/downward trajectory
• Seasonality - Cyclical patterns
• Noise - Random unexplained variations

Time series models maximize signals and minimize noise in historical data for sophisticated revenue projections tailored to the business. These models can incorporate recent data, balancing responsiveness to change with smoothing noise and help you extract actionable insights for reporting and forecasting.

Key Benefits

• Models trends and seasonality specific to the business
• Highlights time-based nuances impacting revenue
• Provides granular, frequently updating forecasts

How It Works

Time series techniques like moving averages, exponential smoothing, and ARIMA modeling analyze a revenue time series to optimize the predictive modeling of its components. 

For example, enterprise software revenues may spike every fourth quarter due to a year-end budget flush. Media subscriptions may dip in the summer months when travel is high. Understanding these nuances helps make more contextual and accurate forecasts.

You can then use the insights generated from the time series forecasts to smoothen the growth curve giving you more predictable revenue. 

Considerations

Time series models need sufficient history to detect reliable patterns. They may miss entirely new market dynamics or one-off events, unlike the past. Hence, combining them with human judgment is important.

3. Bottom-Up Forecasting

Bottom-up forecasting taps insights from sales, account management and other frontline teams to build projections. They incorporate pipeline health, competitive threats, and market mood along with historical data.

How It Works

Let’s take an example organization with sales, marketing, finance, and leadership teams. Here’s how bottom-up forecasting would work:

• The sales team starts by analyzing the health of its current pipeline and expected deal cycles to forecast expected conversion rates by product line and region.
• Meanwhile, marketing examines recent campaign performance and lead generation trends to estimate new MQLs by campaign channel. They apply conversion rates to project new SQLs.
• Finance consolidates these detailed bottom-up forecasts from each department. They identify and resolve any inconsistent methodologies or assumptions between teams.
• Leadership reviews the consolidated forecast and makes final top-down adjustments to determine the official revenue projection.

Key Benefits

• Incorporates insights from sales, account management, and other frontline teams
• Reflects pipeline health, competitive dynamics, and micro-market nuances
• Promotes buy-in through the inclusion of cross-functional inputs

Considerations

Inconsistent assumptions between teams can skew the overall forecast. Guidance from leadership on industry outlook, macroeconomic factors and growth objectives helps align assumptions and methodologies.

4. Top-Down Forecasting

Top-down forecasting starts with the big-picture view of the total addressable market, growth trajectories, economic conditions and business strategy. Leadership sets goals and divides revenue targets across functions.

This ensures strategic alignment between long-term goals and short-term operations. However, seemingly arbitrary targets could demotivate teams without context on the rationale so with top-down forecasting, you need to ensure two-way communication and transparency from leadership.

How It Works

Let’s look at top-down revenue forecasting through an example. 

• The executive/leadership team starts with the overall revenue growth target based on market outlook and strategic goals. They divide this target across sales, marketing and customer success based on revenue impact capacity.
• Each team gets their individual revenue target along with guidance on growth assumptions like pricing, conversions, expansions etc. 
• Teams build goal-aligned execution plans around sales territories, campaigns, and account targeting to meet their top-down number.
• Leadership reviews department plans to ensure coordination and consistent assumptions are in place.

Considerations

• Teams lack insights into the rationale behind seemingly arbitrary targets
• Overlooks micro-market nuances and competitive dynamics
• Requires reconciliation of opposing projections

Blending both top-down and bottom-up approaches for revenue forecasting can help set realistic targets based on market conditions while aligning activities to growth objectives.

What is the Best Method for Revenue Forecasting?

The best forecasting method depends on your use case. Let’s understand this with two examples.

A SaaS company with recurring subscription revenue may find time series analysis to be very effective. That’s because, studying historical revenue patterns over time, seasonal cycles and trends become apparent. Statistical time series models can help quantify these patterns to accurately predict recurring revenues.

On the other hand, for a retail chain opening new store locations, a bottom-up approach could prove more useful. Each new store manager could prepare detailed forecasts for their location based on demographics, nearby competitors, marketing plans etc. Aggregating these bottom-up projections provides a realistic the overall revenue forecast.

The point is, every business is situated differently. The ideal approach depends on:

• Data availability - length of revenue history, presence of relevant drivers/variables
• Revenue characteristics - recurring/seasonal patterns, level of variability
• Business structure - centralized/decentralized, product diversity
• Strategic context - expanding to new markets/geographies, introducing major new offerings

Leaders need to understand revenue drivers in their industry and business and use the insights to tailor the forecasting methodology to their specific situation and objectives.

Combining methods can also be beneficial. For example, a short-term quarterly forecast may use time series analysis to leverage recent revenue trends. And for the annual budget, a bottom-up approach could then add local market perspectives for a comprehensive view.

The key is adapting forecasting approaches to match business realities which provides the accuracy and insights required for confident decision-making across the organization. 

Revenue Forecasting Models: Best Practices

What are some of the best practices for ensuring accurate revenue forecasting when using these revenue forecasting models? Let’s look at 4 of the best practices that you should consider following. 

1. Start with high-quality data

Remember this—garbage in, garbage out. Even the most advanced model cannot compensate for poor-quality data. Invest in processes and systems to collect accurate, complete revenue data, with proper change logs and auditing.

2. Eliminate outdated information

Stale data loses relevance quickly. Establish mechanisms to continually gather the latest data on revenue drivers. This could involve surveys, sales team feedback, customer interviews etc.

3. Reduce the length of planning cycles

Annual plans using old assumptions miss market shifts. Re-forecast more frequently using the latest data to stay agile. Quarterly or even monthly cycles are preferable.

4. Avoid a futile bid for perfection

Obsessing over tiny accuracy improvements is counterproductive beyond a point. Focus on balancing usefulness and cost when selecting model sophistication.

How Factors Can Help Your Business Drive Revenue

Let's face it—optimizing your GTM strategy is tedious, and time-consuming without having all the right data in one place.

You have your metrics in different silos across marketing, sales, and revenue and piecing together a complete picture feels impossible. You could have leaks in your funnel, but cannot find the exact pages. Attribution has become a shot in the dark. And you're pouring money into campaigns without knowing if they’re working or not.

This is where Factors comes in. 

Factors integrates all your disparate data sources—CRM, MAP, web analytics, social media, ad platforms—into one unified view. 

You can quickly pull custom reports to get insights and answers on the fly. Factors also leverages leading IP resolution technology to reveal anonymous website traffic. Helping you discover up to 64% of untapped traffic and turn them into known, sales-ready accounts. More accounts to market means more pipeline and revenue.

With unified data and a complete view of your funnel, you gain the power to make strategic decisions that move the revenue needle. Scale what works, fix leaks, attribute MQLs to campaigns, analyze account journeys—Factors has you covered.

Don’t shoot in the dark. Book a demo with Factors to see how we can help you get better insights and data to power your forecasting models and make data-driven decisions to boost pipeline and growth

FAQs

1. What is revenue forecasting and why is it important?

Revenue forecasting is the process of predicting future revenue for a company using historical data, predictive modeling, and insights. Accurate forecasts empower data-driven planning and growth decisions across functions like finance, sales, marketing and operations. Reliable revenue forecasts are mission-critical for budgeting, managing operations, fueling strategic growth moves and tracking performance.

2. What are the top revenue forecasting models?

Popular models include linear regression to model revenue drivers, time series analysis leveraging historical patterns, bottom-up forecasting aggregating projections from frontline teams, and top-down forecasting starting with leadership’s total target. Combining approaches provides flexibility to tailor models to business needs and data availability.

3. How often should you update revenue forecasts?

Outdated assumptions lose relevance quickly, so forecasts should be refreshed frequently. Quarterly or monthly re-forecasting cycles are preferable to stay agile versus annual plans. Access to latest revenue driver data enables more responsive modeling.

4. What are some common pitfalls of revenue forecasting?

Potential pitfalls include unpredictable market shocks, limitations of available data, human errors in model assumptions, and finite resources to build sophisticated models. Perfection is unrealistic but maximizing useful accuracy is key.

5. What data is needed for accurate revenue forecasts?

Quality historical revenue data is the foundation. Relevant drivers like market trends, sales activities, product changes, and economic indicators help explain revenues. Updated inputs prevent stale assumptions. Data challenges need pragmatic solutions.

6. How can technology enable better revenue forecasts?

Tools like CRM, account intelligence and analytics tools like Factors, etc. provide key sales and marketing data inputs. Purpose-built FP&A software centralizes data for modeling and reporting. Technologies like AI and machine learning can boost forecasting sophistication.

7. What best practices improve revenue forecasting?

Best practices include maintaining high-quality data, eliminating outdated information, shortening planning cycles, combining modeling approaches, and focusing models on business needs. Avoid needless complexity but leverage enough sophistication to meet objectives.

Sales territories are groups of accounts that share certain similarities, allowing sales teams to specialize. This specialization can lead to a more repeatable and efficient sales process. Historically, geography often defined sales territories because sales were conducted in person. However, as digital sales gain prominence, the approach to defining sales territories is evolving. Understanding and effectively managing sales capacity is crucial to driving organizational growth and achieving sales goals.

This blog will explore why sales territories are necessary, different types of territories, and steps to create them, enriched with real-world examples and expert insights.

What is a Sales Territory?

A sales territory is a defined market segment for which a salesperson or a sales team is responsible. In simple terms, territories divide your target market into smaller segments that reps can better manage. For example, back in the day, one person would be assigned to the top half of the west coast of the USA while another would be manning the bottom half.

The territories you define can be based on various parameters like location, company size, industry, product line, channel partners, etc. This can also be useful when working on account-based marketing campaigns.

For example:

●  A software company selling to SMBs across the US can split the country into Northeast, Midwest, South, and West sales territories. Reps based in each territory will handle that area.

●   An enterprise software company may divide its market by industry verticals. One rep handles all education/non-profit accounts; another handles healthcare accounts, and so on.

The primary goal is to create manageable sections that allow sales teams to focus their efforts and resources effectively. These territories can be defined by geography, industry, customer type, product type, or a combination of these factors. 

That said, geography doesn’t matter as much in digital sales as it used to. If you are selling a service performed by people like a circus or even heavy machinery, geography will play a role since you might wish to go and pitch your product. The same applies to an expensive product or service. However, geography won't matter much if a software or course can be sold, bought, used, and serviced anywhere.

We'll explore different types of sales territories later in this guide.

But why do we need sales territories?

Implementing sales territories provides immense strategic value for SaaS organizations. Well-defined territories lead to optimal sales coverage, increased efficiency, and higher productivity.

Let’s understand why sales territories are essential for everyone involved in the transaction:‍

1. Customer Perspective

From the customer’s perspective, sales territories ensure they receive in-person service from sales representatives knowledgeable about specific, specialized products. Customers benefit from having a dedicated point of contact who understands their unique needs and can provide tailored solutions. Studies show that personalized service in sales territories can improve customer satisfaction by up to 20%.
2. Company Perspective

From the company’s perspective, sales territories help build competence within specific product categories or markets, leading to better predictability and coverage. This structured approach allows companies to allocate resources efficiently, track performance accurately, and adapt to market changes swiftly. Sales capacity planning involves predicting future hiring needs and balancing recruitment, ramp-up times, and churn. Effective territory planning can enhance overall sales team efficiency by 40%.

3. Salesperson Perspective

Clearly defined territories mean less overlap and conflict for salespeople, leading to higher motivation and productivity. Sales territories also provide a clear framework for sales compensation and career development. A well-designed sales territory plan can boost salesperson productivity by up to 25%.

Additional considerations in sales territory planning

1. Frequency of Territory Updates

Regular updates to sales territories are essential to reflect changes in the market and business priorities. Market conditions, customer needs, and competitive landscapes can evolve, necessitating adjustments to sales territories. For example, if a company expands into new geographic regions or introduces new products, it may need to reallocate resources and adjust territories accordingly. 

Finding the right balance between stability and flexibility is crucial. Frequent changes can disrupt sales activities and impact performance, while infrequent updates may lead to missed opportunities and inefficiencies. According to Spotio, updating territories quarterly can help maintain alignment with market dynamics and maximize sales effectiveness.

2. Impact on Compensation Structures

The design of sales territories can significantly impact sales compensation structures. Transparent and fair compensation plans motivate sales teams and align their efforts with company goals. Changes to territories can affect how sales representatives are compensated, potentially leading to adjustments in commission structures, bonuses, and performance metrics.
Ensuring that compensation plans remain competitive and attractive, even as territories evolve, is essential. Companies should regularly review and adjust compensation structures to reflect territory changes and maintain alignment with overall business objectives. Data from Xactly indicates that aligning compensation with territory performance can lead to a 15% increase in sales results.

3. Trade-offs in Territory Planning

Every approach to sales territory planning involves trade-offs. Static territories offer stability but may lack flexibility, while dynamic territories provide adaptability but can be complex to manage. Companies must evaluate their specific needs, market conditions, and business objectives to determine the best approach for their sales teams.
Trade-offs include balancing the need for specialized expertise with the desire for a more flexible and responsive sales strategy. Companies should consider each approach's potential benefits and drawbacks and make informed decisions based on their unique circumstances.

Types of Sales Territories for SaaS Companies

Sales territories for SaaS companies can be defined in multiple ways depending on the nature of your business, products, and buyers.

