Factors Blog

Insights Across All Things B2B Account Intelligence & Analytics

How To Use Intent Data To Drive Pipeline (Part I)

May 17, 2023

•

0 min read

All Roads Lead To Revenue

There’s no doubt that top of the funnels like traffic and opportunities remain important indicators to B2B marketers. But increasingly, high-growth marketing teams are held accountable for bottom-line business metrics like pipeline and revenue.

That being said, driving deals is easier said than done. With limited budgets, tight competition, and volatile markets, go-to-market teams need an efficient alternative to make the most of their resources.

Enter: Intent data

Intent data captures buyer intent so you can identify, target, and convert high-fit sales-ready accounts. Here’s what this means for your team:

Intent-based outreach, as opposed to cold outreach
Targeted ABM efforts, as opposed to spray and pray tactics
Deal acceleration for existing or lost accounts in the pipeline

When used efficiently, intent data can wring out every bit of ROI from existing marketing and sales efforts. The following guide highlights how to leverage intent data to drive more pipeline, with less spend.

What Is Intent Data?

Intent data is any data that provides information about customer behavior and buyer intent across campaigns, websites, review sites, or more. There are 4 types of intent data: zero-party, first-party, second-party, and third-party:

Zero-party intent data: Data that a buyer explicitly shares. (Eg: demo form with Name and Email fields)
First-party intent data: Data that’s collected from buyer’s interaction with a business. (Eg: Web sessions, page views, button clicks, etc)
Second-part intent data: Data collected from another company’s first-party data (Eg: First-party data from review sites like G2 or Capterra)
Third-party intent data: Aggregated data from multiple sources (Eg Bombora intent data)

Why’s Intent Data Important?

1. Efficiency gains: Just a few years ago, businesses were ready to buy, buy, buy. These days, companies are far more conservative. Longer sales cycles, lower win rates, and shrinking contract values all point towards this.

That's why prospects that are considering your solution are that much more important. However, only about 5% of website traffic actually converts — leaving the remaining 95% of visiting accounts completely anonymous.

Using intent-data in tandem with account identification tools helps discover, qualify, and convert up to 64% of sales-ready companies already visiting your website. Tap into a pool of mid/bottom of the funnel accounts who are yet to convert with zero additional spend. Here are a few questions you can answer:

Which ICP accounts visited a landing page through a search ad but didn’t submit a demo form?
Which companies are reading bottom of the funnel product blogs at least 50% of the way?

2. Early-intent detection: Studies find that buyers are 57% along the buyer journey before contacting a sales rep. Fifty. Seven. Percent! By this stage, in-market accounts have done their research and formed a rough idea as to which vendor they’re leaning towards.

Intent data helps identify buyer intent much, much before a form is submitted. This gives teams a significant first mover advantage in establishing the initial evaluation criteria, building relevant relationships, and improving the odds for a higher ACV.

It would mean beating competitors to the sales by reaching out to sales-ready prospects before anyone else does. While getting there first isn’t everything, it certainly helps.

Ingredients To Leverage Intent Data

We’ve established that intent data is pretty valuable. But how to collect intent data? Who should be involved? And what’s a comprehensive way to leverage this data to drive pipeline? This section covers the tools, people & process that make intent data work.

1. Tools

Here are all the tools you’ll need to identify, track, report, and activate intent data.

1. Intent Data Providers

Data is essential to make this work. Start by identifying a handful of sources for various types of intent data. This doesn’t have to be complex or expensive, the following tools are a great starting point:

First-party data - Factors.ai, 6sense
Second-party data - G2, Trustradius, Capterra
Third-party data - Bombora, Leadsift, Contentgine

Factors is a account intelligence tool that delivers industry-leading IP-lookup technology to identify up to 64% of companies visiting your website. This includes company name, firmographics (industry, headcount, revenue-range, etc), and behavioral data (page views, scroll-depth, button clicks, etc)

2. CRM

A CRM acts as a single source of truth to unify intent data for the entire GTM engine across sales, marketing, and customer success. You’re likely already using a CRM such as HubSpot or Salesforce. Other alternatives include Zoho, Pipedrive, and Leadsquared.

3. Enrichment Database

Once accounts visiting the website have been qualified for fit and intent, use an enrichment database to identify the appropriate people to reach out to. A few popular enrichment tools include:

Apollo
Zoominfo
Lusha
LeadIQ

4. Sales Engagement

The following sales engagement tools help sales reps and marketers automate the outreach process across multiple channels including email, phone calls, and social media:

Outreach
Outplay
Salesloft
Klenty
LinkedIn Sales Navigator

5. Internal Communications

Push real-time alerts to internal communication tools like Slack or MS teams when new companies or existing leads from target companies are live on the website.

We’ll cover how each of these tools work in tandem in the process section of this article.

2. People

These are the stakeholders and responsibilities involved in mastering intent data.

Marketing: Assign a demand gen lead or program manager to stay on top of all things marketing
Sales: Assign a sales manager to stay on top of all things sales. Onboard a team of SDRs/AEs to activate the intent data by reaching out to high-intent leads and nurturing mid-intent prospects.
Operations: Given that this is a relatively elaborate, data-heavy workflow, assign a mar/sales ops to setup the initial framework, ensure accurate reporting, and
Data & research: While several tools can identify accounts visiting your website, it’s impossible to reveal the exact individual visitor. If possible, onboard a researcher to enrich company-level visitor data with the appropriate prospects to reach out to within each company. A researcher to sales rep ratio of 1:4 is recommended, but not necessary.
Executive sponsorship: Needless to say, it’s important that senior executives are aligned on who’s working on what, and why. There must be clarity in terms of deliverables for each function involved in the process.

3. Process

Bringing it all together, is the following 4-stage, 8-step intent program process to leverage intent data.

1. Stage One: Identify & Notify

As previously mentioned, there are several types of intent data. When it comes to setting up an intent-based outreach program, it’s best to start with first-party website IP-to-company identification data. For one, the website is the most voluminous touchpoint in a B2B/SaaS buyer journey. For another, starting with account identification from website traffic is a low-effort, high-impact initiative involving minimal investment.

