Himani Trivedi

Here we go again. 

Steve from sales is beaming at the office party. And why wouldn’t he be? The team can’t get enough of the star performer who closed ANOTHER high-value deal. 

Everybody seems to be missing out on the fine print, however. When asked “How did you hear about us?” the prospect promptly replied-” Oh! I registered for your webinar through LinkedIn and quite enjoyed it” 

What they fail to mention is that they also compared their current solution to your product with blogs from your website. In fact, the final demo booking came through a click from a search ad. 

Your team isn’t the only one suffering from salesman Steve syndrome. B2B marketing teams often struggle to quantify their impact on pipeline. The following article explores what revenue attribution is and how it can help with the same.  

What is revenue attribution?

Revenue attribution is the process of identifying and assigning value to marketing touchpoints based on their relative influence on conversions, pipeline, and revenue.

With revenue attribution, marketing teams can gain valuable insights into which strategies and activities are most effective in driving bottom-line impact. 

This information enables businesses to make data-driven decisions, optimize their marketing budgets, and improve overall marketing performance. Ultimately, revenue attribution empowers organizations to better understand their return on investment (ROI) make informed decisions to drive growth and profitability.

So if Steve’s team had conducted a comprehensive revenue attribution analysis, they’d assign “credit” to all the channels involved in the deal: paid and organic marketing channels, offline events, AND sales. 

And how much “credit” would each channel get for the sale? That is based on the revenue attribution model they choose to use. 

How do you measure revenue attribution?

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Revenue attribution can be leveraged with a wide range attribution models, each with different use-cases based on the industry, length of sales cycle, number of touchpoints, and so on. 

For example, a B2C company with a short sales cycle and single decision-makers can rely on simplistic single-touch models. Whereas B2B companies with long customer journeys and multiple decision-makers must use multi-touch revenue attribution models — especially if they’re interested in figuring out how multiple channels contribute to revenue. 

A certain attribution model will help discover the best TOFU channels while another may help understand what channels convert the most customers. 

To understand the different attribution models, let us take the example of a customer: Bart. Bart is a mid-level manager for an e-commerce business. He stumbles upon a checklist on LinkedIn that helps identify customers with high CLV. He starts the limited trial version of the product and then follows the company’s page on Linkedin, which announces a webinar on customer loyalty. He signs up and finds the session very helpful. He decides to search for the company and look into the full product, complete with all of its capabilities and features. In the next quarter, when his boss gives him a higher sales target, he looks into the pricing page. Soon after, he books a demo with the sales team.

Now if we were using attribution models to assign credit in this scenario- 

Single Touch Attribution

• First Touch Attribution: Attributes revenue or credit solely to the first touchpoint that initiated the customer's journey. It is ideal for businesses looking to understand what channels get them the most new customers. In Bart’s case the channel is LinkedIn 
• Last touch attribution: Attributes revenue solely to the last touchpoint in the customer’s journey. It is beneficial for companies looking to understand what channels drive the most conversions. In this case, that channel is the demo page.

Multi-touch Attribution

Attributes revenue to multiple touchpoints in the customer journey. 

Rule-Based Attribution

• Linear Attribution: Distributes revenue or credit evenly across all marketing touchpoints in the customer's journey. It does not take into account the impact of individual channels in the customer journey. In Bart’s case, all the channels – organic, inbound and sales would get equal credit.
• Time Decay Attribution: Assigns more revenue or credit to touchpoints as they near conversion i.e. the touchpoint right before the conversion will be assigned the highest credit. It helps understand the bottom-of-funnel and conversion channels effectively. In Bart’s case, the channel with the highest attribution is direct. 
• U-Shaped Attribution: Gives more weight to the first and last touchpoints while allocating a smaller portion to the intermediate touchpoints.  This attribution model helps separate the channels which provide leads and the ones that provide conversions. In Bart’s example, the LinkedIn post and the demo page are touchpoints with highest attribution. 
• W-Shaped Attribution: Emphasizes the first touchpoint,the touchpoint responsible for opportunity creation, and the last touchpoint.  In Bart’s case, LinkedIn, visit to the pricing page and the demo are the three touchpoints with highest attribution. 

That said, there’s a lot that needs to be taken into consideration when picking an attribution model. Each has its advantages and use cases which you should take into account based on your requirements. 

Are marketing attribution and revenue attribution the same thing?