Let’s explore the most common SaaS sales territory structures with real-world examples:

‍1. Geographical Territories

Geographical territories have been a traditional approach where sales regions are defined based on physical locations. This method is still relevant for physical and high-value digital products requiring face-to-face interaction. For instance, a company selling agricultural equipment may divide its territories based on states or regions, ensuring sales representatives can visit farms and build strong relationships with farmers. Similarly, pharmaceutical companies often define territories based on healthcare regions, allowing sales reps to develop in-depth knowledge of local healthcare providers and regulations. A study by HubSpot shows that geographical territories can help reduce travel costs by 20%.
Geographical territories also offer several advantages. They simplify logistics, reduce travel costs, and provide a more focused approach to local marketing efforts. However, they can also present challenges, such as unequal distribution of potential customers or varying market potential across regions. Companies must regularly analyze market data and adjust territories to address these issues.One notable example is Amazon Web Services (AWS), which might sell to various sectors with differing needs. By defining sales territories based on industry, AWS can provide specialized services and solutions tailored to each sector's unique requirements.

2. Industry-Based Territories

Industry-based territories focus on sectors such as government, airlines, and telecom. This approach requires a deep understanding of industry-specific use cases and relationships. Sales teams become experts in the needs and challenges of their assigned industries, enabling them to offer highly relevant solutions. For example, a technology company might have dedicated sales teams for the healthcare, finance, and education sectors, each with tailored messaging and product offerings. Spotio highlights that industry-based territories can lead to a 25% increase in conversion rates due to specialized knowledge.Industry-based territories allow for a more targeted approach to sales. Sales representatives can speak the language of their industry, understand regulatory requirements, and build strong relationships with key stakeholders. This expertise can lead to higher conversion rates and increased customer loyalty. However, significant investment in training and development is required to ensure that sales teams are well-versed in industry-specific knowledge.‍

3. Customer Type Territories

Defining territories based on customer types involves segmenting the market by customer size, purchase behavior, or lifecycle stage. This method allows sales teams to tailor their strategies to the unique requirements of different customer segments, whether small businesses, large enterprises, or key accounts. For instance, a software company might assign sales teams to small, mid-sized, and large enterprises, each with distinct needs and buying processes. Small businesses require more straightforward solutions and cost-effective pricing, while large enterprises may need customized solutions and dedicated support.Customer-type territories enable sales teams to specialize in addressing each segment's unique challenges and opportunities. This specialization can improve the relevance of sales pitches, enhance customer satisfaction, and drive better results. However, it also requires careful segmentation and may lead to a more complex management structure.

‍4. Product Type Territories

Product-type territories assign sales teams to specific product lines or services. This approach is efficient for companies with diverse product portfolios. Sales teams can develop deep expertise in their assigned products, providing better support and driving higher sales. For example, a company that sells various types of industrial machinery might have separate sales teams for each product line, such as forklifts, cranes, and conveyor systems.
Product-type territories allow for a focused approach to product management and sales. Sales representatives can become experts in their assigned products, better understand customer needs, and offer more specialized solutions. However, this approach may require additional resources and coordination to ensure that sales efforts are aligned with overall business goals and that customers receive comprehensive support across product lines.

5. New Business vs Renewals Territories

An account can also be divided between new business reps focused on landing net new customers and renewal reps who manage ongoing subscription revenue.

New business requires more outbound prospecting while renewals need customer success skills. Separate territories prevent mixed focus.

6. Channel Sales Territories

If part of your sales goes through reseller partners, you can have dedicated partner account managers aligned to them.

For example, having an APAC channel partners territory manager who handles all partnerships in that region and works to grow revenue.

7. Named Accounts Territories

Larger SaaS firms often assign strategic accounts like Fortune 500 companies to specific reps who can customize solutions for them.

These named account territories get all the sales and marketing resources required to land massive deals.

As you can see, SaaS sales leaders have many options to define territories based on their unique situation and customer landscape.

How to Create an Effective Sales Territory Plan

Creating an optimal sales territory plan is crucial yet complex. There are many factors to consider and steps involved.

Let's go through a comprehensive, step-by-step process for designing a sales territory plan that drives growth:

Step 1: Define Your Objectives

Start by clearly defining the objectives of your sales territory plan. Are you looking to increase market coverage, improve customer satisfaction, or boost sales in a particular segment? Understanding your goals will guide the entire process.

Step 2: Analyze Market Data

Conduct a thorough analysis of your market data. This includes identifying potential customers, understanding market trends, and assessing the competition. Use data analytics tools to segment your market based on relevant criteria such as geography, industry, or customer type.

Step 3: Segment Your Market

Based on your market analysis, segment your market into manageable sections. Ensure each segment is large enough to justify dedicated resources but small enough to allow personalized attention. This segmentation will form the basis of your sales territories.

Step 4: Assign Sales Teams

Assign your sales teams to the defined territories. Consider factors such as team expertise, experience, and workload. Ensure each team has the necessary resources and training to succeed in their assigned territories.

Step 5: Set Goals and Metrics

Establish clear goals and metrics for each territory. These should align with your overall business objectives and provide a basis for performance evaluation. Regularly review and adjust these goals to reflect changes in the market and business priorities.

Step 6: Implement and Monitor

Implement your sales territory plan and continuously monitor its performance. Use CRM systems and other sales tools to track progress, identify issues, and make data-driven adjustments. Regular feedback from sales teams is crucial to refine and optimize your territories.

Remember to make iterative changes when it comes to sales territories to allow your sales reps time to adjust. You do not want to make knee-jerk changes that disrupt the working processes your sales teams follow.

Static vs. Dynamic Sales Territories

1. Static Sales Territories

Static territories consist of a fixed set of accounts for a specified period. This approach provides stability and allows sales teams to build long-term customer relationships. However, it may need to be more responsive to market changes and evolving customer needs.

2. Dynamic Sales Territories

Dynamic territories adjust based on market changes, customer intent, and sales performance. This approach is more flexible and can respond quickly to new opportunities or challenges. Companies like 6sense are known for their dynamic sales territories, constantly using advanced analytics to optimize territory assignments.

Detailed Real-world Examples and Case Studies

1. AWS's Industry-Based Territories

Amazon Web Services (AWS) is a prime example of a company that uses industry-based sales territories. AWS segments its sales teams based on various industries, including healthcare, finance, and government. This approach allows AWS to tailor its solutions and sales strategies to each sector's needs and regulatory requirements.

By focusing on industry-specific sales territories, AWS can leverage its expertise and build strong relationships with key stakeholders in each sector. This specialization enhances AWS's ability to address complex industry challenges and drive successful customer outcomes.

2. Salesforce's Dynamic Approach

Salesforce employs a dynamic approach to sales territory planning, using advanced analytics to optimize territory assignments. The company monitors market conditions, customer intent, and sales performance to adjust its territories in real-time.
Salesforce's dynamic approach allows it to respond quickly to market changes and seize new opportunities. By leveraging data and analytics, Salesforce can ensure that its sales teams are always focused on the most promising prospects and regions.

3. 6sense's Use of Advanced Analytics

6sense is known for its innovative use of advanced analytics in sales territory planning. The company uses data-driven insights to define and adjust sales territories, enabling its teams to focus on high-potential opportunities and optimize their efforts.
6sense's approach highlights the importance of leveraging data and analytics to drive effective sales territory planning. Using advanced tools and techniques, 6sense can continuously refine its territories and achieve better results.

How Factors Helps Optimize Territories

Factors is an AI-powered Account intelligence & analytics platform that can help maximize the potential of sales territories:

1. Enriches Anonymous Traffic

Factors enriches anonymous website visitors and ad impressions with company data—revealing the company name, industry, location, and other attributes you can use to map accounts to matching sales territories.

2. Automatically Assigns Accounts to Territories

Once Factors discovers the right data, like the location, industry, account size, etc, it automatically assigns the accounts to the right reps based on the territory definitions in your CRM. You no longer have to manually assign a rep every time there’s a new lead in the system. 

3. Alerts Reps About Territory Accounts

Factors helps you automatically alert users when there are new accounts identified. You can set up Factors to automatically message users on Slack informing them about the new account. 

The best part is, Factors continuously monitors your website and other connect platforms for new leads. Your reps are alerted as soon as a new lead hits Factors (in real-time) so they can act upon the leads while they’re hot. 

4. Provides 360-Degree Territory Account View

Factors unifies cross-channel account data to provide a 360-degree view of territory accounts—including web activity, ad impressions, intent data, CRM interactions etc.

5. Enables Data-Driven Territory Optimization

It analyzes territory performance across metrics like engagement, pipeline velocity, and more. This allows data-driven planning and optimization of territories.

With Factors, you can leverage previously untapped anonymous interactions to drive more territory leads. Continuous optimization of territories also becomes easier based on hard data vs guesswork.

Key Takeaways

• Sales territories optimize market coverage, sales efficiency, and account management for your team. Ways to define territories include geographic, industry, size, products, or channels.
• Steps for creating a territory plan include choosing territory types, mapping target accounts, estimating potential, setting goals, assigning territories, configuring lead routing, and tracking performance.
• When assigning territories, take rep strengths into account, involve reps in planning, make data-driven decisions, and limit frequent realignments.
• Specialized software provides visibility into sales territories and makes territory management efficient.
• Factors enriches anonymous traffic to assign accounts to territories. It also unifies data across channels for continuous optimization.
• Well-planned sales territories ensure your reps have reasonable workloads and can nurture the right accounts. Combined with the right technology, sales territories provide immense leverage to scale revenue growth. 
  

Map Your Path to Sales Success with Sales Territories

Territories allow reps to go “all-in” on targeted accounts instead of spreading themselves thin. This results in higher win rates and accelerated revenue growth.

But territory success depends on getting the fundamentals right.

Choose appropriate territory characteristics based on your business model, products, and customers. Involve reps in co-creating territory plans that align with their strengths. Set up your CRM to automatically route inbound leads to the right reps. And continuously track and optimize territories based on hard data.

Factors plays a critical role here. It enriches anonymous website traffic to identify and assign accounts to matching sales territories automatically. Cross-channel analytics further fuel data-driven territory optimization.

With Factors, you can leverage previously untapped traffic to generate more territory leads on auto-pilot. It connects the dots across customer touchpoints to uncover revenue opportunities hidden within your data.

So if you're struggling with sub-optimal territory planning, take control of your revenue engine. Book a customized Factors demo today to see how it can help optimize your sales territories.

On average, it's 5 times more expensive to acquire a new customer than retain an existing one.

There's no doubt that your current customers are your most important assets. But traditional customer metrics such as CAC and churn don't provide visibility into the whole picture of customer sentiments. This is where net dollar retention comes in. 

Net dollar retention (NDR) is an invaluable SaaS metric that helps evaluate the health of your customers and in turn, the health of your business. 

This article explores everything you need to know about NDR.

TL;DR:

• NDR helps determine the revenue retained from existing customers after considering churn and expansion
• Calculating net dollar retention helps identify blockers in your growth like poor product fitment or low customer engagement
• The median NDR for private SaaS companies is 105%
• Improve NDR with better Customer Success operations, user analytics and sales-CS alignment
• Factors.ai can improve sales-CS alignment with account intelligence features

What is Net Dollar Retention?

Net dollar retention is a metric that measures the rate of change in annual recurring revenue over a defined period of time.

The value of NDR helps determine the revenue retained from existing customers after considering churn and expansion.

It's a metric that quantifies customer success in terms of revenue retention, helping you evaluate what percentage of your recurring revenue you’ve retained and if you’ve been able to grow that value over time.

how to calculate net dollar retention?

‍NDR = (ARR at the start of the year - Churn - contraction + Expansion) / ARR at the start of the year

Let's say you want to calculate the NDR for the year.

At the beginning of the year, you have 100 customers, each paying $1,200 per year. So, your Annual Recurring Revenue (ARR) at the start of the year is 100 customers * $1,200/year = $120,000/year.

During the year, you experienced some changes:

Churn: 5 customers decided not to renew their subscriptions, resulting in a loss of $6,000 in ARR.

Expansion: However, you managed to upsell 10 existing customers to a higher-tier plan, each paying an extra $600/year, resulting in an additional $6,000 in ARR from expansion.

So your NDR is:

NDR = {($120,000 - $6,000 + $6,000) / $120,000} * 100, which is 100%.

This means that, on average, you retained and expanded revenue from your existing customer base, offsetting the revenue lost due to churn. An NDR higher than 100% signifies growth in recurring revenue, while a value below 100% signifies a loss in recurring revenue.

NDR can also be calculated for each month using MRR instead of ARR in the formula:

NDR = (MRR at the end of the period - Churn + Expansion) / MRR at the start of the period.

This helps track changes in revenue on a monthly basis.

Why Is NDR Important For SaaS?

When SaaS startups reach the growth stage, they struggle to break the chasm of early adopters. A chunk of revenue is generated through customers who are looking for new technology to experiment with. You’ll have to experiment with pricing strategies, messaging, and deal with higher churn in the early stages of your business. This means that simply measuring unit metrics like churn gives you a rather pessimistic view of your operations. To add to that, your customer success teams bear the brunt of this limiting perception of revenue generation.