The remainder of this article zeroes-in on leveraging first-party account identification data. That being said, the process remains largely the same for other types of intent data.

Step 1: Invest in an account identification tool

When it comes to account identification tools, there’s no shortage of alternatives. Here’s why we recommend Factors over others:

Better data-accuracy: Factors taps-into 6signal — an industry-leading account identification to reveal up to 64% of anonymous website visitors. That’s 27% more than the likes of Clearbit or Kickfire.
Cost-effective plans: Plans start as low as $99/month including dedicated onboarding support and customer success management. More pricing details here: factors.ai/pricing
Advance analytics: Given that Factors is built on strong account analytics foundations, users can achieve granular visibility into website KPIs, visitor behavior, and account timelines.

Step 2: Filter accounts based on fit and intent

Of course, not all website traffic will make a great fit for your business. Refine the total set of accounts identified to just those that fit your ideal client profile using firmographic and technographic filters.

For example, maybe you’re only interested in companies visiting your website that meet the following criteria:

Industry: Software, IT, Education
Geography: US & Canada
Employee headcount: Under 500
Technology: HubSpot, Google Ads

But even still, not every one of these companies may be ready to buy. With Factors, you can filter down the list of ICP companies to high-intent accounts based on their engagement. For example, maybe you’re only interested in ICP visitors that spend at least 60 seconds on high-intent pages such as pricing or features.

Filtering accounts based on firmographics on Factors

Step 3: Notify stakeholders in real-time

Once a criteria for high-intent, ICP accounts has been established, use Factors to push real-time alerts on Slack, MS teams, or Email when accounts that match this criteria are live on the site. This notification may be shared with sales reps to take action while the iron’s still hot.

Phew…this is a pretty involved read so we’ve split the remaining three stages of this intent program here: How To Use Intent Data To Drive Pipeline Part II. Read on to understand how to enrich, engage, and convert sales-ready accounts with intent-data and account identification.

The Complete Guide to Building A SaaS CMO Dashboard

May 3, 2023

•

0 min read

Tracking campaign performance across marketing channels can be a tedious and unintuitive process. CMOs often have to rely on individual department reports to gather a summary of how the team is performing – an endeavor that leaves many gaps and relies heavily on guesswork.

In addition to the time it takes to compile reports, derive actionable insights, and chart next-steps, the traditional way of doing things is prone to several manual errors.

The solution? The perfect CMO dashboard that helps streamline your work based on relevant analytics and metrics under one roof.

This article shows how powerful CMO dashboards can be used to drive data-driven business decisions.

TL;DR

CMO dashboards offer a holistic view of customer data-related metrics and KPIs through intuitive visualizations.

The benefits of SaaS companies using CMO dashboards include rapid decision-making, sensible use of time and resources, improved ROI, and unified visibility of marketing performance.

Before you build a comprehensive CMO dashboard, pay close attention to user-friendly design, use helpful visualizations, integrate platforms to consolidate data, and measure the right metrics/KPIs.

SaaS businesses must track metrics/KPIs such as conversions, leads, traffic, conversion rates, acquisition cost per channel, retention and churn rates, customer lifetime value, and revenue and pipeline velocity by channel source. A CMO dashboard helps visualize these metrics and KPIs with clarity.

What is a CMO dashboard?

A CMO dashboard is a tool that reports and visualizes KPIs and metrics related to a company's marketing activities across demand gen, content, paid, events, and more. It is a centralized, bird’s eye view that helps marketing executives monitor and analyze marketing initiatives and performance in real-time.

There is no hard and fast rule to building a CMO dashboard for your SaaS company. That being said, there are certain elements that are essential for marketing leaders to identify patterns, track progression, and optimize strategies to drive bottom-line business objectives.

We’ll explore these essential ingredients in later sections of this blog.

Why do CMOs need to use dashboards?

Here’s a look at the top benefits of using a well-designed CMO dashboard:

1. Improves decision-making

When making expensive business decisions, relying on guesswork can cost you heavily. CMO dashboards help marketing leaders make well-informed and accelerated decisions based on data-driven insights.

For example, a CMO dashboard can help you identify which channels and marketing campaigns are not performing if you're making budget-related decisions. It also enables you to identify the reason behind poor campaign performance and the following steps to be taken.

Let's say you have the company blog, paid advertising, and podcasts as key marketing channels. A deep dive into the dashboard will help you uncover how much revenue each channel can generate, the cost of leads from each touchpoint, and how long it typically takes them to convert.

2. Offers a quick overview of data without wasting time and resources

A CMO dashboard lets you save hours of work and wasted resources on collecting and processing raw data from scratch.

CMO dashboards extract and present an accurate overview of essential data from platforms or sources such as LinkedIn, Facebook, YouTube, articles, Google Ads, and more.

For example, let’s say you’re calculating the number of sessions on your website that come through various channels. A CMO dashboard will gather the data from all the channels, creating an easy visual for you to see which has driven the most sessions.

3. Helps identify trends and patterns

With all the data condensed onto one dashboard, CMOs and their teams can collectively take note of repetitive patterns in their target audience. This helps them further understand which type of campaigns work well on what channel and when leading to the ability to adapt campaign resources on the go.

For example, the company publishes a blog on the website every Tuesday. But they also post a video on LinkedIn on the same day. Over time, a CMO dashboard can display which content formats perform better on Tuesdays, helping the team double down their focus on that channel alone.

Key considerations when building a CMO Dashboard

An effective CMO dashboard is the central hub for monitoring marketing performance, aligning teams, and driving data-backed decisions. When designed thoughtfully, it becomes an invaluable strategic asset.

1. Intuitive and action-oriented design

A CMO dashboard is defined by its ease of use and ability to drive decisions. A cluttered, text-heavy layout overwhelms users with data but does not provide enough context to make decisions.

In contrast, a clean, visual interface tells a straightforward performance story that connects insights to actions and helps make data-backed decisions. Here are a few considerations for an insightful dashboard.

Prioritize key metrics

Prioritize the most critical metrics and add impactful visualizations like charts, graphs, gauges, and indicators to showcase them. For instance, use:

Line charts to display trends over time for metrics like web traffic, conversions, etc.
Comparison charts or pie charts to show channel effectiveness, campaign ROI, and more
Funnel visualization to showcase drop-offs across the customer journey
Alerts and gauges to highlight metrics nearing goals or thresholds

Optimize Information Absorption

Use color coding, alerts, and trends to highlight priority areas at a glance. Make sure that your dashboards have ample white space for better data absorption.