Marketing attribution focuses specifically on attributing the value or impact of marketing touchpoints or activities in driving customer conversions or sales. It aims to identify which marketing channels, campaigns, or tactics are responsible for generating leads or influencing purchasing decisions.

On the other hand, revenue attribution goes beyond marketing and takes a more comprehensive approach. Revenue attribution considers the contributions of various departments or functions within an organization, such as marketing, sales, customer success, and other operational activities, in generating revenue.

Revenue attribution helps analyze multiple touchpoints and interactions across different functions can influence customer behavior and contribute to revenue generation. Different revenue attribution models can be used to assign value to these touchpoints and activities, whether they are marketing-related or not, to gain a holistic understanding of the revenue-generating process.

Who should be concerned with revenue attribution?

The customer journey and buying process for B2B products are long and complex, and revenue attribution can help bridge the gap between different departments/teams. Unfortunately in most b2b companies, only revenue teams are concerned with revenue attribution, keeping all revenue efforts siloed. 

By understanding the contributions of different teams, channels, and campaigns in revenue generation, teams can allocate resources more effectively. They can identify areas that require increased investment or support based on their revenue-generating potential and ensure that the organization's financial resources are allocated strategically for maximum impact. 

For marketing teams, revenue attribution helps identify effective tactics and channels and refine targeting. According to Alex Sofronas- “it almost acts as a GPS”, helping teams navigate where they are headed by aligning data and insights with organizational goals. Similarly, it helps customer support teams to personalize interactions and make data-driven decisions to drive revenue. 

Why is attributing revenue so important for businesses? 

Revenue attribution opens various growth avenues. Teams can leverage the added insights to accelerate the purchase decision and optimize spending. For businesses at the beginning of their growth curve, it can help develop templatize marketing plans or create iterative action plans. Here are some of the other benefits of revenue attribution: 

Understanding the customer journey

Revenue attribution helps businesses gain a better understanding of the customer journey. B2B sales cycles are often 6-9 months long. Analyzing individual sessions or website traffic through analytics tools only provides a partial view. Ad platforms like LinkedIn, Facebook, and Twitter may focus on the current month's Return on Advertising Spend (ROAS) without considering the long customer journey. If the impact of an ad is realized 6 months later, when a customer moves down the funnel and books a demo or makes a purchase, revenue attribution will help figure this out. By accounting for the entire journey through detailed revenue attribution businesses can make more informed decisions.

Shining a light on effective strategies and touchpoints

Analytics tools track individual sessions or devices, not account-based activities. With revenue attribution businesses can identify the most effective touchpoints for individual customers and plan their spending accordingly. It can also help avoid premature assumptions about campaign success or failure.  

Promoting sales and marketing alignment

By following the account from the first touch, attributing leads to their sources. Unlike CRMs which only provide the original source of the lead, revenue attribution tracks previous interactions and helps understand the conversion process. it allows businesses to foster alignment between sales and marketing teams. This qualitative approach helps marketers improve lead quality and understand customer intent, resulting in better targeting.

Facilitating better forecasting and planning

Revenue attribution helps businesses with forecasting by understanding the decision-making process of buyers. Maybe the efforts you put in today will yield results in 6 months. It also allows for the evaluation of the effectiveness of revenue-generating activities and provides benchmarks for results, enabling more accurate forecasting and strategic planning.

Identifying high-value customers

Revenue attribution enables businesses to identify segments that contribute the most revenue. By understanding the specific characteristics and behaviors of high-value customers within each segment, businesses can tailor their marketing and sales efforts to attract and retain similar customers, leading to increased revenue.

Getting Started with Revenue Attribution

No matter what attribution model you choose to follow, or the goals you set out to achieve, data plays a vital role in successful revenue attribution. So the first order of business for revenue attribution is to collect and consolidate all historical data. Whether it is a sale registered in a CRM or the number of customers reading your newsletter. 

But with so many channels and teams involved, doing so can mean getting buried in a pile of datasheets and reports.

A robust revenue attribution tool will help you unify data across multiple channels, set-up relevant, custom conversion goals, and breakdown the analysis with granular filters and segmentations. 

Factors.ai is a revenue attribution tool that helps monitor and optimize GTM performance across campaigns, content, and events. 

With Factors.ai, businesses can choose and compare various attribution models tailored to their unique buyer journeys, ensuring effective resource allocation and reducing marketing leakage.