Net dollar retention is a cohort-based metric. It allows you to focus your efforts on your most valuable customers. As the company scales, it becomes imperative to identify the sources of recurring revenue and optimize your operations to better serve such customers. Periodically calculating net dollar retention helps identify any blockers in your growth. A low NDR can be caused by high churn and/or limited expansion. This could signify any of the following:

1. Low Customer Engagement 

A low NDR can be attributed to the fact that a significant portion of users did not fully engage with the software during the free trial period, or failed to derive substantial value from it. This lack of customer engagement often results in a reluctance to upgrade, leading to missed upselling opportunities. A diminished NDR necessitates an enhancement of customer success operations, a thorough examination of the signup process, or a refinement of the onboarding and training procedures.

2. Poor Product Fitment 

A low NDR may also signify problems in the product-to-market fit. If churn is high and leads to a reduced NDR, it may be time to reevaluate the product offering and set up thorough feedback loops to understand the customer’s needs better. Similarly, if there is little revenue generated from expansion opportunities, it contributes to a low NDR. It can imply that customers are not convinced of the value addition in upgrades, and the product offerings should be reevaluated.

3. A Key Metric for Investors

NDR plays an important role in investors' decisions. A healthy NDR indicates that you have a strong product-to-market fit and the solution resonates with the intended audience. It serves as a predictor of future growth, as it is a strong indicator of scalability and long-term viability, making it a key factor in investment decisions.

Net Dollar Retention Benchmark: What’s A Good NDR?

A report published by RevOps determined that the median NDR for private SaaS companies was 105%, with the 75th percentile falling above 110%.

If your NDR is close to 105%, you’ve got nothing to worry about. If it is above 110%, there’s cause for celebration. And if you’re below 100%, you should look into ways to improve retention.

The report further suggested that the NDR is not materially correlated with the company size, as it is with other variables including Go-To-Market motion (Product-Led Growth vs. Sales-Led Growth) and pricing model (pure subscription versus Usage-Based Pricing).

5 Ways To Improve Net Dollar Retention

A happy customer will stay with you. A delighted customer will grow with you. A low NDR shows that your customers do not see value in your product offerings or are struggling to derive value from it.

This could be because of poor training, creating a longer learning curve. Maybe the customer opted for more features than they needed, and now they feel overwhelmed when using the tool. Maybe the product isn’t intended for a company that size, or they don’t see the appeal of upgrades. There are ways to improve the user and post-sales experience to:

1. Invest in Customer Success 

Customer success often takes a backseat when we think of revenue generation. However, customer success teams enjoy the strongest bonds with customers and should be encouraged to identify and capitalize on these opportunities. Allocate resources to strengthen your customer success team to ensure that they can contribute to the NDR.

2. Use Product Analytics Amongst Power Users 

Analyze the behavior of your most engaged users to identify features or workflows that resonate with your ideal customer profile. This will help you narrow down your positioning and attract more high-value customers. These insights may also be leveraged to guide your product road map to ensure high adoption and lengthy customer lifecycles. 

3. Keep Customers Involved 

Engage customers through regular communication, interviews, feedback mechanisms, and user groups to understand evolving requirements and expectations. 

4. Optimize Contract Terms Based on Customer Preferences

Offer flexible contract terms and pricing options that align with different customer needs and preferences, promoting upsell opportunities. This will promote customer delight and lead to higher retention rates or open doors for expansion.

5. Look Into Sales-Customer Success Alignment 

One of the key and often overlooked factors in customer success is its alignment with sales and marketing functions. Having first-hand access to customer feedback, customer success teams are equipped to identify the most serviceable customers. The customer success team can help align your messaging and sales efforts to speak to target the ideal customer profile for your business. Aligning the marketing, sales, and customer success functions will help you identify the customers you can serve best, consequently leading to lower churn and higher NDR.

How Factors Helps Improve Net Dollar Retention?

Most businesses chase sales-qualified leads. But getting a sale is only half the battle won. Ensuring a good customer experience, customer satisfaction, and customer retention are equally important for a better NDR. It is crucial to ensure that efforts prioritize CS-qualified leads over sales-qualified leads. While marketing and sales can bring in many customers, focusing on the most serviceable ones will help you scale faster. With Factors.ai's account intelligence and analytics, you can identify the right, high-intent accounts with longer retention, higher growth, and optimized NDR. 

Factors can identify up to 64% of anonymous accounts visiting your website, engaging with product reviews, or viewing your LinkedIn ads. Its event-based data model helps you identify the most effective messaging and marketing touchpoints.

Net Dollar Retention FAQs

Q: What is the net dollar retention formula?

A: Net Dollar Retention (NDR) = ARR at the start of the period - the revenue lost due to churn + the revenue generated through Expansion (cross-sell, upsell, etc.) divided by the ARR at the start of the period.

Q: What does 100% net dollar retention rate mean?

A: 100% net retention signifies that a business retains and expands revenue from existing customers, offsetting any losses from churn.

Q: What’s The Difference Between GDR and NDR?

A: GDR (Gross Dollar Retention) measures total revenue retained from existing customers, while NDR (Net Dollar Retention) considers revenue lost to churn and gained from expansion, providing a more precise growth indicator

‍If you could build the perfect B2B customer in a lab, what would they look like? What industry would they be from? How big would they be? What technologies would they use? 

Building an ideal client profile helps answer these crucial questions and more — albeit with fewer beakers, and more data-driven market research.

The following article highlights everything you need to know about ideal client profiles: definitions, differences, benefits, and most importantly, how to build one for your company. 

Let’s dive in. 

What is an ideal client profile? 

An ideal client profile (ICP) is a detailed representation of a perfect customer for a company based on a range of characteristics including demographics, firmographics & technographics. 

Building (and iterating upon) an ideal client profile helps businesses better understand what their main audience looks like. This results in more effective targeting, outreach & conversions. 

If you’re selling chicken eggs, you probably don’t want to run ads to online vegan communities. They’re hardly a good fit for your business. Instead, you’ll find better luck running ads to fitness enthusiasts looking for a protein-rich diet. Certainly, targeting the latter will result in a superior return on investment and happier, more satisfied customers. A win-win! 

Ultimately, your ideal client profile should be the type of customer you can provide the most value to and, in turn, can generate the most value for your company. 

Unfortunately, defining an ideal client profile isn’t as clear cut in SaaS as it might be in the poultry industry. In later sections, we explore how to go about constructing your ICP in detail. 

How is ICP different from target audience?

Ideal client profile and target audience are closely aligned, but distinct terms nonetheless. Generally, target audience refers to a broader audience that shares certain high-level commonalities such that they may benefit from what a company offers. An example of a target audience may be something like: mid-sized companies in healthcare and financial sectors. 

Ideal client profile picks up on this and goes the extra mile to cover what this “target customer” may look like in far greater detail — including the nature of use-cases, pain-points, technologies, and decision makers involved. In a way, your ICP is a subset of your target audience. 

Let’s take an example. Factors is an account intelligence software that helps B2B teams identify, qualify, and convert anonymous accounts visiting their website. This empowers better outbound efforts, retargeting campaigns and pipeline growth. 

At an immediate glance, the target audience would be GTM teams from SaaS companies. Taking it a step further, however, we can say that Factors’ ideal client profile — that is, clients that will derive and provide the most value from our work — would be SME SaaS marketing and sales teams with significant ABM efforts, marketing spend & high-quality anonymous website traffic. 

This gives us a specific market to go after. 

Here’s an example of an ICP from Cognism: 

What are the benefits of ideal client profile? 

There are several benefits to identifying the characteristics that make your ideal customer, ideal. Here are a few. 

1. Better personalization: A deep empathic understanding of your ideal market’s traits, motivations, pain-points, and everyday workings will empower a far more personalized, tailor-made buying experience. Relevant campaigns, content, and conversations will go a long way in building fruitful relationships with potential customers and a positive brand image. 

2. Better GTM performance: Without knowing who to target, marketing and sales teams often resort to expensive, ineffective spray & pray tactics — spammy blast emails, tangential cold calls, irrelevant ad campaigns. By building out a detailed, well-researched ICP, we can ensure thoughtful, more persuasive go-to-market efforts resulting in better ROI and pipeline growth. 

3. Better internal alignment: A clear, internal alignment as to who you’re targeting will result in operational efficiencies across marketing, sales, product, and customer success teams. An ICP provides unequivocal direction as to who we’re helping and how we’re helping them. 

How to build an ideal client profile: 4 simple steps

Defining your Ideal Customer Profile (ICP) isn't a one-size-fits-all process. It's a journey that involves careful consideration of various factors, including your company's goals, vision, and the stage of growth you find yourself in.

What remains constant is the core principle of defining your ICP: It's all about value

Defining your ICP should solely focus on how a potential customer participates and generates value for your organization. This value can be in the form of revenue, but it can also extend beyond the financial aspect, impacting your company in various other ways:

For example, in early stages, especially before the creation of a minimum viable product (MVP), you should seek early adopters who are willing to experiment with your solution. These customers may provide valuable feedback, helping you refine your offering. However, many companies struggle to cross the chasm and identify their most valuable customers at this stage.

As you progress to the growth stage, your ICP shifts. Now, you're looking for buyers who can provide testimonials and help you gather social proof, building trust in your product. You start evaluating the value these clients bring, factoring in Customer Lifetime Value (CLV) to test product fitment. It's a stage focused on customer satisfaction and building credibility.

But in the later stages, your ICP evolves yet again. Here, you're targeting customers with high lifetime value, those who not only contribute revenue but also showcase unwavering loyalty. These are the customers who become your advocates, providing referrals and further strengthening your brand.

So how do you write an ideal client profile? Here’s the 4-step process:

1. Identify your best customers
2. Conduct research & interviews
3. Compile learnings, build profile
4. Iterate. Iterate. Iterate. 

1. Identify your best customers 

Start by making a list of 5-10 of your best, most-valuable customers. This list should be made up of accounts that actively use and derive value from your product. They should be made up of relevant stakeholders — i.e. decision makers and end users that are familiar with the problem your solution solves for. 

If you’re at an earlier-stage, simply reach out to your network and marketing communities to request a quick conversation (remember, you’re not trying to sell them your product here. Simply learn more about what makes them tick). 

2. Conduct research & interviews

Dig deep to learn everything you can about these customers. Raid websites, LinkedIn pages, Slack communities, competitor product reviews and anything else you can get your hands on. Look to identify your customers:

• Industry 
• Techstack
• Revenue
• Headcount
• Location
• Budgets
• Growth

Once secondary research sources have been exhausted, set-up interviews for qualitative conversations on the motivations, pain-points, and everyday routines of your ideal buyer. Remember, this is your chance to get personal. Avoid generic, or worse yet, leading questions. Here are some questions to consider asking:

• As a {end user role}, what’s the most challenging aspect of what you do?
• What KPIs/Metrics do you care about most? 
• How successful is your team in achieving quarterly targets? In your experience, what goes right and what goes wrong? 
• What is expected of you by your leadership? 

The Mom Test is a great read on how to structure interviews to be effective and unbiased. 

3. Compile learnings, build profile

At this stage, consolidate all your learnings across research, conversations, and anecdotal evidence into a big fat document. Carefully study your findings on your ideal customers and refine the results until you’re left with a masterpiece: an ideal client profile!

4. Refine. Refine. Refine.

Defining your ideal client profile is an ongoing process that must never end. As markets, consumers, businesses, and products continue to evolve, so will the characteristics and expectations of your perfect customer. 

It’s important to regularly go back to the drawing board and refine the details of your ICP. This will ensure you keep up with the times and stay perpetually relevant, fresh, and successful. 

Ultimately, your ICP should be simple to understand, align with your marketing and sales strategies, and help you achieve your goals. 

Win more ICP accounts with Factors

You have your ideal client profile all-set. Now what? Factors is an account intelligence and analytics solution that helps identify, qualify, and convert anonymous ICP accounts engaging with your website. 

{{CTA_BANNER}}

Only about 4% of website traffic reveals itself through form submissions. We can’t let the remaining 96% of anonymous pipeline go down the drain, can we? With Factors, you can:

1. Identify up to 64% of anonymous accounts visiting your website, engaging with your product reviews, or simply viewing an ad — with industry-leading IP-lookup technology. 
2. Qualify the right accounts by configuring custom firmographic and engagement filters so you’ll be notified when sales-ready ICP accounts are visiting your, say, pricing page.‍
3. Convert in-market accounts while the iron’s still hot with real-time alerts sent straight to your Slack or MS teams. Track account engagement and reach out with intent-based outreach or retargeting campaigns. Either way, you’ll be winning ICP accounts like never before.

Navigating Sales In Early-Stage Start-Ups

Building pipeline and scaling sales as a startup is not easy. 

Learn about the challenges with navigating sales in early-stage start-ups — and how to overcome them. Understand the power of account-based sales with Praveen Das, Co-founder of Factors.ai and Ankit Jain, Co-founder of Clearfeed. 

What we’ll cover:

• Common challenges startups face when they begin their sales journey.
• How high-growth teams like Clearfeeder overcome these challenges.
• And why account-based sales is important for early-stage businesses.

Q. As an early-stage company, you have an unknown brand. Your product-market fit is yet to be achieved. Your ICP is evolving. And there’s limited tooling and team bandwidth. Getting to those first 20 customers might seem…impossible. How should you go about it? What was that journey like?