Also, include explanatory captions and annotations to provide essential context.

Offer Intuitive Interactions

Offer intuitive interactions like drill-downs, filtering, and segmenting to customize views on demand. For instance, help users:

Filter data by categories, campaigns, regions, or date ranges
Drill down from aggregate metrics to detailed data breakdowns
Isolate underperforming categories and campaigns

Such flexibility allows slicing and dicing data along different dimensions for deeper analysis.

Streamline Navigation

Create tabs or dropdowns to switch between views, campaigns, time frames, and other dimensions. Optimize compatibility across devices so users can access the dashboard anywhere conveniently.

Most importantly, align terminologies and visualizations to thought processes familiar to users through day-to-day work. Simplicity and intuitiveness accelerate adoption.

2. Unified Data Foundation Across Teams

Marketing cannot drive impact alone. Close alignment across teams provides comprehensive visibility into the end-to-end customer journey.

Break Departmental Silos

Integrate your CMO dashboard tightly with essential systems like CRM, sales analytics, web analytics, finance systems, etc. Automatically sync campaign data, lead status changes, deal progress, and other cross-functional data flows.

For instance, pull web visitor profiles from analytics platforms to enrich lead records. Or, pass lead quality assessment and scoring metrics from marketing to sales for better follow-ups.

Shared Visibility Through Attribution

Compare the performance of marketing-generated vs. sales-generated pipelines on metrics like lead quality, sales cycle times, win rates, and deal sizes.

Conduct multi-touch attribution to understand marketing's influence at each buying stage. Such unified visibility bridges departmental silos with shared goals and metrics, steering coordinated priorities across teams.

3. Flexibility to Highlight Strategic Focus Areas

While cross-functional data consolidation provides tremendous value, a one-size-fits-all dashboard rarely meets specialized business needs fully. You need the dashboard to be customizable and dynamic.

Customizable Templates

Empower users to highlight metrics aligned to their goals—broad awareness or targeted account-based sales—without relying on IT.

Provide pre-built templates for different personas and use cases that showcase industry-specific benchmarks more relevant to their context.

Dynamic Filtering and Segmentation

Offer easy-to-use customization options such as an intuitive template builder interface. Let marketers filter data views dynamically by parameters like region, customer persona, product line, etc.

Such flexibility allows teams to analyze performance through different lenses—whether for the leadership team or campaign managers. As business objectives evolve, custom-tailored dashboards stay focused on what matters most.

4. Ongoing Optimization and Iteration

No dashboard gets designed perfectly right from the beginning. As marketing campaigns and strategies adapt in response to market dynamics, your dashboards also continuously realign to maintain relevance.

User Testing and Feedback Analysis

Monitor usage patterns and user feedback to identify navigation, metric, or visualization enhancements: track clicks, hovers, and other interactions to uncover usability issues. Conduct user surveys and interviews to gather feedback.

Maintain Flexibility

Maintain flexibility for adding new datasets from emerging sources and channels. Continually experiment, test, and optimize to fulfill ever-changing information needs most effectively.

Through an intuitive and action-oriented design backed by an integrated, flexible data foundation, the CMO dashboard becomes a powerful nerve center driving shared visibility, coordinated execution, and data-informed decisions across the business.

CMO Dashboard KPIs and Metrics

A CMO dashboard can include tons of KPIs and metrics depending on what you’re trying to track. However, below are the ones that are of topmost priority:

1. Top-of-the-funnel metrics such as engagement, traffic, leads

Top-of-the-funnel metrics are brand awareness metrics like the engagement rate, traffic, and leads generated. Most SaaS marketing executives track these to attract the target audience and turn them into long-term subscribers.

‍1. Engagement rates are metrics used to measure and track the active involvement of your target audience for the content you produce. The engagement rate formula is:

2. Traffic for SaaS companies is the volume or the total number of visitors their website gets over a certain time period.

3. Leads generated is a mandatory sales KPI every SaaS company must track. Measuring leads lets you uncover issues and nurture prospects further.

Why do these metrics matter?

Top-of-the-funnel metrics help measure the overall exposure of the target audience to your marketing efforts. Tracking and measuring them gives insight into what can help minimize roadblocks that stop prospects from signing up.

2. Conversion rates and efficiency

1. Conversion rates: measure the number of targeted users who converted from unknown prospects to engaged contacts. The higher the conversion rate, the more impact your marketing strategies have. The formula to calculate the conversion rate is:

2. Efficiency: In marketing, the ROI measures the overall performance of your marketing efforts, and conversion rates directly indicate the performance. That means increasing conversion rates while reducing acquisition costs promises a better ROI and shows better strategy efficiency. The formula to calculate marketing efficiency is:

Why do these metrics matter?

Conversion rates and efficiency directly reflect how well your SaaS marketing activities are executed and determine the overall effectiveness of your business campaigns.

3. Cost of acquisition by channel

It’s best to track certain KPIs by marketing channels, such as social media, emails, ads, organic search, etc. Calculating the cost of customer acquisition (CAC) for each channel is one such KPI that indicates the marketing expenses spent on obtaining customers.The formula to calculate CAC by channel is:

Why does this metric matter?

Measuring CAC lets you decide whether or not to pursue marketing for a particular channel and demonstrates high-performing marketing channels having low CAC.

4. Retention and churn rates

Customer retention and churn rates are opposites that indicate the number of customers retained or lost over a time period. The formula to calculate churn rate is:

Why are these metrics important?

Customer churn and retention rates are one of the most important metrics for SaaS CMOs. Measuring churn rate can help shed light on why subscribers are refusing to renew your service, and based on high or low retention rates, you can decide whether to pursue the same strategies or refresh them.

5. Customer lifetime value

Customer lifetime value, or CLV, indicates the average pay throughout a customer’s relationship with your company. It is a critical SaaS KPI to showcase revenue as it conveys a customer’s worth on average. The formula to calculate CLV is:

Why does this metric matter?

