The bottom line
RevenueCat's charts on revenue mix, trial conversion and LTV show whether a subscription app is healthy and ready to scale. Reading them tells you what to fix and whether paid ads can pay off.
Key takeaways
- New revenue should grow faster than renewal revenue. 3:06
- Segmenting by transaction type in one month showed about $56,000 in sales, with roughly $22,000 to $23,000 from renewals and $34,000 from new customers.
- In July, new revenue fell and renewals rose after ad spend was cut. Profit was the best of the year, but renewals outpacing new sales can signal a dying app.
- Trial start rate and trial-to-paid rate show how well the funnel converts. 4:02
- A start rate of 5 to 10% is good, above 10% is great, and above 20% is rare and amazing.
- Trial-to-paid averages 30 to 40%. This niche health app with a 7-day trial converts over 60%.
- LTV per customer decides whether an app can run paid media. 5:21
- His personal rule is that an app needs roughly $3 per install within 30 days.
- Stretching the window to 12, 18 or 24 months barely moves it, to about $3.30. The levers are conversion rates and pricing.
- Paywall experiments show which changes raise conversions and revenue. 7:53
- A paywall variant with money-back guarantee wording is beating the control on initial conversions and trial activations.
- The test is only 4 days old, so it needs more days. He checks conversions at the top of the report and LTV and revenue at the bottom.
- Web funnels may reach buyers who won't purchase inside an app. 9:32
- His Facebook ads to an older audience get strong hook rates, hold rates and cost per install, but the installs don't convert.
- This is an untested hypothesis. He plans to test RevenueCat's web-to-app funnels in a later video.
I want the new to outpace the renewals because if I see something different, you might have a dying app.
Steve P. Young
Chapter summaries
0:00 Segmenting the revenue chart
Splitting revenue by country and by product shows where the money comes from and which offers carry the app.
- Country segmentation shows where sales concentrate. 1:44
- Most sales come from the US, with a few from Canada and the UK.
- A new app is showing early traction in Kenya.
- He is starting ASO and ASA campaigns in Kenya, though the app only just launched.
- The app shown is established and about $37,000 MRR. He bought it.
- Product segmentation shows which plan earns the most. 3:35
- It compares monthly and yearly plans.
- For this app, yearly earns the most.
- He hides the product view on screen so it doesn't reveal too much about the app.
- Transaction type can also be found by search, under products and offering.
3:57 Trial conversion and LTV
The trial chart in relative view and LTV per customer show whether the funnel is healthy enough to buy traffic.
- Trial conversion should be read in relative view. 4:05
- Switch the chart from absolute to relative to see rates, not counts.
- Trial activation rate is the first question he asks new clients.
- His own start rate is high, and he thinks he could still lift it toward 12%.
- January inflates start rates in health and fitness. The more niche the app, the higher both rates go.
- LTV per customer matters most when running paid ads. 5:15
- It is a key sign of whether paid media can work.
- The chart shows LTV across a 30-day span.
- The roughly $3 threshold is his personal opinion, not an industry rule.
- The chart here is the one he checks before spending on ads.
5:41 How long to wait for payback
A longer payback window barely changes LTV for this app, so the cash you can tie up matters more than the chart.
- An advertiser's cash reserve sets how long they can wait for returns 5:56
- Spending $10,000 now and waiting a year for $15,000 only works with money in the bank.
- At 18 months the figure is $329, and at 24 months it barely moves.
- The customer lifetime window is a variable you can change in the chart.
- The higher the number, the better the position.
- RevenueCat can serve as the attribution source for Apple Ads 6:50
- Under acquisition, you can view results by campaign.
- It isn't connecting properly for him, but other clients have it working.
- Done right, it shows how each Apple Ads campaign performs inside RevenueCat.
7:23 Paywalls and experiments
A custom-built paywall can still be tested with RevenueCat's experiment tool.
- A custom paywall beats RevenueCat's builder for now, and the A/B test still runs there 7:33
- RevenueCat's own paywall is pretty basic in his opinion.
- He builds the paywall himself and uses RevenueCat only to run the test.
- You can build paywalls inside RevenueCat or do it custom.
- The results summary sits lower on the page, and the full report holds the detail.
9:04 Web funnels and the API
RevenueCat's funnels and API extend its reach beyond the built-in charts.
- Web-to-app funnels are the next thing to test 9:07
- Many people have seen success with them, and he thinks they are the future.
- The app works well for organic and Apple Ads traffic.
- The idea is to get buyers to pay on the web, then move them into the app.
- He hasn't tried the feature yet.
- The API can feed an AI-built weekly report 10:24
- Technical users can pull RevenueCat data into Claude and have it build its own analysis platform.
- That platform would give a weekly report.
In the growth library
Steve P. Young, Founder of App Masters, app marketing agency and app publisher. A walkthrough of the RevenueCat charts and features used to judge subscription app health and decide when an app is ready for paid acquisition. It shows a roughly $37,000 MRR app with a 7-day trial converting over 60% of trial starts to paid, and a paywall test where a money back guarantee is winning.
Lessons that draw on this:
- How to run free trials and free tastes
- How to tell if paid acquisition is profitable
- How to set, raise and localize prices
- How to design a paywall that converts
- How to judge test results correctly
- How to measure retention honestly
- What metrics to track and how to define them
- How to price annual and monthly plans
- How to build quiz funnels for paid traffic
- How to run trustworthy experiments
- How to work as a team with AI agents
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