A. Startups are like hourglasses. You start with very broad ideas and segments. Then starts the journey of going as narrow as possible: “we serve this one ICP in this one segment”. And finally, you achieve growth. 

1. We identified 4-5 segments we care about. Within those segments, we identified a list of relevant, high-level problems our technology could solve. 
2. Then, we performed customer discovery by reaching out to about 200 people in each of those segments to validate our problem-statements.
3. After these conversations, we identified a “pull” towards one of these segments (Customer success teams from series B dev/infra SaaS start-ups using Slack) and ran with it.
4. Based on this insight, we built a product that this specific niche of people loved — which gave us our initial boost in customers based on referrals and virality.

Q. At this stage, what did your go-to-market engine look like? Was it mostly outbound or inbound? How did you go about GTM? 

A. At this point of time, we didn’t have a market team. It was just the founders and a few engineers so there was no question of inbound. 

The other consideration was whether we’re creating a category or are in an established category. If it’s the latter, you can “buy your way out”. We didn’t have this back then, so it was primarily an outbound motion:

1. A list of 3500 ICP accounts based on firmographics and technographics
2. Reach out via sequences of mails, calls, and LinkedIn
3. This approach helped land 8 meets per month, out which 2-3 convert. 

A quick break from questions to discuss engagement-based sales models…

Engagement-based sales is a sales strategy that focuses on targeting highly engaged accounts and customizing the sales approach to fit the needs of each account (As opposed to a cold approach). 

For context, the “old way” involved a standard process of defining ICP accounts, researching target accounts, reaching out to contacts within those accounts, and measuring success with KPIs.

The challenge with this is approach is:

1. Researching target accounts involves several hours of tedious effort
2. Measuring success with KPIs involves pulling data from disparate sources
3. AND you’re missing out on anonymous accounts that are already engaging with your brand

This is where Factors.ai comes in. Factors identifies and unifies hidden account data across ad campaigns, product review site, website, and CRM to capture demand, monitor engagement, and personalize outreach & nurturing. 

Engagement-based sales is the new way. Here’s how Factors helps:

1. Identify anonymous inbound traffic across channels
2. Track granular account engagement to measure intent
3. Personalize outreach based on engagement and intent
4. Finally, measure marketing & sales KPIs under one roof

Ankit and Clearfeed’s experience with Factors and the new approach

“Why aren’t we personalizing outreach to improve response rates?” is a standard question amongst founders and the standard answer is usually “it takes a lot of time to meaningfully personalize outreach”. 

Then, the question was “how can we find which accounts are most engaged, so we can personalize outreach to them alone?”. Seems reasonable. So with Factors, we identified accounts from our top of the funnel awareness campaigns as well as organic traffic from educational content assets. 

This set of accounts were, at the very least, problem aware. SDRs could now prioritize personalized outreach to this set of “higher-intent” accounts. This has resulted in a 5x improvement in response rate and our ability to book outbound meetings. Real-time alerts with Factors also helps with speed to response rates. These insights are also signals on what accounts care about or why they’re visiting our website. 

Read more about how Clearbit leverage Factors here: factors.ai/customers/clearfeed

Other tips to improve outbound performance include:

1. Achieve a comprehensive understanding of target accounts through their website, customers, growth, and other signals
2. Pinpoint the exact channels your ICPs prefer (LinkedIn, mail, calls, communities, etc) 
3. Keep experiment and iterating on bottlenecks, wins, and learnings

Q. Today, Clearfeed is further along its growth journey — running ads, content, etc. How has Factors come in handy at this stage?

A. As a founder, I always want to know what’s working. With Factors, we can see what accounts that have converted interacted with pre-sales. What are their touchpoints? What pages have they visited? What topics resonate most? and more. This helps guide our content strategy, paid strategy and beyond. 

The Factors advantage for engagement-based sales may be summarized as…

1. Unified account data and scoring: Qualify and target the right accounts based on website engagement, intent signals, and firmographics
2. Advanced analytics: Optimize demand gen and content marketing investment‍
3. Real-time alerts: Stay on top of new ICP accounts and closed lost accounts showing engagement

You're a SaaS company looking to build and sell great products. But how many potential buyers are out there? How many ideal clients are currently in-market? And what sort of revenue can you expect to generate from this market? 

Measuring your Total Addressable Market is the first step in answering these questions and building a sustainable business. This article highlights everything you need to know about TAM: what it is, how to measure it, and how to analyze it for optimized growth.

What is Total Addressable Market?  

Total Addressable Market (TAM) refers to a company’s maximum potential revenue opportunity. It’s the total amount of sales that can possibly be done by a business based on the market for a product. 

At a high-level, TAM can be calculated using the formula: TAM = total number of possible customers in the market x annual contract value of each customer

For example, let’s take a project management software tool for small and medium-sized businesses (SMBs). Given that there are 2 million SMBs in the world, and each one spends $1000 a year on project management tools, the Total Addressable Market for this product would be 2M X $1000, or $2 billion.

In other words, TAM represents the revenue generated by the company if it captures 100% of the market share. Of course, this is just an estimate of the size of the market, without accounting for competitors, economic conditions, and countless other factors that will affect revenue generation. Yet, as the next section explains, TAM provides important directional insights to help your business grow. 

Why is TAM analysis important?

Calculating the total addressable market can serve different purposes at different stages of growth. At the ideation stage of a business, calculating the TAM helps assess the size and viability of the market for your product. If, for example, your TAM is only about $1 million, you’ll likely hit a ceiling for revenue growth within a few short years.  

As the company grows, understanding your total addressable market can support the direction of your company road map. TAM helps evaluate the size of your market when considering new product features, priorities, channels and revenue streams over time. Whether it’s geographic expansion, product development, or forward integrations, TAM helps project growth in later stages of your startup’s journey. 

At any point in your company’s growth, knowing your total addressable market will help evaluate how much of the market share you’ve successfully captured. It helps create healthy expectations and achievable benchmarks for your team and your company. 

A Step-By-Step Guide on How to Calculate TAM

There are three popular methods to calculate TAM: the top-down approach, the bottom-up approach, and the value theory approach. Each method is uniquely helpful based on the scenario. 

1. Top-down approach: This is best suited for early-stage teams looking for a preliminary assessment of the viability of entering a market. 
2. Bottom-up approach: This is best suited for high-growth startups that can leverage insights from historical customer data and revenue trends.
3. Value-theory approach: A third TAM analysis that considers the potential value that customers derive from a product and service, and it helps back-calculate the total addressable market accordingly.

Top-Down Approach

In this method, the initial consideration revolves around estimating the price for the product. This value is subsequently multiplied by the total number of prospective customers. 

A company that is looking to evaluate the need for their product can rely on this approach to estimate market share. It is also a great way to establish a profitable business model when looking for investor funding. 

To illustrate this concept, let's take the example of a SaaS CRM product targeting small and medium-sized businesses (SMBs). Here is a simplified version of the top-down approach when calculating TAM:

Step 1: Define the Parameters

Market Definition: The market we're interested in is the CRM software market for SMBs.

Market Size Data: Research indicates that there are approximately 30 million SMBs.

Average Annual Spend: On average, SMBs spend around $1,000 per year on CRM software.

Step 2: Calculate TAM

Now, we can calculate the TAM using the top-down approach:

TAM = Total Number of Potential Customers × Average Annual Spend per Customer

TAM = 30 million SMBs × $1,000 per year

TAM = $30 billion per year

Step 3: Interpretation

The TAM for this SaaS CRM product for SMBs is approximately $30 billion per year. This figure represents the maximum market potential without any constraints. It indicates that if the SaaS company could capture 100% of this market, its annual revenue potential could reach $30 billion.

Bottom-Up Approach

The bottom-up approach involves defining your target customers, estimating revenue per customer, and then extrapolating this revenue across your entire target market to calculate TAM. It's a detailed and customer-focused method that can be valuable for SaaS companies looking to assess their market potential with a high degree of specificity.

Using the same example,

Step 1: Identify Your Target Customer Base

In the bottom-up approach, you start by identifying your target customer base precisely. For a CRM company, even though its ideal target audience is SMBs, it may not be suitable for certain industries, where the sales cycle is very short and there are no repeat purchases. Hence, we might boil down the customer base to SMB B2B companies alone.

Step 2: Calculate the Average Revenue per Customer

Next, calculate the average revenue per customer. You might consider factors such as pricing tiers, subscription models, and any additional services or upsells. Let's assume the SaaS company offers three pricing tiers for its CRM software:

• Basic Tier: $20 per user per month
• Standard Tier: $50 per user per month
• Premium Tier: $100 per user per month

Assuming an average of 10 users per SMB subscribing to the CRM software, we can calculate the average monthly revenue per customer:

Average Monthly Revenue per Customer = [(Number of Basic Tier Customers × $20) + (Number of Standard Tier Customers × $50) + (Number of Premium Tier Customers × $100)] / Total Number of Customers

Step 3: Estimate the Number of Potential Customers

Now, estimate the number of potential customers in your target market. For this example, let's say there are approximately 5 million B2B SMBs to target:

Step 4: Calculate TAM

With the average monthly revenue per customer and the estimated number of potential customers, you can calculate TAM for the CRM software:

TAM = Average Monthly Revenue per Customer × Number of Potential Customers × 12 (to get the annual figure)

TAM = [(Number of Basic Tier Customers × $20) + (Number of Standard Tier Customers × $50) + (Number of Premium Tier Customers × $100)] / Total Number of Customers × Number of Potential Customers × 12

Value Theory Approach

In the value theory approach, you are essentially calculating TAM by assessing the value proposition of your SaaS product to different customer segments and estimating their willingness to pay based on the perceived value. This approach provides a more customer-centric and value-focused perspective on market potential, allowing you to tailor your pricing and marketing strategies to different customer segments based on varying needs and expectations.

Using the same example,

Step 1: Identify Customer Segments and Their Needs

Begin by identifying different customer segments within your target market and understanding their specific needs. For our SaaS CRM software, customer segments might include small businesses, medium-sized businesses, and startups.

Step 2: Quantify the Value Delivered

For each customer segment, assess the value your CRM software provides. This value could be quantified in various ways, such as increased productivity, improved customer relationships, time savings, or cost reductions. For example:

Small businesses may value the CRM software for streamlining their sales processes, resulting in increased sales and revenue.

Medium-sized businesses may value the software for better customer data management, leading to more effective marketing campaigns and customer retention.

Step 3: Estimate the Willingness to Pay

Determine how much customers in each segment are willing to pay for your CRM software. This can involve conducting surveys, market research, or analyzing competitors' pricing strategies. Let's assume that small businesses are willing to pay an average of $50 per user per month for the CRM software, while medium-sized businesses are willing to pay $100 per user per month.

Step 4: Calculate TAM

Now, calculate the TAM for each customer segment by multiplying the number of potential customers in that segment by the average monthly revenue per customer:

TAM for Small Businesses = Number of Small Businesses × Average Monthly Revenue per Customer for Small Businesses

TAM for Medium-sized Businesses = Number of Medium-sized Businesses × Average Monthly Revenue per Customer for Medium-sized Businesses

Sum up the TAMs for all customer segments to get the overall TAM for your CRM software:

TAM = TAM for Small Businesses + TAM for Medium-sized Businesses

Challenges with TAM Analysis

Calculating TAM using the bottom-up approach and the value theory approach is nuanced and relies heavily on historical data and a deep understanding of customer behavior. The analysis can present certain challenges, mainly:

Limited Data Availability

Gathering accurate data on the number of potential customers, their segmentation, and willingness to pay can be challenging, especially if there's limited market research available or if the industry is highly fragmented.

Pricing Complexity 

Determining the right pricing strategy and accurately estimating the average revenue per customer can be complex. It may require considering different pricing tiers, discounts, and the potential impact of competitors' pricing.

Inaccurate Customer Segmentation 

Identifying and categorizing different customer segments with precision can be difficult. Overlooking or misclassifying segments tend to lead to inaccurate TAM calculations.

Changing Market Dynamics 

Markets are dynamic, and customer preferences, needs, and behaviors will change over time. Keeping up-to-date data and adapting to evolving market conditions is easier said than done.

Data Bias

Data collection may suffer from bias, especially if the company relies on its own internal data, which might not capture the full spectrum of customer opinions and experiences, which is required to carry out a value theory analysis.

And there you have it!

Needless to say, in an incredibly competitive SaaS environment, even the most successful companies capture the attention of only a fraction of their TAM. And an even smaller subset of these accounts actually become customers. In fact, even the most optimistic benchmarks find that only 4% of website traffic converts through sign-ups. Factors helps identify, qualify, and convert the remaining 96% of anonymous accounts visiting your website — so you can capture more of your TAM, than ever before. Learn more about Factors here:

How well do you know your leads? With various marketing channels, leads come pouring in from multiple places daily. But how can you tell which ones are primed to convert and which still need nurturing? 

Enter lead scoring—a crucial mechanism for identifying and prioritizing your most promising leads.

This post will explore the ins and outs of lead scoring in marketing automation software. We'll use HubSpot as an example to illustrate how lead scoring works, best practices for setting up and optimizing your lead scoring, and critical use cases for putting this powerful tool to work. 