CLV is a critical SaaS business viability measure. It is essential for understanding the business value each customer brings and your SaaS company’s long-term potential.

6. Revenue and pipeline velocity by channel source

1. Revenue by channel source tracked by CMOs indicates how well their ads, campaigns, and other marketing efforts perform based on their source. Additionally, it tells you the aggregate revenue earned from successful conversions from each outlet.

2. Pipeline velocity by channel source is a key KPI indicating the speed at which leads move through your sales pipeline for each channel source.

Why do these metrics matter?

A high pipeline velocity means smoother onboarding processes and better conversions. So tracking this and revenue by channel source over various periods lets you improve conversions from each source.

7. Revenue Growth Percentage

Revenue growth percentage indicates how rapidly total company revenue increases over a set time, typically month-over-month or year-over-year. It shows the overall momentum and health of the business.

The formula to calculate revenue growth is straightforward—take the revenue difference between the current and past periods and divide that by the one-time period revenue.

For example, for year over year revenue growth, use the formula:

((Current Yearly Revenue - Last Year's Yearly Revenue) / Last Year's Yearly Revenue) x 100.

Why does this metric matter?

Monitoring rapid or declining growth % signals how well marketing and sales efforts are faring and hitting targets. When coupled with cost metrics, it also showcases profitability trends. Understanding growth by revenue streams also enables executives to double down on the highest traction channels.

8. Customer Lifetime Value

Customer lifetime value totals the likely earnings a business can generate from customers throughout their tenure. In essence, it conveys an average customer's worth.

The formula factors average order size, purchase frequency in a given period, and the average lifespan.

For instance, CLV may be calculated as: CLV = Average Order Value x Purchase Frequency Per Year x Average Lifespan in Years.

Why does this metric matter?

Tracking CLV over annual cohorts helps spotlight content, features, or channel innovations that make customers stickier. Comparing CLV vs acquisition cost also determines the breakeven period to recover expenses.

9. Cost Per Lead

Cost per lead signifies the average expenditure to generate a qualified marketing lead. It is calculated by dividing total lead gen marketing spend by the number of leads captured.

CPL can be calculated as: Total marketing dollars spent / Number of leads

If you spent $1000 to get 10 customers, that’s 1000/10 = $100 — Your CPL is $100.

Why does this metric matter?

Monitoring CPL trends determines the influence of brand equity on the sales funnel—a strong brand lowers CPL over time.

Comparing CPL by channel also helps optimize spending by identifying the lowest-cost customer acquisition sources. Analyzing CPL alongside customer lifetime value further ascertains profitable activities.

10. Brand Search Volume

Brand search volume measures monthly search queries for your brand name and keywords. Sudden surges or declines show changing consumer interest.

Why does this metric matter?

Tracks brand visibility gains/losses to correlate awareness-building campaigns and events. Guides keyword targeting and content strategies.

Creating Effective CMO Dashboards in Factors AI

Over the course of this article, we’ve covered what a CMO dashboard is, what its benefits are, and a few common metrics for CMOs to track. But constructing a comprehensive CMO dashboard is easier said than done — unless of course, you leverage a tailor-made dashboarding tool like Factors.

Factors unifies and reports data across complex buyer journeys involving multiple stakeholders, touchpoints, and channels under one roof. What does this mean for you? No more individual tools to analyze campaign performance, website engagement, and pipeline/revenue related metrics.

It’s simply all the metrics you care about as CMO in one, intuitive, customizable dashboard. Here are a few nifty features loved by CMOs:

Ad hoc filters and breakdowns: Slice and dice metrics and KPIs with a wide range of filters and breakdowns to answer questions like: “How does conversion rate vary between companies with at least 200 employees and smaller teams of less than 50?” or “What’s the difference in sales velocity between leads from paid search and organic social?”
Automated AI-fueled insights: It’s one thing to have your data in one place — but how can CMOs make sense of the numbers? Factors offers automated insights into what’s helping and hurting a specific conversion goal. What’s driving demo form submissions? Our Explain engine may suggest Linkedin campaigns and the pricing page have a positive influence while Display ads and email outreach is limiting performance. This helps the larger team improve resource allocation and drive ROI.
Custom funnels, KPIs, and properties: Every business has different requirements. This is no different when it comes to reporting and dashboarding needs. Factors supports limitless customizations to KPIs and properties so CMO dashboards can be tailor-made to the what matters most to you.

Curious to see Factors in action? Schedule a personalized demo here!

The Ultimate Guide to Marketing Analytics for SaaS Companies

May 3, 2023

•

0 min read

Marketing analytics has become an integral part of any successful marketing strategy.

The industry is expected to grow at a CAGR of 14.8% between 2023 and 2028. Meanwhile, businesses of all sizes must spend the time to upgrade their in-house tech and employee skill-set to stay ahead of the curve.

But with the industry peppering buzzwords and jargon, marketing analytics can seem more complicated than it actually is.

In this guide, we’ll work to make the complex simpler. We’ll discuss what marketing analytics is, why it is necessary, which teams and people in a company should look into it, common limitations and pitfalls, and more. Let’s get started.

What is Marketing Analytics?

Marketing analytics refers to the analysis of data to gain insights into the performance of marketing campaigns and activities. It relies on the number of leads generated, conversion rates, customer acquisition cost (CAC), and customer lifetime value (LTV). Analyzing these metrics can help marketers and founders pave the way for marketing campaigns.

For instance, marketing analytics can help businesses understand which marketing channels or strategies are generating the most leads or conversions, and which ones may need improvement. It can also help identify trends and patterns in customer behavior, preferences, and buying habits, enabling businesses to make more informed decisions about their marketing efforts.

This is done through the use of tools like Google Analytics, Looker Studio, Factors.ai, and others for data visualization, statistical analysis, and predictive modeling.

The data is analyzed from various sources, such as website traffic, social media platforms, email campaigns, and Customer Relationship Management (CRM) systems.

