Thomas Petit (Growth Consultant) strips each step of the pirate funnel and reveal the challenges and opportunities specific to store subscriptions
There are very different kinds of subscriptions, and the retention tactics and levers are entirely different for each subcategory:
- Content - music, books, video, comics, news, etc. → retention lever is the amount of content you're offering
- Motivation - health & fitness, dating, education (language learning, brain training) → retention lever is more about how you onboard people and re-engage them
- Utilities - photo/video editors, dropbox, grammarly, etc. → retention depends more on the value you provide to users on a regular basis.
Subscriptions align users and developers' interests. People will keep paying if you keep providing them value.
Example of Evernote: as you use it more, it becomes even more valuable and that's when the subscription model makes the most sense
When looking at retention for your subscription apps, segment your users based on their subscription status (free users, trialists, paying users) and re-engage them accordingly. Because your retention curves are going to look very different depending on subscription status.
Pay particular attention not only to the LTV but also to when the money is coming back. You want to know your ARPPU but also when the money is coming in. Yearly subscription: all the revenue for the year comes in on the first day. Monthly subscription: maybe a higher LTV but you need to "finance" the cash flow several months ahead.
Iterate on your paywall itself but also optimize on what happens before users reach the paywall and all the communication before you show prices. How people reach the paywall can have at least as much impact.
Don't measure only the impact on your initial funnel, but also the long term impact. Measuring only the impact of paywall changes on trials and uplift is risky because forcing the conversion too much can hurt both long term LTV (renewals, refunds) and user retention.
Try to focus a lot on the experience you provide to free users. Focusing only on paid subscribers can have a negative impact on organic and ASO. You don't want to ignore 90-95% of your users.
Communicate clearly and carefully about the free trial. You might even want to avoid focusing too much on the free trial in external communications because it might create more bad reviews and worst retention from users that only want "free".
Value Optimization is rarely a good fit for subscription apps (vs. app event optimization) because you have low variance between users: they are either paying, or they are not. You do not have whales.
There are very different kinds of subscriptions, and the retention tactics and levers are entirely different for each subcategory:
- Content - music, books, video, comics, news, etc. → retention lever is the amount of content you're offering
- Motivation - health & fitness, dating, education (language learning, brain training) → retention lever is more about how you onboard people and re-engage them
- Utilities - photo/video editors, dropbox, grammarly, etc. → retention depends more on the value you provide to users on a regular basis.
Subscriptions align users and developers' interests. People will keep paying if you keep providing them value.
Example of Evernote: as you use it more, it becomes even more valuable and that's when the subscription model makes the most sense
When looking at retention for your subscription apps, segment your users based on their subscription status (free users, trialists, paying users) and re-engage them accordingly. Because your retention curves are going to look very different depending on subscription status.
Pay particular attention not only to the LTV but also to when the money is coming back. You want to know your ARPPU but also when the money is coming in. Yearly subscription: all the revenue for the year comes in on the first day. Monthly subscription: maybe a higher LTV but you need to "finance" the cash flow several months ahead.
Iterate on your paywall itself but also optimize on what happens before users reach the paywall and all the communication before you show prices. How people reach the paywall can have at least as much impact.
Don't measure only the impact on your initial funnel, but also the long term impact. Measuring only the impact of paywall changes on trials and uplift is risky because forcing the conversion too much can hurt both long term LTV (renewals, refunds) and user retention.
Try to focus a lot on the experience you provide to free users. Focusing only on paid subscribers can have a negative impact on organic and ASO. You don't want to ignore 90-95% of your users.
Communicate clearly and carefully about the free trial. You might even want to avoid focusing too much on the free trial in external communications because it might create more bad reviews and worst retention from users that only want "free".
Value Optimization is rarely a good fit for subscription apps (vs. app event optimization) because you have low variance between users: they are either paying, or they are not. You do not have whales.
There are very different kinds of subscriptions, and the retention tactics and levers are entirely different for each subcategory:
- Content - music, books, video, comics, news, etc. → retention lever is the amount of content you're offering
- Motivation - health & fitness, dating, education (language learning, brain training) → retention lever is more about how you onboard people and re-engage them
- Utilities - photo/video editors, dropbox, grammarly, etc. → retention depends more on the value you provide to users on a regular basis.
Subscriptions align users and developers' interests. People will keep paying if you keep providing them value.