It is best suited for companies that want a deeper understanding of their customer journey and revenue pipeline

Revenue attribution is the link between data, analytics and your organizational goals. Create a roadmap to sustainable growth and higher revenue with our new revenue attribution tool. Click here to get started! 

Maximize ROI with Revenue Attribution

Revenue attribution assigns value to marketing touchpoints, helping businesses understand their impact on conversions and revenue.1. What is revenue attribution and why it matters: Enables data-driven decisions and optimized marketing budgets.

2. Key Insights: Identifies high-performing channels to enhance profitability.

3. Attribution Models:
- Single-Touch Models: Ideal for B2C with short sales cycles.
- Multi-Touch Models: Suited for B2B with complex, long sales cycles.

By selecting the right attribution model, businesses can refine strategies, improve performance, and drive sustainable growth.

FAQ: 

What is an example of revenue attribution?

During a B2B purchase cycle, a customer interacts with various channels such as customer service representatives, marketing campaigns, and salespersons. Revenue attribution is the process of allocating monetary value to each of these events.

Why is revenue attribution important?

Revenue attribution is crucial for businesses to help understand the effectiveness of marketing, sales, and customer support efforts in driving revenue. It helps optimize spends, identify effective strategies and refine budget allocation for each function. 

How do you calculate attributed revenue?

Attributed revenue is calculated by assigning credit to different touchpoints based on their contribution to a sale, using single-touch or multi-touch attribution models such as the w-shaped model or linear attribution model.

If you’re part of a sales team, chances are you’ve considered paying for LinkedIn Sales Navigator at some point. LinkedIn Sales Navigator seemingly ticks all the boxes– whether it's accurate data, intuitive, time-saving prospecting, or effortless sales outreach". But do its features justify its steep pricing? 

In this blog, we take a close look at LinkedIn Sales Navigator, its pricing, features, benefits, and limitations to see if you should invest in the platform.

What is Linkedin Sales Navigator?

LinkedIn Sales Navigator is a valuable tool for sales professionals and businesses, It facilitates lead generation and relationship management on LinkedIn. 

With Sales Navigator’s features, users can efficiently target promising prospects and stay informed about their activities and organizational changes. As compared to the basic/free plan, sales navigator is far more robust. It provides additional data that helps optimize sales strategies as and when the opportunity presents itself:

LinkedIn Sales Navigator Features:

1. Personalized lead recommendations: Sales Navigator offers tailored lead suggestions based on criteria like industry, company size, and job title preferences.

2. Advanced search functionality: Conduct detailed searches using filters such as location, job title, and company size to pinpoint prospects matching your ideal customer profile.

3. Account and lead insights: It provides valuable insights into prospects, including recent LinkedIn activity, company news, and job changes, aiding in better understanding and engagement.

4. InMail messaging: It helps you reach out to prospects via InMail, even without prior LinkedIn connections, expanding your outreach capabilities.

5. Sales Navigator Pages: Utilize customizable pages to track, save, and receive real-time insights on leads and accounts, optimizing your sales strategies.

You’re probably thinking “But this sounds suspiciously similar to LinkedIn Premium”. Well, you’re not entirely wrong. While they do aim to provide similar benefits such as access to InMail etc, they do have some differences:

What is the difference between LinkedIn Premium and LinkedIn Sales Navigator?

LinkedIn Premium is a whole lot cheaper and seemingly offers similar benefits. Considering you can get LinkedIn Premium at 1/3rd the price, LinkedIn Sales Navigator cost sure seems a bit much. But when it comes to prospecting and outreach in particular, Sales Navigator has so much more to offer. 

LinkedIn Premium is designed for a broader audience, including job seekers and recruiters, and offers features such as increased InMail credits, the ability to see who viewed your profile, and access to valuable training courses. 

On the other hand, LinkedIn Sales Navigator is designed specifically for salespeople. Accordingly, it offers advanced search filters, lead recommendations, and granular analytics. So, while LinkedIn Premium may be a good choice for job seekers and recruiters, LinkedIn Sales Navigator is certainly the better choice for salespeople.

Let's pit these two against each other:

Why choose LinkedIn Sales Navigator? 

Given its reputation and popularity, LinkedIn has to be one of the best social selling tools for B2B businesses. 134.5 million people use LinkedIn daily. It's the first place you go to when you want to post a career update, look for new teammates, or simply post company news. Social selling is a great way to supplement traditional channels. Social selling cannot replace these channels. 