Whether you already use a particular software or are just evaluating options, you'll learn fundamental principles of lead scoring to identify and prioritize your most promising leads. The result? More closed deals and faster revenue growth. Let's dive in!

Why Lead Scoring Matters

You have leads from your website, landing pages, online ads, email campaigns, and more. How can you quickly identify the most promising ones worth prioritizing? Relying on guesses won't cut it. 

You need a systematic way to distinguish hot leads from cold ones.

That's lead scoring —a quantitative way to qualify leads based on their level of sales-readiness. It assigns points to leads as they engage with your business and demonstrate buying signals. 

The more points, the hotter the lead.

However, not all scoring models are created equal. 

Many basic systems only look at a limited set of criteria or fail to adapt as leads progress through the buyer's journey. But HubSpot's approach gives you a more customizable and dynamic solution.

With the right lead-scoring strategy, you can:

• Identify hot leads—See at a glance which leads are sales-ready based on their activities. Focus energy on your hottest leads first.
• Nurture cold leads—Understand what criteria cold leads are missing to prioritize relevant nurturing.
• Improve conversions—Convert more leads by focusing on those already showing buying signals.
• Enhance personalization—Deliver personalized, timely experiences matched to each lead's score.
• Track performance—Monitor the impact of your lead scoring criteria over time. Tweak criteria as needed.

Now, let's dive into how scoring works in HubSpot specifically.

How Does HubSpot Lead Scoring Work?

HubSpot's lead scoring methodology is powered by two key components—criteria and weight. Let's explain how each contributes to a lead's overall score.

Scoring Criteria

The criteria component determines which lead attributes and behaviors add or deduct points from a contact's score. HubSpot's software comes pre-loaded with default criteria based on typical buying signals.

Example positive criteria include:

• Visited a pricing page
• Downloaded an ebook
• Clicked on a call-to-action

Examples of negative criteria include:

• Unsubscribed from emails
• Bounced email
• Page visited with keyword "competitor"

However, the criteria driving your lead scoring model can be completely customized based on your unique business. You may tweak the default criteria or add new ones that match your typical buyer's journey.

HubSpot makes it easy to update your lead scoring criteria at any time as your business evolves. Whether launching a new product, shifting target audiences, or identifying new buying signals, you can update criteria on the fly.

Lead Scores or Weightage

The second component determining a lead's score is the points assigned to each criterion.

When a lead meets a defined criterion, the associated points are added to their lead score. When negative criteria are met, the points are deducted.

You control the points for both positive and negative criteria. The higher the weight, the more significant the impact each criterion has on the overall score.

For example, you may assign 50 points for visiting a pricing page but only 10 points for downloading an ebook. This freedom to assign points for each action gives companies greater control over their lead scoring. 

HubSpot's flexible criteria and weighting system enables you to:

• Customize criteria based on your unique buyer's journey
• Continually fine-tune criteria as your business evolves
• Assign point values tied to each criterion's impact on indicating sales readiness

Let's walk through how to configure lead scoring in your HubSpot portal.

Setting Up Lead Scoring in HubSpot

HubSpot allows you to customize the default lead scoring system to match your unique business needs. The setup process is relatively straightforward but does involve some essential steps.

Step 1: Accessing Lead Scoring Properties

First, navigate to the Properties section under Settings. Here, you can view and edit the default scoring criteria. Marketing Hub Professional and Enterprise accounts get access to lead-scoring properties.

Step 2: Adding or Removing Criteria

In the Positive and Negative Attributes sections, you can add new criteria rows to define custom factors not included in the default model. For example, you can add a score based on job title or company revenue.

You can also remove criteria that are not relevant to your business. When criteria are removed, all contacts will be re-evaluated accordingly.

Step 3: Setting Score Weights

Assign positive or negative weights for each criterion based on how many points you want the score to increase or decrease. You can edit the default weights as well.

Ensure high-impact factors get adequately weighted to reflect their correlation with conversions.

Step 4: Defining Filters

The criteria can be filtered further to specify the conditions under which points will be allotted. For instance, you may score only for the first form submission.

There is a limit of 100 total filters across criteria sets. Complex filters can increase processing time.

Step 5: Testing Score Criteria

Once configured, test the scoring against sample contacts to ensure it works as expected. Remember to refine the criteria and optimize based on the latest data.

However, there are a few limitations to note with HubSpot lead scoring:

• You can only have 100 active scoring criteria at one time.
• Each criterion can be assigned between -250 and 250 points.
• Points decay over time, with email actions decaying the fastest.

Best Practices for Lead Scoring in HubSpot

Now that you know how HubSpot's lead scoring works, let's zoom out and discuss best practices. Let’s look at how to build and optimize an effective lead-scoring strategy.

Decide What The Score Should Measure

First, decide what you want the lead score to represent—a general engagement thermometer or a sales qualification threshold. 

• Are you trying to identify sales-qualified leads purely based on intent signals?
• Or do you want a more holistic score combining intent, firmographics, engagement, etc.?

Whatever the goal, the criteria should align with what the score represents.

Use Workflows for Fixed Criteria

Workflows can automatically move contacts to specific lists based on definitive triggers like email clicks or form submissions.

If you have clear SQL criteria like job title + demo booked, use workflows to move such contacts rather than scoring automatically. This helps avoid manually updating scores for obvious qualifications or disqualifications.

For example, you can create a workflow that adds contacts to a "Hot" list whenever they download a pricing sheet or schedule a demo.

Avoid Unreliable Signals

Criteria like page visits or time on site can be misleading as they measure generic engagement. Unless proven to correlate with conversions, avoid such vague scoring factors.

Instead, track predictive signals like content downloads, feature-specific page visits, demo activity, etc., that indicate interest in your offerings.

Incorporate Score Decay

Prospects go hot and cold over time. Their actions should be valued higher for recency. Decaying scores regularly helps surface recently active contacts instead of looking at scores from months ago. 

For instance, you can decay scores by 20% each month to account for recency. This means after a month is completed, a lead score of 100 will become 80.  With this, new activity in the last month gets more weightage than, let’s say, six months old activity.

While there is no direct and simple way to do this in HubSpot, you can add filters like “AND days < 30” to consider scores within the month. Alternatively, you can create workflows to deduct score points at set dates in a month. 

Test, Test, Test

The best way to optimize scoring is to test different versions—run A/B tests on criteria and weighting to see which ones best identify your hottest leads.

Analyze how predictive each criterion is of deals closed last quarter. Eliminate weak signals, adjust weights to optimize correlation, and refine your scoring strategy to find the one that works best for your business.

Review Regularly

As your business evolves, lead behavior and conversions can change. Revisit scoring rules quarterly to check alignment with goals, remove outdated criteria, and adjust weightage as needed.

Also, analyze the correlation between top criteria and won deals over the last quarter to eliminate ones with weak correlation and tweak the weights of strongly predictive ones.

Segment Beyond Just Score

While the score provides a universal gauge of sales readiness, it also segments leads based on persona, source, and other attributes. This provides a more detailed view of where leads are at.

Following best practices will ensure your HubSpot lead scoring model provides an accurate, evolving snapshot of your highest-converting leads.

Top Use Cases for HubSpot Lead Scoring

Now that you understand the mechanics behind HubSpot lead scoring, what are some of the best ways to implement this tool? Here are four top use cases to consider:

Account-Based Marketing

Account-based marketing is a powerful approach to focus your efforts on high-value accounts rather than scattershot campaigns. Lead scoring helps identify prime accounts by combining attributes like industry, size, tech stack, etc.

You can create targeted content campaigns, account engagement plans, and coordinated sales plays customized to these premium accounts. Get the whole revenue team aligned on activating your ideal accounts.

Improved Retargeting

Lead scoring provides the intelligence to create more effective remarketing campaigns. By scoring site visitors based on their content engagement, you can retarget high-intent leads who have shown interest but are yet to convert.

Then, you can create customized remarketing ads and tailored offers around abandoned carts, exit pages, or other drop-off points and identify disengaging leads to re-activate them with relevant content recommendations. 

Refining Buyer Personas

Analyze which lead scoring criteria have the highest correlation with conversions for each of your personas. Identify their unique buying signals.

Then, optimize your personas and associated nurturing journeys to align with how each persona buys from you. Make your personas more predictive—giving your marketing and sales teams the data needed to optimize their approach.

Personalized Onboarding

Lead scoring lays the foundation for tailored onboarding and ramp-up. Identify high-intent visitors and fast-track them with expedited onboarding while providing assistance and training to low-intent leads to get them up to speed.

The applications span across the funnel—from separating anonymous traffic to routing qualified leads and much more. But HubSpot has some limitations which can hinder your decision-making. 

Major Limitation of Lead Scoring in HubSpot 

While HubSpot provides a customizable lead-scoring tool, there are still some inherent limitations to be aware of:

Siloed Data

Lead scoring on HubSpot only accounts for behavior within its tools, not across your tech stack. This interferes with necessary signals like:

• Website analytics data
• Marketing campaign performance
• CRM data on deals and customers
• External intent signals

With data trapped in silos, you miss critical behavioral and intent signals outside HubSpot, resulting in incomplete lead profiles and inaccurate scoring.

Without connecting data across your martech stack, you lack the 360-degree view of each lead needed to power predictive scoring. This significantly hinders the model's accuracy.

No Historical Data Access

Unlike dedicated scoring tools, HubSpot does not provide visibility into the historical progression of a lead's score over time.

For certain high-growth companies, these limitations around flexibility, integration, and visibility can become bottlenecks. Lead routing and sales prioritization may need to be fully optimized.

But how can you overcome these gaps without completely changing tech stacks? Factors.

Close Deals Faster with Factors

Factors eliminates siloed data by combining information from all your marketing and sales channels—not just a single CRM. It enriches this unified data with account intelligence, intent, and more.

Unlike HubSpot, Factors retains the lead timeline and maps it to conversion—going from the first touchpoint on any platform to the last touchpoint on any platform—all on a single screen. This gives a 360-degree predictive view of sales readiness across channels and time.

Other key advantages over HubSpot scoring include:

Privacy-First Web Data Collection

HubSpot may not completely anonymize data, depending on how it has been set up. This can create compliance risks as regulations like CCPA and GDPR evolve.

In contrast, Factors uses data masking and consent management to collect anonymous website behavior data aligned with privacy requirements. You avoid regulatory exposure while still gaining crucial digital body language signals.

Superior Predictive Power and Accuracy

HubSpot's rule-based scoring methodology has inherent limitations in modeling the intricacies of human behavior. The rigid criteria often miss key predictive signals.

Factors overcomes this through sophisticated machine learning algorithms that examine thousands of potential factors to uncover the strongest predictors of sales readiness for your business. This enables vastly superior accuracy in identifying your hottest leads.

Transparent Scoring Models

With HubSpot, you lack visibility into why leads received specific scores, creating a black-box scoring model.

In Factors, you can inspect the critical data points behind each score to understand which attributes or behaviors added or deducted points. This model transparency is invaluable for refining your lead-scoring strategy over time.

Flexible Integration Across Your Stack

HubSpot's walled-garden approach requires ripping out your existing marketing stack to realize its full potential. Unless your existing marketing stack includes all tools from Hubspot, you’d have difficulty bringing it all together. This creates risky and expensive tech disruptions.

Factors flexibly integrates across your martech stack via APIs, pre-built connectors, and custom integrations. You can easily augment HubSpot with enterprise-grade scoring without replacing your foundational systems.

Hands-On Support and Modeling

HubSpot requires you to manage scoring setup and optimization mostly on your own through self-service options. Hubspot is known to have lousy support when it comes to critical issues. 

With Factors, you get dedicated customer success managers to provide strategic guidance around data pipelines, report customization, usage, technical issues, and more tailored to your unique business needs. This white-glove service amplifies your marketing performance.

If the built-in limitations of HubSpot scoring hinder your ability to operationalize scores, Factors provides the enterprise-class upgrade you need. 

With Factors, siloed data, and manual processes are replaced with end-to-end predictive intelligence. Leads are automatically scored, segmented, and routed based on a complete understanding of sales-readiness.

FAQs About HubSpot Lead Scoring

Let's wrap up with answers to some frequently asked questions:

Is HubSpot lead scoring retroactive?

No, HubSpot will only start scoring leads from the point you have lead scoring configured. It does not retroactively calculate scores before setup. This is unlike some advanced lead scoring and account intelligence tools like Factors.

Is HubSpot good for lead generation?

Yes, HubSpot provides a wide array of lead-generation tools, including blogging, SEO, landing pages, forms, and more. Lead scoring helps you quantify and prioritize all the leads being generated.

Can you adjust the points scoring scale in HubSpot?

No, you can only assign points from -250 to 250 for criteria. The scoring scale itself cannot be adjusted.

What happens if you delete a scoring criteria in HubSpot?

Deleting a criterion will automatically re-evaluate all existing contacts and update their scores accordingly.

Key Takeaways

• Lead scoring is a powerful prioritization tool if optimized for your unique business. Don't rely on default criteria - make your own.
• Review and refine your scoring criteria to match how your buyers' journey evolves. Keep it dynamic.
• Test different scoring models through A/B testing. Measure the impact on conversions to optimize the model.
• Combine scoring with workflows and segmentation for a multilayered view of your leads' sales-readiness.
• Consider solutions like Factors to overcome limitations like siloed data. Take your lead routing to the next level.
• With the right strategy, lead scoring gives you the focus and intelligence to accelerate deals and delight more customers.

