Why SaaS cohort analysis is essential for your SaaS

The notion of the customer cohort is well known in marketing. But it’s also a key concept to integrate into the management of a SaaS company.

In this article, we’ll look at what a cohort analysis is, why it’s important, and how to set it up in your startup.

1 - What is a SaaS cohort analysis?

Cohorts are not just a popular concept in marketing. They are also a powerful tool for studying SaaS performance. A cohort is a group of customers or users who share at least one common characteristic.Bringing them together in a cohort makes it easier to analyze the behavior and retention of customers or users over time.

1.1 - Cohort and marketing: definition

Marketing relies heavily on data analysis. To study the behavior and value of customers who have something in common, the cohort is an excellent tool.

For example, with Google Analytics, it’s possible to analyze all visitors to an e-commerce website who arrive via a Google Ads campaign during a given week. The aim is then to track the behavior of this group over the coming weeks and learn from it.

This approach of analyzing groups of customers with common characteristics is very useful for steering the growth of a SaaS company.

1.2 - Customer cohort and SaaS management: definition

SaaS financial management also relies on cohort analysis. Grouping customers enables us to draw lessons for business and economic performance. The various SaaS cohorts provide valuable information on customer lifecycle and retention issues.

1.3 - How do you create a cohort?

The company can create as many cohorts as there are time periods or customer characteristics. A single cohort, for example, corresponds to the group of SaaS users who entered the customer base in a given month. Monthly cohorts are the most widely used to analyze SaaS performance and subscriber behavior. They provide a number of insights into the behavior of each group:

• how often subscribers upgrade to additional services;
• subscription renewal rate;
• contract cancellation rate;
• average subscription amounts, etc.

Building a cohort can also mean creating finer segments. Here, we’re talking about cohorts of customers acquired by period AND by price plan. It is also possible to create cohorts by customer type.

If you plan to offer one or more free months for one of your services, creating a cohort can help:

• analyze the transformation rate (trial to paid);
• and measure monthly churn to detect high-risk months.

2 - Why analyze a cohort of SaaS customers?

Every SaaS has precise KPIs for its revenues (ARR and MRR), churn rate (attrition rate), CAC (customer acquisition cost), and LTV (lifetime value: total revenue expected per customer). But you must be able to study them in detail! This is the role of cohort analysis.

2.1 - A detailed analysis of past growth of the SaaS business

Recovering data for a cohort and examining it over months provides a better understanding of the customer base. Analyses of various cohorts show how layers of the business stack up over time. This detailed study of sales history and growth is difficult to obtain by any other method.

Cohort analysis also makes it possible to:

• Study the effectiveness of acquisition, by measuring new customer acquisition on a month-by-month basis (monthly cohorts).
• Evaluate the ability to upsell to existing customers based on customer type or seniority (monthly cohort).

2.2 - Identifying churn data and loyalty actions

Cohort analysis is an excellent way of studying attrition rates (customers leaving SaaS). Within each defined user group, it becomes possible to identify the moments when churn is highest, for example during the third month after subscription (case of a monthly cohort). Then you can investigate why churn peaks at this time and implement corrective measures to boost loyalty and retention.

You can take this a step further by creating monthly cohorts by customer type. This provides a very detailed understanding of customer behavior over time according to their specific characteristics.

2.3 - Help with calculating lifetime value (LTV) and MRR forecasts

1.   Cohort analysis and LTV

Cohort analysis is not an aid to LTV calculation as such. But it does enable us to calculate a more detailed LTV by cohort.

Cohorts by customer type are useful for identifying users with a higher or lower LTV (due to higher ARPU and/or lower churn) and therefore to focus acquisition efforts on them.

2.   Cohort analysis and MRR forecasting

By analyzing the behavior of existing cohorts, we can make very precise assumptions about how they will evolve over the coming months:

• Analyze churn by monthly cohorts to apply the churn rates of older cohorts to new cohorts;
• and analyze behavior over time by customer type enables us to segment the customer base and so make assumptions about future trends.

3 - How to conduct a SaaS cohort analysis?

Cohorts therefore allow in-depth investigation of billing data to customer data to SaaS product usage data.

The complexity of the tasks involved can be daunting for CEOs, CFOs, and their teams. Fortunately, there are tools that can automate the calculation of cohorts.

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3.1 - Analysis of segmented cohorts: useful, but complex

Cohort analysis is an essential tool for tracking the evolution of your income in detail. It is, however, complex to implement since it requires a great deal of data processing.

This process requires that you:

• compile accurate data from your billing software;
• segment customers or subscriptions according to the specific features of your SaaS;
• aggregate data according to selected cohorts;
• monitor data trends over time.

Cohort segmentation brings relevance and granularity, but also complexity.

💡 For example, a customer account can be enhanced by classifying customers by family, such as “private individual,” “sole proprietorship,” “VSE,” “startup,” etc.

But you can also further segment your data for added granularity: for example by acquisition channel, by product, etc.

These segmentations can therefore pile up. Your job is to ensure that this complexity doesn’t come at the expense of your ability to draw relevant analyses from your data.

3.2 - Cohort analysis in Excel or Google Sheets: forget it!

Creating and analyzing multiple, segmented cohorts with a simple spreadsheet program is not an option:

• First, it’s complicated to implement, given the number of possible segmentations;
• Second, crossing information sources over time makes the job even more difficult.

And let’s not forget the risk of errors and the fact that spreadsheets require manual data updating.

In addition, the creation of a summarized cohort table requires numerous time-consuming preliminary steps. Cohort analysis using Excel or Google Sheets is likely to discourage even the most enthusiastic.

3.3 - An automated cohort analysis tool: Fincome

Fincome helps SaaS companies manage their finances. With our reporting and cohort analysis tools, SaaS managers can closely and seamlessly manage their business. They can concentrate on studying KPIs and automatically calculated data.

Thanks to our automatically formatted reports and tables, managers have reliable information to help them make the right decisions.

Cohort analysis is a powerful tool for SaaS. Request a demo and see for yourself how SaaS cohort analysis benefits your startup.

💡 Complete your reading with the following articles:

• How is a SaaS company valued?
• 3 common mistakes that kill SaaS startups
• Why SaaS reporting is a must (plus the best KPIs)
• Top tips for communicating with SaaS investors
• Automated reporting for SaaS: a quick guide
• KPI reporting at every stage of your startup
• Investing in management tools: why is it a great idea?
• Why is SaaS financial reporting still crucial for your startup in 2023?