The community and trust are certainly the primary appeal of the platform. Here are some other benefits of using LinkedIn Sales Navigator:

Advanced Filters

LinkedIn Sales Navigator has more than 40 advanced search filters. You can filter your search based on company, role, workflow, and keywords. What's unique about this feature is its spotlight filter option. Here are some of them: 

1. The Job Changes spotlight identifies prospects who have changed jobs within the last three months.

2. The Shared Experiences spotlight uncovers prospects who attended the same schools, worked at the same companies, or belong to the same LinkedIn Groups as you.

3. The LinkedIn Activity spotlight shows prospects who have posted or shared content on LinkedIn in the past 30 days.

4. The Mentioned in the News spotlight uncovers prospects who have been mentioned in the news in the past 30 days.

5. The Leads that Follow Your Company spotlight uncovers prospects who follow your company on LinkedIn.

6. The TeamLink spotlight finds prospects who are already connected to your colleagues. (not available on all plans)

This feature establishes Sales Navigator as a great “social” selling tool, taking searches a step further and helping sales teams establish connections with leads. 

Recommended Leads  

LinkedIn recommends leads on Sales Navigator through three methods: on specific company pages, at the top of a lead's profile, and via a recommended leads list.

The Recommend Leads list in Sales Navigator offers an auto-generated list of up to 100 recommended leads based on past user activity, such as searches and saved leads. 

Note: This feature relies on AI and functions optimally with increased data input. Therefore, you need to save relevant leads to your lists manually. The more interactions and saved profiles, the more refined your recommended section becomes on Sales Navigator.

Intent Identification and Alerts

LinkedIn Sales Navigator helps sales teams identify buyer intent by monitoring their company interactions– if the prospect has connected with you or your team or if they’ve engaged with your LinkedIn Ads. It sends real-time alerts for each of these activities and helps you make the most of an opportunity. 

Note: you need to manually save prospects in a list to ensure you get alerts for activities on their account.

Smart Links

One of the best features of Sales Navigator is the smart link. It allows you to simply create their deck online using this feature on LinkedIn Sales Navigator or even upload an existing PPT. A smart link is shareable and trackable for opens and clicks so you won’t need to switch to your CRM or another software for analytics. 

This brings us to the final benefit of the tool: 

Performance Analytics

Sales navigator allows you to track user groups and performance trends– you can analyze usage patterns to pinpoint areas of improvement, such as low InMail acceptance rates. Your training programs can be tailored to address these gaps and enhance sales team proficiency.

LinkedIn Sales Navigator Cost

LinkedIn Sales Navigator has a tiered pricing structure. It has three plans: Core, Advanced, and Advance Plus. At the time of writing, the prices for each plan are as follows:

Here are the additional features you get with each of the pricing plans:

Limitations of LinkedIn Sales Navigator

While there are numerous benefits of using Sales Navigator, users have reported some issues with the following:

1. Steep Learning Curve

Some users may find Sales Navigator to have a steep learning curve, especially if they are new to LinkedIn or CRM tools. It may require significant time and effort to fully grasp and utilize all the platform's features effectively, and the complex user interface needs to do more to help. It potentially delays the realization of its benefits apart from taking a lot of resources to set up.

2. Limited InMail Credits

While Sales Navigator provides InMail credits, users are allocated a limited number of Inmail credits each month. 

Once you exhaust these credits you need to purchase additional ones or upgrade your plan, adding to the overall cost of using the platform and potentially constraining outreach efforts.

3. Data Inaccuracy

LinkedIn's data, including contact information and job titles, is user-generated, leading to potential inaccuracies or outdated information in profiles. This can undermine the effectiveness of outreach campaigns and result in wasted time and resources.

4. Integration Challenges

Despite offering integration with popular CRM systems like Salesforce and Hubspot, some users encounter difficulties in setting up and maintaining these integrations. Sales Navigator's inability to expert lead or account lists is another challenge for users. These challenges can disrupt workflow efficiency and hinder seamless data management between platforms.

LinkedIn Sales Navigator Cost: Final Verdict

LinkedIn Sales Navigator is a premium service, which can be expensive for individual users or small businesses. This cost may pose a barrier to entry for some potential users, impacting adoption rates and accessibility.

When it comes to social selling, LinkedIn has a unique proposition that can’t be matched by other tools. It is an extension of a professional networking platform and provides insights on “shared experiences” and “commonalities” allowing you to build a rapport with your leads. So if you already have a prospecting or sales intelligence tool and you’re looking to add a social selling tool to your tech stack- we highly recommend LinkedIn Sales Navigator. 