The Benefits of Marketing Analytics

Marketing analytics offers multiple benefits in a B2B context. It helps businesses with interpreting data and making the most accurate and informed decisions. But that’s just one aspect of it. Let’s take a look at some other benefits of marketing analytics:

Improves Targeting

Marketing analytics enables you to identify the most relevant and receptive audience for your product or service. Then combining demographic, psychographic, and behavioral metrics, you can create a detailed customer persona that represents your ideal target audience. This data-driven approach allows you to tailor your messaging, offers, and content to resonate with these individuals, ultimately leading to higher conversion rates.

For instance, suppose your marketing analytics reveals that your most engaged customers are millennial entrepreneurs in the tech industry. In that case, you can fine-tune your marketing campaigns by focusing on the channels they frequent—such as LinkedIn and Twitter. Then begin creating content around industry trends, tips for startup growth, or case studies of successful tech entrepreneurs while subtly pitching your product or services.

Reduces Cost of Acquisition

The cost of acquiring a new customer can often exceed the expenses related to retaining an existing one. The average customer acquisition cost (CAC) including all SaaS industries is $704. Marketing analytics helps businesses identify the most cost-effective channels and methods for customer acquisition by studying metrics like cost-per-click, cost-per-lead, and return on ad spend.

Let’s take an example here. Say your marketing analytics data shows that LinkedIn ads are generating a lower cost per acquisition (CPA) and higher conversion rate compared to Facebook ads. In this case, you can shift a larger portion of your ad budget to LinkedIn, driving down your overall cost of acquisition.

Improves the Customer Experience

86% of buyers are willing to pay more for brands that offer great customer experience. And SaaS companies doing $1 billion annually can expect to earn an additional $1 billion with just 3 years of investing in customer experience.

Analyzing customer feedback data can help SaaS marketers identify areas of improvement in their products or services. This leads to a better overall experience for customers. Marketing analytics can also help companies understand customer touchpoints, identify gaps in their communication strategies, and improve customer support.

Helps with Customer Retention

As time goes by, fewer and fewer customers stick around. This can be clearly demonstrated with the retention curve.

However, spending money to retain existing customers is often more cost-effective than acquiring new ones.

Existing customers are 50% more likely to buy a product and spend 31% more on average than new customers. Marketing analytics can help businesses identify patterns and trends in customer behavior that may indicate potential churn or dissatisfaction.

For instance, if your marketing analytics reveals that customers who don't engage with your email campaigns are more likely to churn, you can modify your campaigns to launch a re-engagement strategy. You can target these at-risk customers with personalized content and offers to reignite their interest and loyalty. Sometimes, special pricing or preferential rates go a long way for customers.

Unveils Upselling Opportunities

Upselling is a powerful strategy in the B2B SaaS world. An average SaaS business generates 16% of its annual contract value (ACV) from upselling to customers. Companies doing $40 to $75 million annually can attribute twice as much revenue to upselling. With marketing analytics, you identify existing customers who are most likely to benefit from and be receptive to upgrading their current plans or purchasing additional products or services.

For instance, with marketing analytics data you may notice a few high-usage customers that could benefit from improved speed or better service offerings in your higher plans. Personalizing an upsell for those businesses and accounts can help you better improve your bottom lines in the long run.

What’s the Difference Between Product Analytics and Marketing Analytics?

Product analytics and marketing analytics are two important types of analytics that businesses need to use for making informed decisions. Unfortunately, these terms are used interchangeably and can cause confusion. Let’s look at the differences between product analytics and marketing analytics.

Product analytics analyzes the product experience. This type of analytics is generally performed on the data of users already using the product. It focuses on understanding how users interact with a product, including feature adoption, engagement, and product usage. With product analytics, the goal is to drive product-led growth by identifying areas for improvement, prioritizing feature development, and optimizing user experience.

Marketing analytics, on the other hand, helps identify how effective your marketing campaigns are. It helps identify how easily customers can find your product or website, what channels are working best for your marketing, and how many users are converting into paid users through the journey. Metrics for marketing analytics include lead generation, conversion rates, customer acquisition cost (CAC), and customer lifetime value (LTV).

For B2B businesses, both product and marketing analytics are important for driving growth. Product analytics helps businesses optimize product offerings and user experience. Marketing analytics helps companies improve their marketing strategies, target their audience more effectively, and allocate resources better.

Are Marketing Analytics and Marketing Attribution the Same Thing?

Marketing analytics and marketing attribution are complementary, yet distinct, disciplines within the realm of digital marketing. While both are essential for evaluating and optimizing marketing efforts, they serve different purposes and bring unique insights to the table. In this article, we will delve into the nuances of each concept, highlighting their primary focus, use cases, metrics, tools, and more.

Marketing Analytics vs Marketing Attribution - Quick Comparison

Aspect	Marketing Analytics	Marketing Attribution
Primary Focus	Evaluating overall marketing effectiveness	Measuring the impact of touchpoints on conversions or other outcomes
Use Cases	Identify high-performing channels, calculating CAC & LTV, evaluating ROI, tracking customer engagement, and informing marketing strategy	Evaluating individual channel effectiveness, identifying influential touchpoints, optimizing spend, tailoring messaging, and informing marketing strategies
Metrics	CAC, LTV, Churn Rate, Retention Rate, ROI	Measured using models such as Single-Touch Attribution, Multi-Touch Attribution, Position-Based Attribution, Custom Attribution
Tools	Google Analytics, Adobe Analytics, Mixpanel, Tableau, HubSpot	Factors.ai, Adobe Marketo, Dream data,

Marketing Analytics

Marketing analytics encompasses the measurement, management, and analysis of marketing performance data to optimize marketing effectiveness and maximize return on investment (ROI). Its primary focus is to provide a comprehensive understanding of marketing efforts, from the impact of individual campaigns to the overall health of a marketing strategy.

Use Cases:

Identifying high-performing marketing channels
Calculating customer acquisition cost (CAC) and customer lifetime value (LTV)
Evaluating marketing ROI
Tracking customer engagement and retention
Analyzing data to inform marketing strategy and decision-making

Metrics:

Here are some of the marketing analytics metrics that you must keep a watch on.