Example of Evernote: as you use it more, it becomes even more valuable and that's when the subscription model makes the most sense
When looking at retention for your subscription apps, segment your users based on their subscription status (free users, trialists, paying users) and re-engage them accordingly. Because your retention curves are going to look very different depending on subscription status.
Pay particular attention not only to the LTV but also to when the money is coming back. You want to know your ARPPU but also when the money is coming in. Yearly subscription: all the revenue for the year comes in on the first day. Monthly subscription: maybe a higher LTV but you need to "finance" the cash flow several months ahead.
Iterate on your paywall itself but also optimize on what happens before users reach the paywall and all the communication before you show prices. How people reach the paywall can have at least as much impact.
Don't measure only the impact on your initial funnel, but also the long term impact. Measuring only the impact of paywall changes on trials and uplift is risky because forcing the conversion too much can hurt both long term LTV (renewals, refunds) and user retention.
Try to focus a lot on the experience you provide to free users. Focusing only on paid subscribers can have a negative impact on organic and ASO. You don't want to ignore 90-95% of your users.
Communicate clearly and carefully about the free trial. You might even want to avoid focusing too much on the free trial in external communications because it might create more bad reviews and worst retention from users that only want "free".
Value Optimization is rarely a good fit for subscription apps (vs. app event optimization) because you have low variance between users: they are either paying, or they are not. You do not have whales.
Notes for this resource are currently being transferred and will be available soon.
Subscriptions are a big growth driver for Apple, and for developers it is the only way to lower the store fee down to 15%.
Subscriptions are huge outside of gaming
[💎 @01:52] There are very different kinds of subscriptions, and the retention tactics and levers retention are entirely different for each subcategory:
Example of difference of retention mechanics: the retention of a recipe apps with 2k recipes instead of 500 might not increase retention significantly vs. how you onboard people and retain them. Very different from books.
Don't take for granted anything that is generic to subscriptions because things depend on the kind of subscriptions you're selling.
[💎 @04:08] Subscriptions align users and developers' interests. People will keep paying if you keep providing them value. Example of Evernote: as you use it more, it becomes even more valuable and that's when the subscription model makes the most sense.
Different products with different value over time: burgers, news and evernote.
[💎 @05:06] When looking at retention for your subscription apps, segment your users based on their subscription status (free users, trialists, paying users) and re-engage them accordingly. Because your retention curves are going to look very different depending on subscription status.
People in a free trial period are going to end up in either free users or purchasers but you don't know until the end so they are harder to engage.
Subscriptions funnels are complex: trials, refunds, renewals. Benchmarks are scarce and mostly unreliable.
LTV & payback models for subscriptions differ from ads & IAP.
[💎 @08:11] Pay particular attention not only to the LTV but also to when the money is coming back. You want to know your ARPPU but also when the money is coming in. Yearly subscription: all the revenue for the year comes in on the first day. Monthly subscription: maybe a higher LTV but you need to "finance" the cash flow several months ahead.
With Covid-19, we have no idea how cohorts will evolve.
Here is the link to the "Grow Your Revenue With Subscription Optimizations" article that Thomas mentions.
[💎 @09:37] Iterate on your paywall itself but also optimize on what happens before users reach the paywall and all the communication before you show prices. How people reach the paywall can have at least as much impact.
[💎 @10:10] Don't measure only the impact on your initial funnel, but also the long term impact. Measuring only the impact of paywall changes on trials and uplift is risky because forcing the conversion too much can hurt both long term LTV (renewals, refunds) and user retention.
Here is the link to the "App Pricing Optimization Guide" that Thomas mentions.
Most subscriptions happen early on. If you put the paywall too late some users will have already churned before they reach it.
Store data is messy, and building your own as well. A company like RevenueCat can be helpful for this.
Challenges with subscriptions:
Organic and ASO
Paid UA Challenges
Subscriptions are a big growth driver for Apple, and for developers it is the only way to lower the store fee down to 15%.
Subscriptions are huge outside of gaming
[💎 @01:52] There are very different kinds of subscriptions, and the retention tactics and levers retention are entirely different for each subcategory:
Example of difference of retention mechanics: the retention of a recipe apps with 2k recipes instead of 500 might not increase retention significantly vs. how you onboard people and retain them. Very different from books.
Don't take for granted anything that is generic to subscriptions because things depend on the kind of subscriptions you're selling.
