Managing advanced cohort analysis in Salesforce

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1. What is cohort analysis ?

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Cohort analysis is a method of studying user behaviorby grouping individuals with common characteristics and examining theiractivity patterns. This approach helps in tracking and understanding how usersinteract over time based on shared attributes. A cohort refers to any set ofpeople who share specific traits or experiences.

For example, a company may track a cohort of customersacquired in Q1 through a paid advertising campaign and compare their revenueperformance to customers acquired via organic search in Q2. This approach helpsbusinesses identify which acquisition channels are driving the most long-termvalue.

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2. Why cohorts analysis is key for companies

Cohort revenue analysis is mainly used by marketingand finance teams

• Marketing teams use it to identify how effective are their campaigns, content strategies, and lead generation channels. By understanding which cohorts are the most profitable, they can evaluate how to allocate budget to optimize their ROI
• Finance teams use cohort analysis to predict revenue, calculate payback periods, and estimate customer acquisition costs (CAC) versus lifetime value (LTV). It helps them to make budget decisions and justifying expenditures based on actual revenue contributions rather than vanity metrics like clicks or impressions.

Let’s put that into an example.
Pied Piper Inc needs to reach 26K Monthly Recurring Revenue in Q2.

They are willing to spend additional 10K in marketingin Q2 but wants to ensure that those 10K will be spent on channels andcampaigns which can generate revenue in less than 3 months.

When looking at their revenue attribution report theysee that Linkedin Ads is the most performing channels so they are thinkingabout investing all marketing budget on it.

However, after carefully looking at revenue and costattribution data, they realize that Linkedin Ads, despite being the topperforming channel in terms of closing rate is also the channel leading to thehighest acquisition costs and longest sales cycle (6 months).

Therefore they will not be able to reach their Q2target if only relying on performance data and will consider other channelswhich could represent a fast track to revenue.

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3.Why Cohort Analysis is Challenging for B2B Brands

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While cohort revenue analysis is relatively easy to monitor for eCommerce companies, it can become a real challenge for B2B brands due to siloed data spread across multiple platforms:

• Website data stored in analytics tools (e.g., GA4)

• Advertising data housed in ad platforms (Google Ads, LinkedIn Ads, etc.)

• Conversion data recorded in Salesforce

With such dispersed data sources, marketing, revenue operations, and finance teams struggle to collaborate efficiently. The process often requires manual data consolidation, leading to partial data at best or inaccurate/nonexistent data at worst.

A Common Pitfall in B2B Cohort Analysis

Many companies rely on "Lead Creation Date" in Salesforce to conduct cohort analysis, comparing it with the date when a lead converts into a closed-won opportunity. However, this approach is highly misleading for several reasons:

• The Lead Creation Date doesn’t reflect the first time a prospect engaged with your brand.

• It can be inaccurate if leads aren’t immediately pushed to Salesforce but are first nurtured in third-party tools (e.g., HubSpot) until they reach a specific score.

Example: The Hidden Time Lag in B2B Sales

Let’s illustrate how this issue can impact budget allocation decisions.

• On January 1st, John Doe clicks on a LinkedIn Ad.

• Over the next few months, John conducts research, compares solutions, and occasionally revisits your website when you post updates.

• Internally, John is waiting for budget approval before making a purchase.

• On May 12th, he finally fills out a form on your website to book a sales call.

• Thanks to his prior research, the sales cycle is short, and John converts into a closed-won opportunity on June 12th.

Now, here’s the issue:

If you rely solely on Lead Creation Date (May 12th), it appears that John converted in just 31 days. However, in reality, the entire journey from the first ad click to revenue took 162 days (over five months).

The Risk of Misguided Budget Decisions

Going back to our earlier budget allocation scenario:

If you had based your Q2 investment purely on Lead Creation Date, you might have wrongly assumed LinkedIn Ads was driving fast revenue and gone "all in" on that channel only to later realize the actual conversion timeline was much longer.

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4. How to Run a Successful Cohort Analysis

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As explained above, the key to running a successful cohort revenue analysis is ensuring that all your data is centralized in one place from paid ad platform data to revenue data, including website visits and content engagement.

Why Centralize All This Data?

• Paid ad data allows you to compare cohort revenue with accurate acquisition costs.

• Revenue data is essential for calculating cohort revenue.

• Website visit data helps compare the revenue generation date with the first engagement date of a prospect on your website.

• Content engagement data enables more granular cohort analysis, helping you understand how different personas and content interactions impact conversions.

Where Should You Centralize This Data?

The ideal solution is Salesforce and here’s why:

Keeping your data secure is critical. You cannot rely on third-party solutions that:

1. Store prospect data using cookies or fingerprinting, which can be unreliable or restricted by privacy regulations.

2. Require access to your Salesforce data (including personal data of leads and contacts) to match records posing a security and compliance risk.

This is why you need a solution that ensures no external hosting and zero third-party access to your Salesforce data.

How Heeet Solves This Problem

Heeet provides a unified view of all the key metrics allowing marketing, revenue operations, and finance teams to collaborate using shared insights. It offers a clear cohort analysis view natively within Salesforce, integrating website data, revenue data, acquisition costs, and content tracking in one place.

Below is an example of a cohort analysis report based on First Website Visit and Revenue Close Date, showing the average number of days required to generate revenue per channel.

Here is a cohort analysis at the campaign level, displaying the same metrics

And here is the same analysis based on keyword search, you can see on this example the average number of days required from first visit to revenue per keywords.

With all these metrics centralized in Heeet, you can now visualize all key information about the fastest channels, campaigns, and keywords leading to revenue in a single Cohort dashboard in Salesforce.

You want to see how Heeet can help marketing, revenue operations and finance to collaborate more closely to generate revenue faster using cohort analysis? Feel free to book a demo by clicking here.

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