Lead scoring provides invaluable visibility into the sales readiness of all your leads. And, to take lead scoring to the next level, book a demo with Factors today to see how predictive intelligence can help you identify and convert your hottest leads faster.

Looking for Lead Forensics competitors to better identify and enrich anonymous accounts engaging with your business? You're in the right place. Here's our review of the top 10 Lead Forensics alternatives in 2024

In this article, we’ll cover:

• Lead Forensics' features, limitations, and pricing
• Top 9 Lead Forensics competitors — including their features, limitations, and pricing 
• Factors you should consider when investing in an account intelligence tool

About Lead Forensics

Lead Forensics is a popular visitor identification software that works with over 60,000 customers worldwide. The tool helps businesses identify companies visiting a website using reverse IP-lookup technology.

Some of its key features include:

• Real-time website visitor tracking
• Large database regularly updated with B2B IP addresses 
• Access to contact-level data such as email IDs and phone numbers

Lead Forensics offers two plans: Essential and Automate

Although there’s not much clarity about the pricing on their website, here’s our comprehensive breakdown of Lead Forensics Pricing

Why look for a Lead Forensics Alternative?

Lead Forensics is a widely used tool in the account intelligence space. That being said, no solution is without its flaws. Here are a few reasons why B2B marketers and sales folk consider Lead Forensics competitors. 

Lack of Granularity in Data: Users have stated that they prefer to gain access to deeper insights with the data collected by the tool 

Steep Pricing: Customers across review platforms have stated that Lead Forensics can be relatively pricey for SME businesses looking for cost-effective solutions

Learning curve: Users on G2 have reported that the tool presents certain complexities, leading to a slightly steep learning curve

What to Look for in a Lead Forensics Alternative

• Granular Data: Look for a solution that offers in-depth insight into when a high-fit and high-intent account visits your website. This means access to technographic and firmographic data as well. 
• Real-Time Notifications: Ensure your sales and marketing teams act right when target accounts visit your website. Select a tool that sends real-time alerts on Slack and MS Teams instead of just emails. 
• Robust Integration Options: Invest in a platform that allows flexible integration with existing tools in your tech stack. 
• Ease of Use: Make sure you select a platform that is easy to navigate and has a clean UI 
• Broader ABM functionality: While identifying web visitors is one part, taking actionable steps with this data is equally important. Opt for a tool that gives you the ability to execute your ABM strategy without the need to switch between multiple platforms
• Account and Engagement Scoring: Find a tool that tells you how much your prospects engage with your website so you can appropriately target your marketing and sales efforts
• Intent Data from Multiple Platforms: Your LinkedIn and G2 profiles are lead-generation goldmines, so invest in a solution that gives you 

Top 10 Lead Forensics Competitors in 2024

There are many Lead Forensics competitors in the market today, but we’ve researched and hand-picked the best ones for you. Here’s all you need to know about the top 10 visitor identification and account intelligence tools among B2B companies ⬇️

1. Clearbit

Clearbit is a marketing intelligence tool for B2B businesses that offer users visitor deanonymization, along with intent data, contact data of leads & firmographic data. The tool offers users a large collection of data sets, using publicly available data on the internet, proprietary data, and a large language model (LLM) that organizes unstructured data into usable, standardized modes of information.

Key Features‍

Clearbit offers B2B companies a three-part solution: Enrich, Reveal, and Capture.

• Enrichment: Clearbit’s vast database comprises over 250 data sources and millions of data points, allowing users to easily obtain novel leads.
• Reveal: The tool uses AI-powered deanonymization with data in multiple languages to help users recognize lucrative advertising initiatives and high-intent accounts.
• Capture: Clearbit’s seamless integration capabilities allow it to capture all relevant information from your CRM and streamline sales and marketing processes. 

💡Check out Factors’ new partnership with Clearbit

Limitations

• Relatively high pricing compared to other tools offering similar capabilities

• Users find Clearbit’s integrations immensely useful. However, they find that its data accuracy levels could be higher.‍

Pricing

TrustRadius lists Clearbit’s pricing as $20,000 annually, but the company does not have publicly available pricing information on its website. Clearbit offers flexible pricing on its website, which depends on the user’s contact creation needs, web traffic, and database size.

2. Visitor Queue

Visitor Queue is a visitor identification tool that businesses use to identify prospective clients. You can then use it to reach out to decision-makers from the companies that you’re targeting. 

The tool also provides names, contact information, location, and social media links for the businesses visiting your website. It ensures compliance with local and international privacy laws by relying entirely on publicly available data pulled from a variety of sources.

Key Features

Visitor Queue offers its clients:

• Real-time visitor identification
• Website personalization
• Anonymous website visitor tracking.

Limitations

• It does not have as large a database of companies as many competitors
• It sometimes identifies internet service providers (ISPs) as visiting businesses.

Pricing

Visitor Queue offers five payment tiers depending on the number of leads a client requires from them per month. Here are Visitor Queue’s payment plans:

3. Factors.ai

Factors is an account intelligence and analytics solution that connects with industry-leading data partners to provide IP-based deanonymization. It also provides robust account analytics functions including multi-touch attribution, account scoring, path analysis, and more.

Key Features

Factors offers its clients versatile, comprehensive features, including:

• IP-based B2B account identification across the website, product reviews & ad impressions, with match rates powered by 6sense and Clearbit
• Real-time alerts across Slack & MS Teams to stay on top of high-intent accounts are live and engaging 
• Account scoring where you can create your own scoring rules to score and qualify and segment high-intent accounts based on cross-channel engagement
• G2 and LinkedIn intent signals to identify how prospects are engaging with your profile 
• Workflow automation that allows you to push high-fit and high-intent prospects to mail sequencing tools, push to LinkedIn retargeting audience, and more with webhooks
• Robust analytics and attribution that gives you complete overview on how buyers act at each stage of the customer journey.
• ‍

💡Check out how Factors helped Drivetrain 3x their sales engagement 

Limitations

• Factors doesn’t offer native contact enrichment unlike other the more established platforms on this list but integrates with major enrichment tools like Apollo and Zoominfo 

Pricing

Factors offer a free plan along with 3 other tiers:

• Free
• Basic
• Growth 
• Custom

Learn more about our pricing here

4. Happierleads

Happierleads’ visitor identification tool enables you to reach out to, and target leads that aren’t currently converting into clients. Happierleads’ automated solutions enable users to follow up with visitors and retarget them on autopilot. Its large database of companies also makes for quicker, easier visitor identification.

Key Features

Happierleads offers users four solutions:

• Web Visitor Identification, which helps clients understand which visitors to target
• Prospector, a solution that enables users to contact decision-makers for over 60 million companies
• Enrichment, which adds missing information about leads
• Outreach Software, which sends cold emails to target prospects

Limitations

• Users have reported that the platform can be unintuitive and difficult to navigate 

• Does not offer dedicated engagement analytics

Pricing

Happierleads offers 4 different pricing plans based on the company’s growth stage:

5. KickFire (now part of Foundry)

KickFire identifies leads who are engaging with your company and segments them according to intent. KickFire allows you to prioritize leads based on intent segmentation. It also allows users to see which types of content resonate the most with their target audiences. It is now a part of Foundry as of 2024. 

Key Features

KickFire offers users the following features:

• Data verified by humans and normalized across the sales and marketing platforms
• Prompts that offer actionable sales and marketing insights
• Easy installation and buyer identification.

Limitations

• Customers have reported that the filtered results aren’t accurate and lack granularity when compared to other tools in the market

‍Pricing

KickFire does not offer pricing information publicly.

6. LeadLander

LeadLander’s visitor identification solution gives you employee contact information for priority leads. The tool offers users contact profiles and key data points that can help companies close more deals. It also provides user journey information and the web pages each visitor has seen.

‍Key Features

• De-anonymization
• Customer behavior and journey data
• Key contact information for high-priority leads‍

Limitations

• Sometimes gives cable or ISP addresses in place of visitor data
• Account scoring and engagement scoring capabilities are limited

Pricing

LeadLander offers 2 pricing plans:

7. LeadInfo

LeadInfo de-anonymizes website visitors for B2B clients using their extensive data set. They match the visitor’s IP address against their vast database. Their clients obtain an overview of website users, the companies they belong to, and their behaviors.

It offers users various one-click integrations and worldwide coverage to ensure seamless lead generation. It also lets B2B companies view website visitors in real-time.

‍Key Features

Leadinfo’s key features include:

• A vast dataset of companies
• Global coverage
• 60+ one-click integrations
• Real-time website visitor information‍

Limitations

• Limited dashboard capabilities
• Users state that pricing is slightly on the higher end compared to tools with similar capabilities‍

Leadinfo Pricing

Leadinfo’s pricing model uses a sliding scale based on the number of unique companies recognized per month on their clients’ websites.

8. Albacross

Albacross’s account intelligence offerings help users nurture leads visiting their websites. They help clients discover unseen purchasing intent through their deanonymization feature, thereby generating more pipeline and accelerating sales.

Key Features

Albacross offers its users:

• Visitor deanonymization
• Real-time alerts for priority prospects
• A global database of companies

‍Limitations

• Albacross doesn’t offer as many integrations as its counterparts
• Software has a relatively steep learning curve
• Doesn’t offer workflow automation  

Albacross’s interface helps users organize data intuitively. However, small businesses have found that the tool may be more suited to larger organizations due to informational gaps in Albacross’s database.

Pricing

Albacross offers users two pricing models: Self-service and Growth.

9. Leadfeeder (now Dealfront)

Leadfeeder’s visitor identification capabilities help users convert page views into valuable pipeline.

Leadfeeder’s four-step plan to uncover hidden leads visiting their users’ websites is to identify, qualify, collect, and send leads. This ensures that their users obtain high-value leads that have a better chance of converting.

Key Features

Leadfeeder’s features include:

• Website visitor tracking
• Account-based marketing, and
• Sales prospecting.

‍Limitations

• Limited integrations
• Does not offer real-time alerts for website visitors
• Lack of engagement scoring  and workflow automation

Pricing

Leadfeeder offers users two payment plans:

💡Compare‍ Albacross and Leadfeeder

10. Warmly

‍

Warmly is a sales orchestration platform that uses AI to identify, track, and connect with website visitors who are actively looking to buy. They offer workflow features that automate sales prospecting for SMB-sized revenue teams.

Key Features

• Autonomous Sales Orchestration
• Automated Intent-Driven Outreach
• Website deanonymization

Limitations

• Massive pricing jump from the free plan
• Customers have mentioned they would like additional filters to better segment their data
• Users have reported that the tool has a steep learning curve

Pricing

Warmly offers a free plan along with a business plan for $1200/mo and an enterprise custom pricing.

Choose the Right Account Intelligence Tool For You 

Deanonymization is essential for B2B companies to expand and target high-value prospects. Your account intelligence tool should also help you qualify and activate high-intent accounts visiting your website. Factors analytics and attribution platform helps you evaluate and iterate your sales and marketing campaigns so you can turn prospects to paying customers in no time. 

Its no-code integrations and robust reporting make for an easy user experience with a minimal learning curve.

Get in touch with us today to find out how Factors’ account intelligence capabilities can help your company minimize pipeline leakage and increase efficiency and revenue.

We’re delighted to announce our partnership with leading B2B marketing intelligence platform, Clearbit! 

With this partnership, users can leverage Clearbit’s extensive intelligence database in tandem with Factors’ proven analytics platform to identify, qualify and convert accounts like never before. 

Not a Clearbit customer yet? No worries! You’ll still be able to enrich anonymous accounts with over 100+ firmographic & technographic attributes through Factors at no additional cost. 

If you’re already using Clearbit, you can simply connect Factors to your Clearbit account using an API key. 

We’re super excited for the immense value this partnership brings to our customers. Here are a few ways in which you can expect to make the most of Clearbit + Factors. 

What’s in it for you?

Factors is a tried and tested analytics & attribution solution loved by 200+ high-growth SaaS teams. This partnership with Clearbit complements our core features — web analytics, multi-touch attribution, account scoring, path analysis, and more — with robust IP-based intelligence and account enrichment. Here’s what’s in it for you:

1. Identify, qualify & convert 

It’s commonly accepted that only about 4% of website traffic actually reveals itself through form submissions or sign-ups. This means that the majority of accounts engaging with your brand, remain anonymous! Now, with IP-based intelligence & enrichment, you can accurately identify hidden accounts visiting your website, engaging with product reviews, or simply viewing ad campaigns. Once identified, you can configure custom scoring criteria to qualify high-intent accounts based on their firmographics, technographics, and engagement.

This is tremendously valuable to marketing and sales teams as it’s far more effective to prioritize in-market, brand-aware accounts as opposed to cold accounts from generic ICP lists. 

With Factors x Clearbit, you can accurately identify up to 50% of anonymous accounts already engaging with your brand. These accounts may then be filtered down to ICP accounts based on firmographic and technographic properties such as industry, size, geo, techstack and more. 

Now, it’s probably unlikely that all ICP accounts on your website are ready-to-buy. Some may be further along the funnel than others. Factors helps qualify sales-ready accounts based on their engagement across websites, product reviews, and ad impressions. 