[💎 @04:08] Subscriptions align users and developers' interests. People will keep paying if you keep providing them value. Example of Evernote: as you use it more, it becomes even more valuable and that's when the subscription model makes the most sense.
Different products with different value over time: burgers, news and evernote.
[💎 @05:06] When looking at retention for your subscription apps, segment your users based on their subscription status (free users, trialists, paying users) and re-engage them accordingly. Because your retention curves are going to look very different depending on subscription status.
People in a free trial period are going to end up in either free users or purchasers but you don't know until the end so they are harder to engage.
Subscriptions funnels are complex: trials, refunds, renewals. Benchmarks are scarce and mostly unreliable.
LTV & payback models for subscriptions differ from ads & IAP.
[💎 @08:11] Pay particular attention not only to the LTV but also to when the money is coming back. You want to know your ARPPU but also when the money is coming in. Yearly subscription: all the revenue for the year comes in on the first day. Monthly subscription: maybe a higher LTV but you need to "finance" the cash flow several months ahead.
With Covid-19, we have no idea how cohorts will evolve.
Here is the link to the "Grow Your Revenue With Subscription Optimizations" article that Thomas mentions.
[💎 @09:37] Iterate on your paywall itself but also optimize on what happens before users reach the paywall and all the communication before you show prices. How people reach the paywall can have at least as much impact.
[💎 @10:10] Don't measure only the impact on your initial funnel, but also the long term impact. Measuring only the impact of paywall changes on trials and uplift is risky because forcing the conversion too much can hurt both long term LTV (renewals, refunds) and user retention.
Here is the link to the "App Pricing Optimization Guide" that Thomas mentions.
Most subscriptions happen early on. If you put the paywall too late some users will have already churned before they reach it.
Store data is messy, and building your own as well. A company like RevenueCat can be helpful for this.
Challenges with subscriptions:
Organic and ASO
Paid UA Challenges
Subscriptions are a big growth driver for Apple, and for developers it is the only way to lower the store fee down to 15%.
Subscriptions are huge outside of gaming
[💎 @01:52] There are very different kinds of subscriptions, and the retention tactics and levers retention are entirely different for each subcategory:
Example of difference of retention mechanics: the retention of a recipe apps with 2k recipes instead of 500 might not increase retention significantly vs. how you onboard people and retain them. Very different from books.
Don't take for granted anything that is generic to subscriptions because things depend on the kind of subscriptions you're selling.
[💎 @04:08] Subscriptions align users and developers' interests. People will keep paying if you keep providing them value. Example of Evernote: as you use it more, it becomes even more valuable and that's when the subscription model makes the most sense.
Different products with different value over time: burgers, news and evernote.
[💎 @05:06] When looking at retention for your subscription apps, segment your users based on their subscription status (free users, trialists, paying users) and re-engage them accordingly. Because your retention curves are going to look very different depending on subscription status.
People in a free trial period are going to end up in either free users or purchasers but you don't know until the end so they are harder to engage.
Subscriptions funnels are complex: trials, refunds, renewals. Benchmarks are scarce and mostly unreliable.
LTV & payback models for subscriptions differ from ads & IAP.
[💎 @08:11] Pay particular attention not only to the LTV but also to when the money is coming back. You want to know your ARPPU but also when the money is coming in. Yearly subscription: all the revenue for the year comes in on the first day. Monthly subscription: maybe a higher LTV but you need to "finance" the cash flow several months ahead.
With Covid-19, we have no idea how cohorts will evolve.
Here is the link to the "Grow Your Revenue With Subscription Optimizations" article that Thomas mentions.
[💎 @09:37] Iterate on your paywall itself but also optimize on what happens before users reach the paywall and all the communication before you show prices. How people reach the paywall can have at least as much impact.
[💎 @10:10] Don't measure only the impact on your initial funnel, but also the long term impact. Measuring only the impact of paywall changes on trials and uplift is risky because forcing the conversion too much can hurt both long term LTV (renewals, refunds) and user retention.
Here is the link to the "App Pricing Optimization Guide" that Thomas mentions.
Most subscriptions happen early on. If you put the paywall too late some users will have already churned before they reach it.
Store data is messy, and building your own as well. A company like RevenueCat can be helpful for this.
Challenges with subscriptions:
Organic and ASO
Paid UA Challenges
