Use cohort analysis to find your ICP

1. Test different trial period lengths and look at factors like how long participants took to convert, the price points they chose, how many upgraded or downgraded, and which percentage were still paying customers after 90 days.

You can also look at prospects in the trial who received a certain email follow-up sequence or went through a particular customer onboarding process. Which ones turned into customers, and how much were those customers worth over time? Common Conversion Activities (CCAs) show what prospects in your free trial did right before they became a customer. Once you know that, you can work to orchestrate those activities with new prospects.

2. Look for characteristics of your customers on the highest pricing tier, that set them apart from other customers.

You can also look at customers that paid upfront instead of monthly on an ongoing basis. Look for characteristics like: The marketing channel that brought them in. Time to purchase. When they signed up. What type of company they are.

3. Rank your customers by lifetime spend on upsells and examine the highest spenders to see which channels they arrived through, and any other characteristics that can help you develop a valuable customer profile.

Check their lifetime value to you against the cost of acquiring them, just in case they’re not actually that profitable because you had to spend too much to gain their custom.

4. Compare your current customer and prospect base, with your ideal customer and valuable customer profiles.

Are you attracting prospects who fit these profiles? If you aren’t, why not? Can you adjust your marketing to reach people who do fit those profiles? Selling to the wrong customers is likely to lead to frustration for everyone.

5. Pick groups to track over time, that will give you insight into your sales and marketing strategies.

This won’t be the same for everyone as it depends on your goals and KPIs. KISSMetrics laid out some questions to ask yourself when thinking about which cohorts to track: Will the data I get from these cohorts produce insights that can change my marketing strategy? Will I be able to clearly know what’s working and what’s not when it comes to marketing? What targets do I need to hit this year? Will this cohort help me improve that metric? For example, PPC Hero chose to create a segment to include only users who purchased a specific brand. Their metric was revenue. Most of the revenue, of course, occurred during week 0 (acquisition), but there is also a decent amount in weeks 1 and 2. So PPC Hero looked at days to transaction for this segment. From this, they could tell that 4.95% of transactions happen between days 7-13. They could also see fluctuations in conversions, which might allude to some form of external promotion. Using this data, they can better plan for their remarketing campaign, homing in on the times that customers are most likely to purchase.