Having said that, LinkedIn Sales Navigator leaves you wanting more in terms of data accuracy and lead generation. Anecdotal evidence suggests it's clunky and has surface-level integrations with CRMs. So if you’re building your sales tech from scratch, we recommend you steer clear of LinkedIn Sales Navigator. Here are some tools we recommend instead- 

1. Factors.ai 

Factors.ai is a tool that facilitates account-based selling. It not only delivers industry-leading enrichment rates of up to 64% but also helps qualify and target the right accounts based on intent data. Factors.ai takes into account website engagement, intent signals, and firmographic information to qualify leads and expedite the sales process. 

In comparison, LinkedIn provides a detailed however limiting view of the customer journey, due to its primary focus on LinkedIn activity. Most of the decisions are made based on interactions with the product’s website, its social channels, G2 reviews, etc. Factors.ai (due to its partnership with Clearbit) provides an extensive database and accurate intent identification as well. 

If you want more than a primary database and prospecting solution, Factors.ai is a great tool that provides analytical insights that help you identify target and close leads. 

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2. Cognism 

Cognism serves as a sales intelligence solution and data provider, offering cell phone numbers, direct dials, and emails across multiple regions. Its browser extension operates seamlessly across various corporate websites, including LinkedIn.

In contrast,  LinkedIn Sales Navigator is effective for targeting prospects active on the LinkedIn platform, aiding in the identification and connection with decision-makers within an Ideal Customer Profile (ICP). It provides access to public emails and phone numbers of these prospects.

Moreover, Cognism boasts phone-verified mobile numbers, ensuring an 87% connection rate with listed contacts. This surpasses LinkedIn's reliance on user-provided data, which, as indicated by Sales Navigator reviews, may lead to data inaccuracies and user frustration.

If you are looking for a global database and want to reach out to decision-makers through the same solution, Cognism is a great choice for you.

3. Zoominfo

Zoominfo is a leading B2B data provider and is a suitable alternative to Sales Navigator- 

LinkedIn Sales Navigator is specialized for targeting known prospects, while ZoomInfo excels at identifying decision-makers within targeted accounts. Sales Navigator emphasizes specific personal details, sourced from user updates, whereas ZoomInfo offers more up-to-date macro-level data, collected from web scraping.

Sales Navigator enhances contact targeting with network tools and professional news updates, while ZoomInfo facilitates bulk contact list exports and offers additional tools like ZoomInfo Engage, Chorus, and Chat for comprehensive sales support. If you are looking for a tool that puts equal emphasis on collaboration along with sales prospecting and lead generation- Zoominfo is the way to go. Competitors like Factors.ai are more powerful account intelligence solutions that can make your lead generation cycle seamless. Know more about Factors.ai here.

Is LinkedIn Sales Navigator Worth the Investment for Lead Generation?

LinkedIn Sales Navigator offers advanced search filters, lead recommendations, and in-depth analytics to enhance social selling.

Key features include:

1. Spotlight Filters & Smart Links: Identify high-intent prospects and personalize outreach.

2. Advanced Search & Lead Lists: Segment and track ideal buyers efficiently.

3. Intent Data & Insights: Prioritize leads based on engagement signals.

However, challenges like a steep learning curve, data inaccuracies, and integration issues may impact usability. While Sales Navigator is a powerful tool, its high cost might not suit every business. For greater data accuracy and expanded lead generation, alternatives like Factors offer competitive solutions.

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.

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

We get it. 

The B2B sales cycle looks more like a roller coaster than a funnel. 

With numerous touchpoints, interactions, and channels involved, your potential buyers are getting lost in a sea of data and numbers. 

And your team? 

Is just as confused as you are… 

Without a clear understanding of what buying signals to look out for, your sales and marketing teams are probably losing out on the opportunity to close deals faster-

With the right approach, you can bring the customer acquisition costs down and eventually increase the bottom-line revenue. 

So what are buying signals?

Buying signals are actions and behaviors that demonstrate a prospect’s purchase intent.  Buying signals play a crucial role in both sales and marketing endeavors. It helps identify customer needs and streamline the buying process, allowing your team to expedite the sales cycle. Analyzing buying signals also helps determine the most effective messaging and marketing campaigns, helping optimize your campaigns.