Customer acquisition cost (CAC): This metric helps you identify the cost of acquiring a new customer. It accounts for all the marketing and promotional costs involved in reaching and converting the customer.
Lifetime value (LTV): Once a customer is converted, how long do they remain a paying customer? To find this value, note the length of time that each customer has stayed with your business and the total revenue generated by each. Then, multiply the average revenue per customer by the average length of time (lifespan). For example, if you have 100 customers paying, on average, $300 per month for 6 months, your customer lifetime value will be $300 x 6 = $1800.
Churn Rate: How many of your customers are dropping off after they turn into paying customers? In fact, you can even count the churn rate for your free users as this can help you start digging deeper into the reasons why they don’t sign up for one of your paid plans.
Retention Rate: This is the opposite of the churn rate. Here we check how many customers stick around for a specific period of time and more. For example, you may want to consider a customer as a retained one if they continue to pay for your SaaS for longer than 3 consecutive months.
Return on investment: This metric is a must for businesses, no matter the industry. In the case of B2B SaaS businesses, this metric lets you understand how much money you are making based on the marketing spend.

Tools:

Google Analytics: This is the most popular tool for marketing analytics—majorly because it’s free of cost. Google Analytics provides a wealth of information about traffic, user behavior, and much more.
Factors: Factors is a powerful marketing analytics platform that specializes in B2B visitor identification, account analytics, and more. It integrates with your existing marketing stack and helps businesses reveal anonymous website visitors, decode customer journeys, and drive marketing ROI.
Adobe Analytics: Adobe Analytics has a range of tools for tracking customer behavior, segmenting users, and identifying trends to improve overall marketing performance.
Mixpanel: Mixpanel is more focused on product analytics. It enables businesses to monitor user interactions within web and mobile applications.
Tableau: Tableau helps marketers transform raw marketing data into interactive visualizations that are easy to understand and share.
HubSpot: HubSpot provides businesses with a holistic view of their performance and the tools necessary to optimize their strategies. From tracking website traffic and user behavior to measuring the effectiveness of email campaigns and social media outreach, it enables companies to make smarter marketing decisions and achieve better results.

Marketing Attribution

Marketing Attribution is the process of determining the value and impact of various touchpoints along the customer journey, helping marketers understand which channels, campaigns, and tactics are most effective in driving conversions and other desired outcomes. Attribution primarily focuses on assigning credit to specific marketing efforts that contribute to a conversion, sale, or other predefined goals.

Use Cases:

Evaluating the effectiveness of individual marketing channels and campaigns
Identifying the most influential touchpoints in the customer journey
Optimizing marketing spend and resource allocation
Informing marketing strategy and tactics based on attribution insights
Tailoring messaging and targeting to maximize conversion potential

Attribution Models:

There are several attribution models available that help businesses assess the impact of their marketing efforts. Here is a breakdown of some of the most common types:

Single-Touch Attribution: Assigns credit to a single touchpoint, either the first touch or the last touch. Common single-touch models include First-Touch Attribution, Last-Touch Attribution, and Last Non-Direct Touch Attribution.
Multi-Touch Attribution: Distributes credit across multiple touchpoints throughout the customer journey. Examples of multi-touch models are Linear Attribution, U-Shaped Attribution, and Time Decay Attribution.
Position-Based Attribution: This attribution model allocates credits based on the position of a touchpoint in the customer journey. For instance, it gives 40% of the credit to both the first and last ad interactions and corresponding keywords. The remaining 20% is spread across the other ad interactions on the user journey.
Custom Attribution: Utilizes data and machine learning algorithms to create custom attribution models tailored to the unique needs of a specific business or industry. This approach allows for a more accurate representation of the customer journey and the impact of various marketing channels and tactics.

Tools:

Factors: Factors is an AI-driven marketing attribution platform that provides detailed insights into the impact of each touchpoint on your customer journey. With its advanced modeling capabilities, Factors helps businesses make informed decisions on marketing spend and resource allocation.
Adobe Marketo Measure: A part of the Adobe Marketo suite, Measure offers powerful marketing attribution and revenue planning features. By connecting marketing and sales data, Measure enables businesses to accurately attribute revenue to specific marketing efforts.
Dreamdata: Dreamdata is a B2B revenue attribution platform that allows you to track and analyze the performance of your marketing efforts across all channels. By unifying data from various sources, Dreamdata provides a holistic view of your customer journey and helps optimize your marketing strategy.
Ruler Analytics: Ruler Analytics is a marketing attribution platform that connects closed revenue data with the customer journey. It provides insights into which marketing channels are driving conversions, allowing businesses to optimize their efforts and improve ROI.

Who Should Be Thinking About Marketing Analytics at SaaS Companies?

Marketing analytics helps businesses measure the effectiveness of their marketing campaigns, optimize strategies, and make data-backed decisions to drive growth. But who should be thinking about marketing analytics at SaaS companies? Generally, it is CMOs, marketing executives, and CROs who stay updated with this information.

But, there's more to the story.

While it's essential for top-level executives and decision-makers to understand marketing metrics, it's not practical for everyone involved to monitor every single metric. Requiring the marketing team to constantly share their progress is counter-intuitive to progress as well. That’s where dashboards help teams stay in sync and keep tabs on what’s happening within marketing.

Dashboards offer a streamlined and efficient way to stay on top of the effectiveness of marketing strategies. They present data in a visually appealing and easy-to-understand format, allowing for quick insights and adjustments when needed. Here are a few benefits of dashboards.

Enhanced collaboration: A well-designed dashboard helps teams across the board to stay updated with the changes in marketing. It also reduces the communication required to get data from individual teams as everyone can directly pull data from the dashboards. This increases transparency between teams.
Increased accountability: Because of the increased transparency, teams, and individuals have accountability for the tasks assigned to them. This allows for greater productivity across teams and helps things progress faster.
Customization: Dashboards are designed to be completely customizable. You do not need to showcase the same verbose data to everyone involved. Dashboards can help you summarize and visualize the required data based on who you want to demonstrate or showcase the data to.

If you want to implement a marketing dashboard within your company, we have an in-depth article on CMO dashboards. This will guide you through the process of designing a dashboard that serves the unique needs of your SaaS app development company.

Addressing Common Marketing Analytics Challenges

As businesses continue to evolve and adapt to the digital era, marketing analytics has become a vital aspect of marketing success. However, there are several common challenges that marketers face when trying to harness the power of data analysis.

