Investors love SaaS customer cohort analysis. It shows that you are analyzing your business, using data to identify areas of strength and weakness. It shows that you know your customers and can analyze which segments are likely to grow and which are at risk for churn.
If you can identify the groups most likely to churn, you can do something about it and improve your performance. If you know the groups most likely to grow, you can better allocate resources to find more of them and drive more sales and revenue growth.
What is SaaS Customer Cohort Analysis?
SaaS customer cohort analysis looks at a set of data and breaks it into groups by some set of common characteristics. In the SaaS world, cohort analysis is often done by time period, ie., comparing how the customers acquired in a certain month or year are performing versus the customers acquired in different months or years.
A time-based analysis is fine and can tell you overall whether your sales and marketing, onboarding, and customer success is improving or not. Time-based cohort analysis is good to analyze whether your organization is continually improving or stuck.
To get at the root of weaknesses, it is important to use SaaS customer cohort analysis to dig into two specific drivers of revenue growth:
• Firstly, is your entire sales and marketing organization focused on the ideal customer profile?
• Secondly, how consistent is the performance of your sales organization?
Using Cohort Analysis to Define Target Customer Profiles
In sales, you want to “go after the low-hanging fruit.” Low hanging fruit can mean customers and deals that convert quickly. To figure that out, segment customers by sales cycle length (days from qualified lead to close).
But fast sales cycles don’t always mean the best business, so it is also important to look at sales cycles by customer value. What’s the average retention rate, average contract value, average expansion revenue of this group? Customers that close fast but churn quickly may not be worth the customer acquisition cost. Customers that close fast may be smaller customers and have little expansion or upsell opportunity. Or be your most profitable customer – you won’t know until you do the analysis.
Sort your customers by:
• Sales Cycle length,
• Average Contract Value (ACV)
• Retention and
• Customer Lifetime Value (CLV)
CLV will tell you the most profitable customers. The sales cycle length can be used as a proxy for the cost of customer acquisition (CAC) since it is often very difficult to segment CAC by customer cohorts accurately.
Once you know the characteristics of ideal target customers (size, type, geography, whatever), you can hone your marketing messages and programs and sales effort to target more of them.
Using Cohort Analysis to Improve Sales Performance
In addition to finding the characteristics of the ideal customer profile and low-hanging fruit, it is important to analyze your sales organization’s performance. The more consistent everyone in the organization is, the better the overall performance.
Is one geography better at closing deals than another, allowing for the fact that some regions are better than others for reasons out of anyone’s control? Are a few account reps typically closing deals faster and more profitably?
Quota attainment analysis will give you an understanding of which reps are achieving quota, but customer cohort analysis based on a sales rep will give you deeper insights that you can use to improve the whole organization by showing the type of customers that are high achieving and low achieving reps typically close. Low achievement may be improved by better training, closer monitoring and mentoring, and a better understanding of the target customer profile or by hiring reps better suited to your ideal customer type.
Segment customers for each account rep by:
• Products sold
• Average contract value
• Customer size and vertical industry
You’ll see patterns that were not obvious from looking at high-level analysis of the sales organization.
Benchmarking Against Peers Highlights Where to Start Doing Your Cohort Analysis
Start by benchmarking key metrics against peers and market leaders. Benchmark each of the below metrics against peers selling similar average contract values:
• Average sales cycle length
• Sales productivity (ARR/rep)
• Customer growth rate
• Retention rates: logo retention, gross dollar, and net dollar retention
Given that SaaS customer cohort analysis can take time and resources, the initial benchmark analysis will tell you where to focus first. Then segment your customer cohorts in the ways described above to improve your performance so that you are above average in each of these key indicators.