Types of Buying Signals

Buying signals can be classified as verbal and non-verbal cues. Your sales teams should be trained to consciously look out for these signals during interactions with prospects:

1. Verbal Cues

Here are some verbal cues to keep a lookout for- 

• Open communication - prospects freely express their needs and challenges, indicating a willingness to engage and explore solutions.
• Repeating or complimenting features - When prospects emphasize or praise specific features, it signals interest and a potential alignment with their requirements.
• Meaningful questions during sales engagement - Asking insightful questions during a product demonstration suggests an active interest in understanding the solution's applicability.
• Picturing themselves using the tool - When prospects inquire about specific use cases or imagine scenarios involving your product, it indicates a practical consideration of its utility.
• Enquiring about pricing plans - Explicit inquiries about pricing or discussions around budget indicate a transition from interest to serious consideration.
• Risk Minimization Questions - While objections may seem negative, questions about overcoming challenges or minimizing risks indicate a prospect's genuine interest in finding a suitable solution.

2. Non-Verbal Cues

These non-verbal cues are often overlooked during sales interactions

• Nodding Head: Positive body language such as nodding signifies agreement and interest, reflecting a favorable disposition toward the product.
• Smiles and eye contact: Non-verbal cues like eye contact and smiling suggest engagement and comfort, indicating a positive reception to the sales pitch.
• Leaning Forward: Physically leaning into the conversation demonstrates active involvement, signaling a heightened level of interest in the presented information.

These signals can help close a deal once you have the opportunity to interact with your potential customers face-to-face. However, as a recent Gartner study suggests, 80% of B2B sales interactions will happen through online channels by 2025. This suggests that marketing teams should also keep an eye out for buying signals to streamline their process and make sense of each customer interaction. 

Here’s how marketers can make sense of data to identify buying signals throughout the B2B sales cycle:

3. Fit Data

Fit data encompasses firmographic and demographic information utilized to assess whether a prospect aligns with the characteristics of an ideal customer. This type of data serves as a potential indicator during the buying process, helping determine if a customer is well-suited for a company's products or services.

For instance, consider a company specializing in providing IT services to small businesses. Fit data elements such as company size and industry become crucial signals, suggesting a strong alignment with potential customers. Similarly, in the context of a company offering high-end luxury products, fit data, including income levels, proves valuable in identifying individuals likely to have both interest in and financial capacity for the products.

It is essential to note that being a fit alone does not guarantee a customer's inclination to make a purchase. Therefore, integrating fit data with intent data becomes imperative to enhance the precision of marketing and sales strategies.

4. Opportunity Data

Opportunity data, on the other hand, pertains to information indicating a potential customer's likelihood to make a purchase based on specific events or circumstances. In the realm of B2B companies, this could encompass favorable situations within an organization that create optimal conditions for a successful sale.

For example, if a prospective company recently experienced a successful funding round, it may signal an expanded budget. This, in turn, suggests a higher likelihood of them being receptive to new business opportunities and facing fewer budgetary constraints. Again, opportunity data in itself does not indicate a willingness to buy and therefore should be viewed in conjunction with intent data.

5. Intent Data 

Intent data focuses more on buying actions when your potential buyers are moving through the stages of the customer journey. Imagine a prospect navigating through your content, attending webinars, and signaling interest through various touchpoints. The power lies not just in identifying these signals but in understanding their nuances, their cadence, and their context within the larger buying journey. Intent data can either be behavioral or contextual: 

6. Behavioral Data

Behavioral data refers to the way potential customers engage with your business. Say you’re running a travel agency. A website visitor interacts with a blog titled “10 places to visit in Europe” and then looks into the pricing of your Europe tour packages. This indicates intent and reaching out to the prospect with exciting discounts and offers on their preferred destination will certainly help them purchase from you. This is some behavioral data you should take into consideration: 

• Website activity and visits to specific pages
• Signups and activity for free products and trial accounts
• Content downloads
• Webinar signups and attendance
• Blog post and case study views
• Email engagement
• Ad engagement

7. Contextual Data

Contextual Data gives insights on who your website visitors are and how they are interacting with your website in the awareness stages:

• Referral sources (understanding what led them to visit your website)
• Marketing campaign source
• If they are a new or returning visitor
• Keyword searches and intent

Understanding these queues helps streamline marketing functions. The ability to streamline processes is tantamount to progress in B2B. By aligning buying signals with the stages of the buying cycle, you can create repeatable and optimized processes. This not only eliminates noise but also offers insights into what works and what doesn't. The result? Time saved, resources optimized, and a clear pathway to building meaningful, personalized connections with your prospects.