Siloed data

The importance of seamless data integration cannot be overstated. With various marketing tools and platforms being used simultaneously, data can become fragmented and difficult to consolidate. Apart from that, customer data can get siloed at each of the touchpoints as well.

This siloed data can lead to an incomplete view of your marketing efforts and hinder your ability to make data-driven decisions. Marketing attribution tools like Factors combine data from multiple platforms and create a unified timeline that helps you view all the touchpoints of your customers in a single place.

Not knowing what to track

Identifying the right metrics to track is essential for marketing success. Focusing on the wrong metrics or not tracking them at all can lead to misguided decision-making. In fact, tracking a metric incorrectly can lead to worse outcomes than not tracking it at all.

For example, if you incorrectly attribute the success of your conversions to your paid ads, you may end up spending more on the wrong channel and wasting your marketing efforts.

Incorrect understanding of metrics

Metrics should be analyzed in tandem with other data to gain meaningful insights. For example, if the cost of acquisition in one quarter is dramatically lower than that of the previous two quarters, it could be the direct result of pausing a poor-performing marketing campaign.

But only looking at the CAC may lead to incorrect conclusions—CAC is going lower and thus your profits are going up.

Lack of automation and limited visualizations

Manual data analysis can be time-consuming, and error-prone, and ultimately limit your ability to make the most of it. Automating data collection and analysis processes is essential for maximizing efficiency and accuracy. Also, visualizing data through intuitive dashboards and reports enables easier understanding for everyone involved.

Factors address these common challenges by offering a powerful marketing analytics platform featuring seamless integrations, automation, and advanced visualization capabilities. Comprehensive marketing analytics and attribution solutions like Factors help overcome these challenges and ultimately achieve better results from your marketing efforts.

Top Marketing Analytics Use Cases for SaaS Companies

Marketing analytics can provide valuable insights and drive growth in various aspects of a SaaS company’s marketing efforts. The three key use cases for marketing analytics include acquisition and conversion tracking, campaign performance analysis, and customer segmentation and personalization. Here’s what each of them means:

1. Acquisition and Conversion Tracking

Acquisition and conversion tracking allows SaaS businesses to monitor how efficiently their marketing efforts are attracting and converting customers. For example, a SaaS company offering project management software might use acquisition and conversion tracking to analyze the sources of their website traffic. This could include social media platforms, search engines, and email marketing campaigns. They can then determine which channels are most effective in driving new users to sign up for their software. If the analysis reveals that content and SEO are generating a high number of sign-ups, the company can allocate more resources to that platform to capitalize on its success.

2. Campaign Performance Analysis

Campaign performance analysis evaluates the effectiveness of marketing campaigns and helps improve the campaigns through data. This involves monitoring click-through rates, conversion rates, and cost per acquisition, to determine the overall success of each campaign.

Imagine a SaaS company specializing in human resources software launches a Google Ads campaign targeting HR managers.

Campaign performance analysis can be used here to evaluate the effectiveness of the ads. If the data indicates that one type of ad is outperforming the others, the company can optimize the campaign by allocating a higher budget to the more successful ad. This constant analysis and improvement can lead to more efficient marketing campaigns and higher ROI.

3. Customer Segmentation and Personalization

Customer segmentation and personalization involve grouping customers based on shared characteristics and tailoring marketing messages and offers to meet their specific needs.

For instance, a SaaS company that provides email marketing software could segment its customers into groups based on their industry, company size, or the frequency of their email campaigns.

They could then create content and offers targeted at each segment. A small e-commerce business might receive tips on how to maximize its email open rates during the holiday season. A large enterprise client, on the other hand, might receive a case study showcasing how their email marketing success has successfully scaled email campaigns for similar organizations.

Grow your business with streamlined marketing analytics

Marketing analytics is a powerful tool for driving growth and improving marketing performance in B2B companies. Focusing on key use cases, such as acquisition and conversion tracking, campaign performance analysis, and customer segmentation and personalization, will enable you to make data-driven decisions and optimize your marketing efforts.

As a result, you'll attract more customers, improve customer satisfaction, and ultimately, increase your company's revenue. Don't miss out on the potential that marketing analytics can unlock for your SaaS company—start harnessing the power of data with Factors.ai today.

FAQs

Why is marketing analytics important?

Marketing analytics makes marketing effective. It offers deep insights into the preferences and behavior of your customers. It allows you to shape the marketing campaigns in accordance with your customer’s expectations and helps you make data-backed decisions rather than relying on intuition and experience.

What are the three types of analytics that can be used in marketing?

Descriptive analytics, predictive analytics, and prescriptive analytics.

Descriptive analytics analyzes historical data to understand past performance.
Predictive analytics uses data and statistical algorithms to forecast future outcomes
Prescriptive analytics provides recommendations on how to optimize marketing efforts based on data-driven insights.

Identify & Target High-Intent Accounts With Webhooks & Pipedrive

May 3, 2023

•

0 min read

Target the right accounts, at the right time with intent-based outreach

B2B sales teams spend a lot of time and effort reaching out to cold prospects only to achieve disappointing results. In fact, even successful benchmarks tag the average cold-call response rate at just 2%.

And honestly, It’s not difficult to see why.

While it’s simple enough to find lists of companies and contacts that fit your ideal client profile, it’s a monumental challenge to convince prospects to consider your solution when they’re not in the market for one.

So what’s the alternative to reaching out to the right accounts at the wrong time?

Reaching out to the right accounts at the right time of course! Or more specifically, it’s intent-based outreach based on the goldmine of anonymous, sales-ready companies already visiting your website.

The following guide explores how to identify and target sales-ready accounts with the combined powers of Factors’ account identification and Pipedrive webhooks. We first discuss how this integration works, before delving into a handful of use-cases.

How It Works: Pushing data back into Pipedrive

Factors taps into industry-leading IP-lookup technology to identify up to 64% of anonymous website traffic at an account-level — without the need for form submissions. This includes company names as well as firmographics such as geography, industry, employee headcount, revenue range and more.

In addition, Factors auto-tracks account-level website activity, engagement, and intent with advanced analytics. This includes page views, button clicks, scroll-depth, account timelines, funnels and more.