Let’s take 5 milestones to explain: 

1. visits pricing page 
2. visits G2 review 
3. reads blog for > 30s  
4. views LinkedIn ad 
5. opens sales email 

On Factors, you may configure your scoring model to tag accounts that complete all 5 milestones as “hot”, accounts that complete none as “ice”, and accounts that complete 2-3 milestones as “warm”. Note that this scoring model is completely customizable within Factors based on the touchpoints you care about most.

Ultimately, this combination of intelligence and analytics empowers teams to go after the right accounts at the right time to drive markedly more conversions. 

But don’t just take our word for it…

2. Build workflows, effortlessly

Go-to-market teams should spend less time worrying about operations and logistics and more time iterating on strategy to drive pipeline. To support this approach, Factors can push relevant account data to nearly any other platform (CRMs, MAPs, internal comms, etc) in the world using Webhooks (Zapier, Make, etc). 

For example, let’s say your ICP looks something like this: US-based software companies with 500-1000 employees using HubSpot. With Factors, you can configure trigger alerts so when an account that matches this criteria visits a high-intent page (like factors.ai/pricing), Factors can automatically:

• Push this data to a retargeting list in your CRM 
• Notify the relevant SDRs on Slack 
• Initiate a sequence on your mail automation tool

This way, 

• The marketing team can retarget warm accounts with relevant ad campaigns 
• SDRs can reach out to relevant prospects while the iron’s still hot 
• And known prospects can be placed in a nurture sequence

All without any manual intervention. 

In short, Factors can automate a lot of the heavy lifting, so teams can focus on what they do best.

Learn more about how customers use Factors for intent-based outreach and retargeting.

3. Make the most of marketing

If you’re like most B2B teams, you’re investing significantly in paid ads, content & seo, events & webinars, and other marketing efforts. For the most part, however, it's challenging to measure the impact of these efforts. 

Let’s take content, for example. Without the right tools, marketing teams have little visibility into which anonymous accounts are reading blogs, how accounts are engaging with case-studies, and what the bottom-line impact of content assets are. 

As a solution to this, Factors and Clearbit complement each other seamlessly to: 

• Identify anonymous organic traffic to monitor traffic quality
• Measure engagement with metrics such as time spent & scroll-depth
• Attribute the impact of ungated content assets on conversions & pipeline

There are several other ways in which our customers are leveraging Clearbit’s intelligence with Factors’ analytics and attribution. If you’re curious to learn more, schedule a demo with our team here:

{{CTA_BANNER}}

Why Clearbit?

While it’s true that there are several B2B intelligence platforms and alternatives out there, Clearbit stands out as one of the best when it comes to accuracy, technology and value. As a leader in this space, Clearbit is home to one of the largest, most reliable IP databases &  infrastructure in the market.

We believe that this partnership will further empower our customers to discover otherwise hidden buyer intent, build robust audience lists, analyze the impact of content and campaigns, and improve customer experience and conversions across the board. 

FAQ

1. Do users need a separate Clearbit account to use this?

Nope! You do not need to be a Clearbit customer. Our partnership allows users to leverage Clearbit data as part of Factors for no additional charge. Learn more about how this works over a quick chat with our team! 

2. How does pricing work?

Access to Clearbit data is part and parcel of our pricing plans at Factors. You won’t have to pay extra or purchase Clearbit separately. Instead, our pricing is based on the volume of accounts identified and monthly unique visitors. Learn more about our pricing here: factors.ai/pricing

3. Can Factors identify email IDs or phone numbers of anonymous website visitors?

No. Factors works with data partners to discover account-level information such as company name, industry, size, technographics, and much more. Factors does not identify or distribute anonymous user level information such as phone numbers or mail IDs. 

4. Is Factors privacy compliant? 

Absolutely! Factors is aligned with GDPR & PECR privacy standards. Factors is also SOC2 Type II certified. Rest assured, your data is yours alone — and is protected vigilantly with industry-standard security practices. Moreover, Factors only de-anonymizes IP data at an account-level. We do not identify or distribute anonymous user-level data (personal phone numbers, mail IDs, etc) whatsoever. 

5. How does IP-based identification work?

Read more about how IP-based account identification works here.

When validating a SaaS concept in its early stages, teams often have a one-track mind and focus on product over profitability. While acquiring customers is critical, you must also be mindful of this metric: Customer acquisition cost. 

Customer acquisition cost (CAC) plays an important role in determining the sustainability and scalability of SaaS businesses. 

This blog highlights everything you need to know about CAC.

What is Customer Acquisition Cost (CAC) in SaaS? 

Customer Acquisition Cost (or CAC) is the total amount of money a company spends on marketing, sales, and other GTM activities to acquire new customers. 

The formula to calculate CAC is:

Customer Acquisition Cost = (Sales expenditure + Marketing expenditure) / New Customers Acquired in a given period.

Here, sales expenditures include employee salaries, sales tools and tech, and the like etc. Marketing expenditures include ad spend, content production costs, event expenses, etc. 

Note that CAC excludes repeat customers. It only accounts for new customers, not new orders from existing accounts. 

A lower CAC indicates that a company is acquiring customers more cost-effectively. This generally implies solid product-market fit and successful marketing and sales efforts. A higher CAC, however, suggests that the company might need to re-evaluate its GTM strategy.

Why is Customer Acquisition Cost Important In SaaS?

Here are some ways CAC is a powerful barometer for profitability, product-market fit, and overall strategic direction.

1. Gauge Profitability

CAC helps SaaS companies assess the balance between acquisition costs and revenue generated. A low (or lowering) CAC-to-CLV ratio helps galvanize the brand by signaling efficient, sustainable growth.

2. Evaluate Product-market Fit 

A high CAC often indicates misaligned PMF or inefficient GTM efforts. This signal can then prompt course-correcting adjustments. Say a company with a tiered pricing structure spends $1000 to acquire a new customer. However, 90% of its customers end up subscribing to the most basic plan, which is priced at only $150 per annum. At this rate, the company will need more than 6 years to recover the acquisition cost. 

In this instance, it may help to re-evaluate the product offerings and customer requirements and make adjustments that make the company more profitable. 

3. Optimize Resource Allocation 

Insights from measuring CAC can help inform efficient resource allocation. By analyzing how each channel contributes to customer acquisition, teams can optimize marketing and sales budgets to maximize return on investment.  

Say a company uses the following channels for customer acquisition:

Say a company uses the following channels for customer acquisition: 

In this case, although events bring in the maximum number of acquisitions, content marketing provides the lowest acquisition costs. Hence, the company may want to consider investing more in content marketing efforts going forward. 

Should you view CAC in isolation?

You should not CAC in isolation. SaaS businesses need to strike a balance between CAC, Customer Lifetime Value (CLV), and the CAC payback period. 

You can justify a high CAC with a high CLV or a short payback period. 

Say a company spends $5000 to acquire a new customer. If the lifetime value of this customer is $18,000, or it takes only about a month to recover the $5,000 through subscription or in-app purchases, the CAC is justified compared to a company that spends $100 to acquire a customer but has an average CLV of $50. 

In other words, a company experiencing higher churn rates is bound to rely on low customer acquisition costs to become profitable. 

Additionally, CAC also varies widely based on industry standards, such as:

• Purchase Frequency
• Purchase Value
• Customer Lifespan
• Company Maturity
• Length of Sales Cycle
• Research and development 

Step-by-Step Guide to Calculating CAC for SaaS

Calculating CAC can be a nuanced task. Here is a step-by-step guide to help you through the process:

1. Identify all costs related to customer acquisition ‍

Make sure only to include expenses that directly contribute to customer acquisition.

Advertising Expenses: This includes the total ad spend across search ads, paid social, sponsored events, etc.  

Technological Investments: Technological costs include spend on marketing and sales technology that supports go-to-market initiatives. This consists of automation platforms, intelligence solutions, outreach tools, etc.

You should also consider infrastructure costs, such as those for data storage platforms like SingleStore, Google Cloud, Azure, etc. The CAC is relatively higher than the costs for other SaaS platforms.

Note: This category should not include software or technology that does not directly affect the sales funnel, such as your internal collaboration or task management tools, such as Slack, Asana, Notion, etc. 

Employee Salaries: If you have a dedicated sales team working on outreach, their salaries should be considered when calculating CAC. 

💡TIP: Most companies exclude the salaries of the entire marketing team when calculating CAC. This is not the right approach, as marketing costs can add up quickly. The right approach is to include the salaries of employees who come in direct contact with customers or directly impact sales. For example, a PPC or SEM expert should be factored into the calculations. Still, SEO experts or website developers who do not contact customers directly should not be included.

Content Marketing Costs

Content marketing costs encompass all expenses associated with creating new content assets across blogs, media, and more. For example, when producing a video, this includes the cost of purchasing equipment, setting up a studio, acquiring backdrops, obtaining editing software, and other related expenses. Remember: these costs should be considered even if you hire a third-party content producer.

Research and Development
PLG companies invest in R&D as part of their customer acquisition mix (free sidecar products, freemium, growth teams, self-service purchasing, etc.). Atlassian, for instance, spends $2.43 on R&D for every $1 on sales and marketing.

However, R&D investment is usually not factored into the CAC payback period calculation, blurring the picture of the growth model.

If you’re investing in PLG, plan to stay below the “normal” CAC payback benchmarks.

2. Decide on a tracking period 

The tracking period is the timeframe over which you'll calculate your CAC. It's essential to choose a period that aligns with your sales cycle. This could be monthly, quarterly, or annually for SaaS businesses, depending on how long it typically takes to convert a lead into a paying customer.

3. Calculate the number of customers acquired in your tracking period 

Count the number of new customers you've acquired during the chosen tracking period. This should include all paying customers during that time frame.

Note: The more accurate way to analyze customer acquisition cost is to track the costs and acquisitions over the length of an industry's sales cycle. For example, if enterprise sales in the healthcare sector take about 10 months to close a deal and get a paying customer, then the CAC should be tracked for that period.

4. Divide your acquisition costs by the number of customers

Calculating CAC is straightforward: CAC = Total Acquisition Costs / Number of Customers Acquired. Plug in the numbers: Divide the total acquisition costs (step 3) by the number of customers acquired during the tracking period (step 2).

Here's an example to illustrate these steps:

Suppose a SaaS company spends $50,000 on marketing and sales efforts in a quarter. During the same quarter, they acquired 500 new customers.

CAC = $50,000 / 500 = $100 per customer.

Determine your total marketing and sales expenditure within a specific time frame. This time frame can be a month, quarter, year, or any other relevant period. Next, calculate the number of new customers acquired during that same time frame.

Utilize the customer acquisition cost formula to ascertain the average cost per customer. This will provide insight into your gross margin and how much you potentially earn per new customer.

CAC benchmark: “What’s a good customer acquisition cost?”

There isn't a one-size-fits-all benchmark for CAC, as it can vary significantly depending on factors like your industry, target market, business model, and growth stage. What might be considered a good CAC for one SaaS company might not be the same for another. That said, here are some general guidelines and benchmarks to use as reference:

CAC Payback Period

There isn't a one-size-fits-all benchmark for CAC, as it can vary significantly depending on factors like your industry, target market, business model, and growth stage. What might be considered a good CAC for one SaaS company might not be the same for another. That said, here are some general guidelines and benchmarks to use as reference:

CAC Payback Period

OpenView’s report on SaaS Benchmarks shows CAC Payback periods based on company size or annual revenue, with a focus on different customer segments:

 Source: SaaS benchmark report 2023 by Openview

As you can see, the payback period has gotten worse as companies grow in revenue. This holds especially true for companies that grow upward of $20M ARR. There could be 3 main mistakes here:

• Not focusing on Net Dollar Retention (NDR)
• Believing that sales and marketing are the sole costs of acquisition
• Looking at CAC payback on a revenue basis instead of a cash basis 

Andrew Allsop, Senior Demand Gen Manager at Bryter put it best when he said that marketers must focus on new sources of acquisition instead of over-optimizing an existing channel:
"If you’re able to acquire customers that fit within your financial model then do so until you can anymore, and then find other ways to do the same thing.

New sources of acquisition = greater growth potential than spending 100s of hours squeezing an extra few cents out of an existing channel."

CLV: CAC Ratio

The CLV: CAC ratio is a more reliable metric when at least 1-2 agreement renewal cycles have occurred to establish a more consistent churn rate across renewal periods. It helps gauge the return on investment regarding customer acquisition. 

According to a report by Benchmarkit, over the last three years, the benchmark for the CLV: CAC ratio has varied between 2.1 and 6, regardless of the company’s size, ARR, or any other revenue metrics. 

The report implies that for every $1 spent on customer acquisition, the business should ideally generate revenue of $2.1 or $6.

NOTE: Both metrics should not be viewed in isolation. A company can have a high CLV: CAC ratio, but if the CAC payback period is much longer, say 24 months, the business does recover its initial cost of acquisition, but it takes them two years just to break even.

Challenges with calculating CAC

Calculating customer acquisition costs is simple in theory but can get complicated really quickly. There are several nuances to account for, and businesses typically face these challenges in calculating CAC: 

1. Inconsistent tracking period

"Days to close" can significantly impact Customer Acquisition Cost (CAC). Typically, businesses opt to provide reports on a weekly and monthly basis. However, a challenge arises when attempting to make monthly reports, especially when the "days to close" metric stands at just 14 days. This situation implies that any new visitor acquired during the latter half of a month will only become a customer in the first half of the subsequent month.