The synergy of intent data and behavioral data is only possible within the ABM framework. Introducing Account-Based Marketing (ABM) is not merely a strategic approach but a transformative solution for B2B businesses, especially when empowered by the right automation software. Imagine having the ability to seamlessly track customer journeys across various touchpoints, discerning key buying signals in interactions over all channels. A robust ABM tool like factors.ai not only identifies these signals but also helps act on them at the earliest.

That's another reason to employ automation to identify buying signals. Studies suggest that businesses that respond to leads in five minutes or less are 100x more likely to convert opportunities. Using automation tools, teams can reach out to prospects instantly, and capitalize on every opportunity that presents itself through digital interactions.

Automating this process enables marketers to personalize communication and expedite the buying process.

How Factors.ai helps identify intent-based buying signals:

Factors.ai has several beneficial features that help identify customer intent using behavioral and contextual data: 

With powerful marketing attribution, you can identify the referral sources with the highest ROI. it allows you to optimize your marketing efforts and spend to optimize all efforts aimed at increasing awareness. 

As far as behavioral data is concerned, Factors.ai allows you to identify website users and track their movement and interactions- right from the first touch to the last. With account intelligence and features that provide a clear overview of the customer journey, it is easy to understand how potential customers move through the funnel and employ the appropriate sales and marketing tactics to close the deal.

And that’s not all!

Factors allows you to employ filters based on demographic, firmographic as well as behavioral data to customize marketing campaigns and even personalize communications. This helps sales and marketing teams make sense of their data and act on buying signals with great ease!

Your teams can save time and effort while driving in more conversions!

Cognism is a popular B2B sales intelligence platform that helps users discover and engage with their ideal prospects with premium company and contact information. But with numerous alternatives available to users, how does Cognism fare in terms of its data quality, pricing, and features?

In this blog, we’ll explore Cognism, Cognism pricing, and Cognism’s alternatives in detail

What is Cognism?

Cognism is a sales intelligence platform that provides advanced data enrichment, lead generation, and prospecting features to help businesses improve GTM operations. Here’s how Cognism impacts each of these verticals: 

Cognism enables direct dialing of verified contacts, streamlines the process of prospecting for new leads, and provides access to company-specific data, enhancing lead generation and qualification efforts.

For marketing teams, leveraging the platform facilitates the targeting of new accounts with contextual data points that make it easy to build account lists. It also equips marketing teams with intent data for a more targeted approach.

Furthermore, Cognism serves as a valuable tool for GTM leaders in devising strategic initiatives to drive company growth. It aids in identifying buyer intent, matching and populating missing lead values in your database, and setting a more accurate lead scoring system. 

Here are all of Cognism’s product offerings that help achieve these results: 

Prospector: Cognism combines contextual data with intent data helping you truly understand your buyer to get your relevant message right in front of buyers.

Enhance: Cognism prevents data decay and helps append your database with updated company and contact information so you don’t lose out on revenue.

Intent Data: Cognism Intent Data helps you identify accounts actively searching for your product or service, making the sales cycle shorter and helping reduce CAC. 

Cognism’s product offerings and features serve different purposes for different operations, but what about its impact on your growth and revenue?

Why Choose Cognism?

Cognism has great benefits for businesses looking to streamline their sales prospecting and create laser-focus outreach campaigns that shorten the sales cycle and drive revenue and growth:

1. Compliance and Security

Security forms the core of Cognism's service provision. The platform maintains rigorous compliance with GDPR, SOC2, and ISO27001 standards, guaranteeing the protection and responsible handling of your business data in line with globally recognized benchmarks. Cognism's dedication to safeguarding Personally Identifiable Information (PII) underscores its commitment to ensuring robust security measures.

2. Integrations

Cognism's integration library may not be as extensive as some competitors, but it still offers a solid selection of compatible apps. This is understandable considering Cognism's smaller user base. Despite its smaller customer pool, Cognism provides integration options with popular platforms such as HubSpot, Salesforce, Pipedrive, Microsoft Dynamics, Outreach, Zapier, Wufoo, Salesloft, Vidyard, G Suite, Yahoo, Office365, Gmail, Insightly, Slack, Zoho CRM, Copper, and Close.

3. Chrome Extension 

The Cognism browser extension gives you quick access to company employees and your prospects' coworkers. It not only enhances LinkedIn profiles and Sales Nav prospect lists with actionable contact data but allows you to access company website information on target firms and their employees. 