With this information, users can filter the total set of anonymous website visitors down to ICP accounts that have expressed buying intent:

ICP criteria: Filter down traffic based on firmographics such as industry, headcount and revenue-range to identify accounts that fit your ideal client profile.
Intent criteria: Filter down traffic based on intent signals such as high-intent page views such as pricing, time-spent on page, and percentage scroll-depth to identify sales-ready buyers.

In short, access a list of high-intent ICP accounts that are already visiting your website but are yet to submit a form or sign-up.

Now, with webhooks and Zapier, it’s easier than ever to automatically push all this identification data from Factors into any other tool your team uses. This includes ad platforms, marketing automation platforms, and, in this case, Pipedrive CRM.

How will this help? Rather than going after cold leads with negligible chances of conversion, sales reps can view, segment, and target sales-ready accounts inside Pipedrive. As we’ll see in the next section, this dramatically simplifies and improves targeted sales outreach.

Implementing Webhooks on Factors is easy as pie. See how here.

Use-cases: Making the most of your website traffic

1. Identify new business opportunities

Factors surfaces anonymous, high-intent companies visiting your website. As previously discussed, this data can be filtered down to high-fit, high-intent accounts.

Using webhooks, this data can be pushed from Factors into Pipedrive. In other words, you can automatically create organizations inside Pipedrive for visitors that match your ICP and intent criteria.

For example, webhooks can be configured to create a new company when a visitor from a US-based software company with at least 250 employees is live on your website.

Here are a few more examples of what you can see inside your CRM with Factors:

Accounts that visit a landing page through a search ad but fail to submit a form
Software companies with at least 500 employees visiting high-intent pages like pricing
US-based companies that have read through at least half a product comparison blog

Rather than relying on the 5% of website traffic that submits a form, teams can identify and target a deep new pool of potential pipeline — all within Pipedrive. What’s more? Alerts can be relayed to sales reps in real-time through Slack or MS teams so they can immediately reach out to live prospects.

2. Stay on top of existing target accounts

In addition to recording new accounts visiting your website, Factors can be used to monitor and update data for target accounts that already exist within Pipedrive.

For example, say an account clicks on a search ad, submits a demo form, but never schedules time on your calendar. While the account's data is available in Pipedrive, it can be tedious to track and update their actions post the demo form submission.

To solve for this, Factors can automatically update CRM properties based on trigger criterias when account return to your website. Let’s say that the same account is back reading a product alternatives blog or visiting the pricing page after a couple of weeks. This event can be updated within Pipedrive, including their last active time.

Sales reps can be notified with real-time when high-intent events take place so as to be able to immediately reach out to accounts and improve the odds of conversion.

3. Accelerate deals with behavioral data

Certain marketing material may or may not be relevant depending on the audience in question. For example, an enterprise-level account may be especially interested in security compliance related content. An early-stage start-up, on the other hand, may find content around cost-effective pricing more appealing.

Factors can track how various types of companies are interacting with your website to understand what target accounts care about most. This data can be pushed back into Pipedrive so sales reps can easily assess a prospect’s interactions, priorities and pain-points before jumping into a sales call.

For one, sales reps can accelerate deals by personalizing the customer experience. For another, marketing teams can gauge what resonates best with the target audience and finetune content efforts accordingly.

4. Rekindle lost opportunities

Use Factors to track how prospects who have dropped off the funnel or former customers are returning to engage with your website. For instance, maybe a client who churned a couple of quarters ago is back interacting with a page that highlights a new feature release.

This may be an intent-signal that the account is reconsidering your product. It might be a good idea for sales reps to reach out and share some relevant information on what’s new. Of course, this doesn’t necessarily guarantee a conversion. But it’s far more effective than reaching out to an ice cold prospect.

This guide has covered a handful of ways in which pushing visitor data back into Pipedrive can be helpful. Ultimately, the goal is to align account data with relevant stakeholders and technologies in order to:

Drive intent-based sales outreach
Refine ABM efforts and spends
Optimize retargeting campaigns

There are countless other use-cases with account identification working in conjunction with CRMs, MAPs, and more. With webhooks, Factors can push valuable website account data to nearly any platform on the planet. How you make the most of that data is really up to you — the possibilities are endless.

Discover Sales-Ready Accounts With Zoho & Webhooks

May 3, 2023

•

0 min read

Target the right accounts, at the right time with intent-based outreach

And honestly, It’s not difficult to see why.

While it’s simple enough to find lists of companies and contacts that fit your ideal client profile, it’s a monumental challenge to convince companies to consider your solution when they’re not in the market for one.

So what’s the alternative to reaching out to the right accounts at the wrong time?

Target the right accounts, at the right time

The following guide explores how to identify and target sales-ready accounts with the combined powers of Factors’ account identification and Zoho webhooks. We first discuss how this integration works, before delving into a handful of use-cases.

How It Works: Pushing visitor data back into Zoho

Factors taps into industry-leading IP-lookup technology to identify up to 64% of anonymous account visiting your website. This includes company names as well as firmographics such as geography, industry, employee headcount, revenue range and more.

‍

In addition, Factors auto-tracks website activity and engagement at an account level with advanced analytics. This includes page views, button clicks, scroll-depth, account timelines, funnels and more.

With this information, users can filter the total set of anonymous traffic down to ICP accounts that have expressed buying intent:

ICP criteria: Filter down traffic based on firmographics such as industry, headcount and revenue-range to identify accounts that fit your ideal client profile.
Intent criteria: Filter down traffic based on intent signals such as high-intent page views such as pricing, time-spent on page, and percentage scroll-depth to identify sales-ready buyers.

In short, access a list of high-intent ICP accounts that are already visiting your website but are yet to submit a form or sign-up.

Now, with webhooks and Zapier, it’s easier than ever to automatically push all this data from Factors into any other tool your team uses. This includes ad platforms, marketing automation platforms, and, in this case, Zoho CRM.

How will this help? Rather than going after cold leads with negligible chances of conversion, sales reps can view, segment, and target sales-ready visitors inside Zoho. As we’ll see in the next section, this dramatically simplifies and improves targeted sales outreach.

Implementing Webhooks on Factors is easy as pie. See how here.