In such a situation, you’ll be incorporating the costs incurred in Month 1 and revenue generated in Month 2, which can throw you off track. The best way to tackle this situation is detailed user journey mapping. Tracking a customer’s interactions from the very first touchpoint to the final is a great way to understand the sales cycle and determine the tracking period for CAC calculations.

2. Unreliable attribution

What campaigns and content actually contribute to conversions and pipeline? Without understanding the impact of marketing and sales touchpoints on bottom-line metrics, it’s difficult to attribute CAC accurately. 

The main challenge with revenue attribution is the nonlinear nature of customer journeys. When a visitor becomes a paying customer, it's rarely because of a single touchpoint. It's likely a result of many touchpoints: channels, campaigns, content, and people — working together to convince the buyer.

Without the right attribution tools, it's difficult to understand and appreciate how each channel contributes to revenue generation. 

3. Fragmentary data and analytics

Another challenge when calculating CAC is siloed data across various sales and marketing channels. Manually monitoring KPIs and staying on top of channel-level performance is tedious and time-consuming. Again, without the right tools, the team’s focus may be redirected towards operational tasks such as reporting and away from strategic decision-making. 

Wrapping up

Teams should spend more time making sense of their CAC and less time actually measuring it. When you track relevant metrics such as NDR and CLV, you get a holistic view of how much you spend in acquiring customers and how you can save costs accordingly.

Need help seeing results from your marketing campaigns? You need to begin tracking the right demand generation metrics. They help you know what's working at each marketing stage—from initial brand awareness to customer retention.

While there are numerous metrics that you can track, let's explore the 12 most important demand generation metrics you must consider tracking. From website traffic to content engagement and beyond—we'll cover the key performance indicators (KPIs) that allow you to:

• Identify bottlenecks in your marketing processes
• Prioritize high-impact campaign strategies 
• Continuously optimize based on actionable data
• Prove and improve marketing's impact on revenue

Let's get started. 

Top 12 Demand Generation Metrics 

Rather than tracking every metric under the sun, it pays to focus on a targeted set that will give you true insight into your marketing efforts. We'll split them into sections of the B2B sales funnel—top of the funnel, middle of the funnel, bottom of the funnel, and post-conversion metrics for simplicity. 

Here are the top 12 metrics you must track for better demand-gen marketing. 

Top-of-the-funnel metrics

The top of the funnel is all about driving awareness and interest in your brand. To measure effectiveness at this stage, focus on these key metrics:

Website Traffic and Unique Visitors

Your website traffic shows the total number of sessions or pageviews on your site over time. The unique visitors metric represents the number of new people who have come to your website within a designated time frame.

When both metrics are tracked together, it gives insight into how well your campaigns expose your brand to fresh audiences and drive engagement.

For example, if you drive 5,000 visits and 4,000 unique visitors in a month, it tells you your traffic sources are introducing 1,000 repeat visitors along with 4,000 new people to your site. 

This analysis helps you identify which channels excel at attracting relevant new visitors vs. repeat traffic. You can then focus efforts on high-performing channels for new visitor growth while phasing out ones only to drive repeat traffic.

Landing Page Conversion Rate

Your landing page conversion rate is the percentage of visitors completing your desired goal action on your landing page, like downloading content or signing up for a demo. For instance, if you get 300 downloads from 1,000 visitors, your conversion rate is 30%.

Landing Page Conversion Rate: (Total conversions / Total visitors to the landing page) x 100

You can test different elements on your landing pages, like copy, visuals, and calls to action, to refine them for higher conversion rates over time. With an analytics tool like Factors, you get the insights necessary for optimizing your funnel for better conversions. 

Click-Through Rate (CTR)

Click-through rate is the ratio of users who click on your ad or content compared to the number who saw it. For example, if your ad gets 300 clicks after being seen 1,000 times, your CTR is 30%.

CTR: (Total clicks / Total impressions) x 100

CTR indicates how well your ads perform. If more people click on your ad, it reaches the right people and resonates with them. So, it makes sense to monitor CTR by campaign, ad group, and keyword to identify high-performing content. 

Middle-of-Funnel Metrics

Once you've attracted visitors and converted them into leads, it's time to begin nurturing and qualifying them and determining their sales-readiness—that's the middle of the funnel. These key metrics help you assess pipeline health at this stage.

Lead Generation Rate

Your lead generation rate shows how many new leads are produced over a specific period, typically monthly. For example, if your marketing efforts on one channel generate 400 leads over two months, you have a monthly lead gen rate of 200. The higher this number, the better it is—indicating better marketing. 

Lead-to-MQL Conversion Rate

Once you have collected the leads, it's time to convert them into MQLs and take them further along the funnel. This metric looks at the percentage of new leads that turn into marketing qualified leads (MQLs)—these are deemed ready for sales follow-up. For instance, if you generate 400 leads monthly and 100 qualify as MQLs, your conversion rate is 25%.

Lead-to-MQL Conversion Rate: (Total MQLs / Total new leads) x 100

This helps you understand how effectively your lead nurturing process moves prospects down the funnel to sales-readiness. A higher conversion rate shows better lead scoring, nurturing, and qualification processes.

Cost Per Lead (CPL)

Your cost per lead represents the average spend required to acquire a new marketing lead. It's calculated by total marketing costs divided by the number of new leads. 

For instance, $4,000 in marketing was spent to generate 400 leads. The CPL is $10.

Cost Per Lead: Total marketing costs / Total new leads

We want the cost to be as low as possible to acquire the same number of leads. So, in this case, lower CPL is better for your marketing campaigns. Once you've nurtured your leads, it's time to track and analyze the leads that move to the final stage of purchase—the bottom of the funnel. 

Bottom-of-the-Funnel Metrics

As leads move to the final sales stages, these metrics indicate how effectively your processes close and retain business:

Opportunity-to-Win Ratio

This metric evaluates the percentage of sales opportunities that successfully convert to won deals. For example, if your team successfully closes 50 out of 100 closed opportunities, your opportunity-to-win ratio is 50%.

Opportunity-to-Win Ratio: (Total won opportunities / Total closed opportunities) x 100

The higher this percentage, the better your sales team performs. The average sales win rate hovers around 47%. If your sales team can close a higher percentage of leads, it means the sales team better understands your audience's needs. But along with that, it also signifies your lead filtering is done well. 

Customer Acquisition Cost (CAC)

Your CAC is the average cost to convert a new customer. It's calculated by dividing total sales and marketing costs by the number of new customers won. 

For instance, $40,000 in marketing and sales to gain 100 new customers means a CAC of $400.

Compare CAC to factors like customer lifetime value and retention rates to ensure your acquisition costs align with potential revenue and longevity from each customer gained. Use CAC benchmarks by industry to optimize your spend.

Sales Cycle Length

The sales cycle length tracks the average days from initial contact to deal close. In the B2B space, the average sales cycle length can be over two months. However, it's best to aim for a lower average here. 

You can try account-based selling—a technique where you look at leads as accounts or companies to target instead of individual users. 

This allows you to gain a holistic perspective of the pain points a particular account is trying to solve and target individual accounts with messaging that checks the right boxes.

Determining an individual lead's account can become easier using account intelligence tools like Factors.  

Post-Conversion Metrics

Once a customer is acquired, you must also ensure they stay with your company. This involves customer success, customer support, and customer experience throughout their journey. Let's look at some metrics that help you determine the actual value of your products or services.

Customer Lifetime Value (CLTV)

Your customer lifetime value metric represents the average revenue generated from a customer over the entire relationship. It's calculated using average purchase value, frequency, and customer lifespan. 

For instance, if a customer pays you $200 a month, and the average relationship is 14 months, your customer lifetime value is $2800. 

This metric is valuable for two reasons—one, it tells you the average revenue each customer generates, and two, it tells you how much money you can spend to acquire each customer. Continuing the above example, you're running profitable marketing campaigns if you spend $350 to acquire a new customer.  

As you acquire more customers, keep an eye out for this number. Suppose you optimize this through better customer experience, improving features based on feedback, and providing more and more value every month. In that case, you can create a sustainable business in the long term.

Churn Rate

Your churn rate shows the percentage of customers you lose in a given timeframe. For example, if you lose 50 of your 500 customers annually, your churn rate is 10%.

The average annual churn rate in SaaS is 32-50%. This means 50-68% of the users continue using the same product for over a year. While the churn rate cannot be zero, the lower you keep this, the better it is for your business. 

Higher churn signals a problem—the product or service isn't delivering enough value to the customers. It also hurts marketing since they now have to work with smaller budgets to acquire more customers while working with the high churn—and it's a vicious cycle you'd best keep at bay. 

The best way is to track this metric closely and take action to reduce the churn rate whenever it is going in the wrong direction. 

Customer Satisfaction and Net Promoter Score (NPS)

Customer satisfaction metrics like NPS measure customers' happiness and loyalty via direct feedback. NPS asks customers their likelihood to recommend your product or service on a 0-10 scale.

Net Promoter Score: % Promoters (9-10 score) - % Detractors (0-6 score)

This metric relates to the two metrics we discussed above. If your customers are happy, they will stay with the business longer, with less churn. 

With technology aiding customer support, begin taking advantage of chatbots trained on your product documentation to answer customer questions instantly—and leave the complex queries for your lean support team.

Aligning the Chosen Metrics for Your Demand Generation Goals

While you can pick a few metrics from the above list and start tracking, you must ensure that the chosen metrics align with your demand generation goals. Let's look at what to consider to do this effectively. 

Connect Metrics to Overall Goals

Consider your main company goals, like revenue growth, customer acquisition, or market expansion. Determine which critical metrics at each funnel stage help track progress toward those goals.

For example, track lead volume and velocity through the pipeline and retention rate for a revenue growth goal. To expand market reach, monitor website traffic sources and visitor engagement—this will tell you the story of how far and wide your marketing reaches.

The idea is to have a standardized set of primary metrics you and your marketing team will watch at each stage that map back to high-level goals. With this, you automatically align teams to work towards the same set of targets instead of creating an organizational drift. 

Customize Metrics for Your Business

While standard metrics provide a strong starting point, you may want to customize based on your business model, goals, and audience.

Research benchmarks specific to your industry to set targets to gauge performance. Websites like Statista can help you understand the average range for your metrics. For instance, B2B businesses have higher CAC than DTC businesses. And that will help you set expectations when it comes to marketing costs. However, remember that the averages only help you set the goals initially. Once your marketing team has run campaigns over a few months, there will be enough data to create your own goals and metrics that work just right for your business. 

Optimize Processes to Move Metrics

We must set metrics and remember them. Monitor how team hand-offs influence your metrics and identify friction points. Based on the data you gather, refine roles and information transitions across sales, marketing, product, and service to align activities that impact your numbers.

For instance, long lead follow-up times could slow velocity and conversion rates. However, refining the process to improve marketing-to-sales hand-offs can be a low-hanging fruit that maximizes lead nurturing effectiveness and increases sales readiness.

Don’t forget to take the time and understand how your teams work collaboratively and identify ways to accelerate progress on the metrics tied to company objectives—calibrate efforts across the funnel for maximum business impact.

Take the Steps To Achieve Your Business Goals with Data-Backed Marketing

Tracking every vanity metric gives us an illusion of understanding marketing performance. But drowning in numbers only muddies the picture. You want the numbers to tell a story about how marketing is progressing toward your business goals.

You want metrics to help you zero in on the KPIs and offer visibility into campaign health and opportunities—enabling strategic decisions to drive growth. And for that, you need to track the most important ones. 

This guide will give you a headstart in creating tracking dashboards with the 12 most crucial demand generation metrics. But consider this as the beginning. Start pooling in data from multiple sources and aligning metrics with your business goals to extract the most valuable insights and tell the story right. 

Try Factors when you need an analytics tool to help you achieve that quickly. 

Factors helps you cut through the noise and clearly understand your marketing performance and revenue opportunities. It also takes advantage of visitor data to identify the business and industry a visitor is associated with—extremely valuable for account-based marketing campaigns.

Stop tracking your campaigns in the dark. The metrics are right here for you to make the most of them. Book a demo with Factors and see how we can make extracting insights easier. 

FAQs

How is demand generation measured?

Demand generation is measured through a combination of website traffic, landing page conversion rate, lead volume, cost per lead, sales cycle length, win rate, churn rate, and customer lifetime value. Tracking these KPIs provides visibility into a campaign’s effectiveness at driving new prospects into the funnel and successfully converting them to customers.

What is lead scoring in demand generation?

Lead scoring helps prioritize, which leads to focus on nurturing and advancing down the funnel. It assigns points to leads based on attributes like demographics, behaviors like page views, or interactions like downloading content. The resulting lead score represents a lead's sales readiness. Analyzing metrics by lead score helps focus efforts on higher-scoring segments for better conversion.

How do you measure the ROI of demand generation?

To measure ROI, first calculate campaign costs like advertising spend, human resources, and content creation. Then, quantify revenue driven by new customers acquired through demand gen efforts. Subtract expenses from income to determine net profit, then divide by costs to calculate ROI as a percentage. Tracking attribution helps accurately assign revenue to suitable campaigns and channels.