The Cognism Chrome extension integrates seamlessly with Outreach and Salesforce to enrich records within your CRM or Sales Engagement tool- making it easier for sales teams to perform tasks without switching back and forth between multiple tabs or windows.

Cognism Pricing

Although Cognism refrains from providing detailed pricing information on its website, the factors influencing pricing can aid prospective clients in understanding the associated costs. Here are the three factors that help determine the pricing for Cognism’s clientele:

1. Core Platform Fee

Central to Cognism's pricing model is a fixed platform fee, granting users access to its web application and Chrome extension. Moreover, Cognism seamlessly integrates with popular sales tools like Salesforce and HubSpot. This fee ensures users can harness the platform's robust functionalities and integrations to optimize their sales and marketing endeavors.

2. Unrestricted Data Access

Cognism's platform offers an extensive repository of data to assist businesses in identifying and engaging potential leads. Under the pricing structure, users benefit from unrestricted access to this data, including the ability to export information for utilization in other applications or tools. This access empowers users to fully leverage the platform's potent data capabilities for lead identification and targeted marketing initiatives.

3. Adaptable Workflows

One of the main reasons why Cognism's pricing structure is tailor-made is because of its custom workflows. This feature enables users to customize the platform to suit their specific requirements, crafting workflows that enhance lead qualification and streamline the sales process, and are charged accordingly.

These factors determine the final cost in their pay-as-you-go subscription model. However, the ambiguity may be a cause of concern for businesses of all sizes. Apart from this, Cognism does not provide a free trial. Uncertainty with Cognism pricing? Here are a few alternatives for your consideration:

Cognism Alternatives 

Here are some of the most popular Cognism alternatives for B2B businesses: 

1. ZoomInfo 

ZoomInfo offers a robust platform beyond traditional B2B contact directories, catering specifically to sales, marketing, and recruitment professionals. In addition to its expansive database of detailed profiles, ZoomInfo provides unique features such as intent signals, which indicate companies actively exploring specific topics. Another one of its notable features is Scoops, offering valuable insights into potential business opportunities. For those seeking to optimize their outreach strategies, ZoomInfo is a standout choice.

Why pick Zoominfo over Cognism: While Zoominfo and Cognism pricing arent transparent and can prove to be costly for smaller teams, features like Scoop and advanced analytics are bonus features that make Zoominfo a better choice for teams looking for added capabilities in their sales intelligence software. 

2. Clearbit 

Clearbit stands out by seamlessly integrating data into existing workflows rather than focusing solely on data provision. Engineered to seamlessly merge with sales and marketing tools, Clearbit delivers real-time insights about prospects.

 Notably, its Enrichment feature transforms basic email addresses or domains into comprehensive person or company profiles. Moreover, Clearbit's Reveal function assists in identifying anonymous website visitors, effectively converting them into actionable leads.

Why pick Clearbit over Cognism: Cognism has an extensive and unparalleled database for the European market, but it cannot compete with the accuracy of Clearbit’s global database. For companies that are targeting US-based clients, Clearbit is the better choice between the two.

3. Lusha

Lusha, a Sales Intelligence Software, empowers business professionals in building trustworthy connections with leads, contacts, and candidates. With streamlined tools, it facilitates the enrichment and verification of business profiles, aiding sales, recruitment, and marketing efforts. 

Lusha simplifies the process by retrieving emails and phone numbers with just one click, enhancing business profiles across social networks, Gmail, and Salesforce. Its clientele spans from small and medium businesses to industry giants like Google, Amazon, Salesforce, and Apple.

Why pick Lusha over Cognism: 

Lusha claims to update its database weekly and provides proactive job change alerts to keep the sales team well-informed. Cognism falls short in this aspect as users report receiving outdated information on the platform.

4. Factors.ai

Factors is an account intelligence tool with robust partnerships with 6sense and Clearbit. This is reflected in our database of over 50M companies & 4.7B IP addresses. Factors delivers industry-leading enrichment rates of up to 64% and helps qualify and target the right accounts based on website engagement, intent signals, and firmographic information. 

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Cognism FAQs

What is Cognism and what is it used for?

Cognism is a B2B sales intelligence software that helps sales and marketing teams to build lead lists and supercharge their outbound efforts. 

How does Cognism collect data?

Cognism has created its database for email generation apart from relying on third-party vendors for data collection.