June uses a set of rules to analyse your retention inside the retention template.

Ideal frequency

To run a useful retention analysis you need to ask yourself "what's the ideal frequency at which my product should be used?". You need to figure out what makes the most sense for your business.

Usual answers are: daily, weekly, monthly or yearly;

To get the most value from June, don't forget to set up this value inside the template header.

Examples

To help you navigate this decision here are some examples:

1. Daily

  • Social networks

💡 Real life example: Whatsapp. If you’re a chat app like Whatsapp, long-term retention would more suitably be daily active usage.

2. Weekly

  • Food delivery

  • Ride sharing

  • Grocery shopping

💡 Real life example: Pinterest. It makes practical sense for users to visit them weekly to discover new inspiration for their lives. This is why Pinterest chose weekly active usage (WAU) as a measure of retention. (source)

3. Monthly

  • eCommerce

  • Subscription

4. Yearly

  • Travel (ex: Airbnb)

Main rules we use

When you craft your retention cohort, they are fundamentally four things that June is looking at:

  1. Long-term retention should be stable and parallel to the x-axis. It is common to see a dip after the first period (e.g., month 2 for high-velocity products), but the most important thing is to make sure that the long-term retention is stable and parallel to the x-axis.

  2. Long-term retention in line with "average or median" benchmarks in your specific vertical: It is important to benchmark your retention against companies in your specific vertical. For example, stable long-term retention of 10% is poor if you are a social network.

  3. If you have anything less than 20%, you've got to start paying attention, no matter what space you're in.

  4. Newer cohorts should perform better: "Cohort" refers to the group of new customers that started using your service that particular month. Determine whether newer cohorts are performing progressively better than older cohorts. If the retention of newer cohorts are better than older cohorts, it implies that you are improving your product and value proposition.

  5. Let's say your graph shows that 50% of new users don’t return after the first week. This is a strong indicator to focus even more on improving your initial onboarding and first-use of your product. Of course every product will retain differently, but it’s very common to see that the window to retain a user degrades over time, which is why it’s so important to deliver core product value as soon as possible.

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