Andy Carvell (Phiture - mobile growth consultancy) outlines why in-app messages work, when they work – and talks about the tremendous impact they can have.
You can use a push notification or email to have users come into the app, before showing the in-app message adapted to the segment. That way you chain these campaigns together to leverage the strengths of these different channels.
Best use cases for in-app messages: on-boarding, upselling, content recommendation and surveys.
If you are building slightly more advanced in-app messages with javascript you can ping results of surveys straight back into CRM system to enrich user profiles and start immediately segmenting them.
Simplified "propensity to churn" model: at SoundCloud they looked at the whole userbase to define how many days users should be inactive and mapped out the graph of when they should contact them to reactivate them.
Simplified "propensity to purchase": build a kind of intent model. Look at the signs of intent to purchase and sort them by level of intent: click on a feature that is behind the paywall, interaction with the paywall, starting a free trial, etc.
People are very willing to answer surveys and seem to actually like being asked for their opinion about things, including during onboarding.
When it comes to in-app messages something important is to have trigger points, not just target based on a segment. But keep in mind the smaller reach you might get if you go with something too narrow: you want to get statistical significance.
Low-hanging fruits for in-app messages: work on the onboarding flow. Figure out your key features/screens in the app (something tied to better activation rates), target users that haven't used/seen these features and educate/deep link to them.
You can use a push notification or email to have users come into the app, before showing the in-app message adapted to the segment. That way you chain these campaigns together to leverage the strengths of these different channels.
Best use cases for in-app messages: on-boarding, upselling, content recommendation and surveys.
If you are building slightly more advanced in-app messages with javascript you can ping results of surveys straight back into CRM system to enrich user profiles and start immediately segmenting them.
Simplified "propensity to churn" model: at SoundCloud they looked at the whole userbase to define how many days users should be inactive and mapped out the graph of when they should contact them to reactivate them.
Simplified "propensity to purchase": build a kind of intent model. Look at the signs of intent to purchase and sort them by level of intent: click on a feature that is behind the paywall, interaction with the paywall, starting a free trial, etc.
People are very willing to answer surveys and seem to actually like being asked for their opinion about things, including during onboarding.
When it comes to in-app messages something important is to have trigger points, not just target based on a segment. But keep in mind the smaller reach you might get if you go with something too narrow: you want to get statistical significance.
Low-hanging fruits for in-app messages: work on the onboarding flow. Figure out your key features/screens in the app (something tied to better activation rates), target users that haven't used/seen these features and educate/deep link to them.
You can use a push notification or email to have users come into the app, before showing the in-app message adapted to the segment. That way you chain these campaigns together to leverage the strengths of these different channels.
Best use cases for in-app messages: on-boarding, upselling, content recommendation and surveys.
If you are building slightly more advanced in-app messages with javascript you can ping results of surveys straight back into CRM system to enrich user profiles and start immediately segmenting them.
Simplified "propensity to churn" model: at SoundCloud they looked at the whole userbase to define how many days users should be inactive and mapped out the graph of when they should contact them to reactivate them.
Simplified "propensity to purchase": build a kind of intent model. Look at the signs of intent to purchase and sort them by level of intent: click on a feature that is behind the paywall, interaction with the paywall, starting a free trial, etc.
People are very willing to answer surveys and seem to actually like being asked for their opinion about things, including during onboarding.
When it comes to in-app messages something important is to have trigger points, not just target based on a segment. But keep in mind the smaller reach you might get if you go with something too narrow: you want to get statistical significance.
Low-hanging fruits for in-app messages: work on the onboarding flow. Figure out your key features/screens in the app (something tied to better activation rates), target users that haven't used/seen these features and educate/deep link to them.
Notes for this resource are currently being transferred and will be available soon.
Andy believes in-app messages are the golden channel for mobile right now.
It is a small user interaction unit that is delivered from a server-side platform (Braze, LeanPlum, CleverTap, etc.). The way it behaves is down to the marketer and some platforms allow more flexibility than others:
Platforms allow to build out what's essentially a small HTML webview.
In-app messages target people that are already using an app.
Just like push notifications and e-mail, in-app messages are typically deployed through a marketing automation platform so you can segment how you wish and measure the impact.
Other key difference: with in-app messages not only you are able to reach active users, but they would typically be triggered after a specific event (doing an action, landing on a screen) so you can show them in a very contextual moment.
[💎@06:55] You can use a push notification or email to have users come into the app, before showing the in-app message adapted to the segment. That way you chain these campaigns together to leverage the strengths of these different channels.
[💎@07:40] Best use cases for in-app messages:
There is often tension between the growth marketing team and the design team re: in-app messages because you are "getting up in users' face" so you better deliver value. However they routinely see insane conversions from them.
Segmentation is crucial and you might want to understand probabilities of users reacting a certain way. This is the "next level" of personalization, using AI, propensity scoring, etc.
Andy hasn't seen this really well done by any product yet and has seen several smart teams struggling to build propensity/prediction models.
You can get pretty far with that kind of logic before going into trying to build a deep machine learning model.
[💎@20:47] People are very willing to answer surveys and seem to actually like being asked for their opinion about things.
Custom recommendations also work really well.
[💎@22:00] When it comes to in-app messages something important is to have trigger points, not just target based on a segment. But keep in mind the smaller reach you might get if you go with something too narrow: you want to get statistical significance.
Example: segment of users that are on the 3rd day with the trigger point of adding something to their cart.
In terms of infrastructure: do not build it yourself. If really on a budget, you can use Firebase.
Andy believes in-app messages are the golden channel for mobile right now.
It is a small user interaction unit that is delivered from a server-side platform (Braze, LeanPlum, CleverTap, etc.). The way it behaves is down to the marketer and some platforms allow more flexibility than others:
Platforms allow to build out what's essentially a small HTML webview.
In-app messages target people that are already using an app.
Just like push notifications and e-mail, in-app messages are typically deployed through a marketing automation platform so you can segment how you wish and measure the impact.
Other key difference: with in-app messages not only you are able to reach active users, but they would typically be triggered after a specific event (doing an action, landing on a screen) so you can show them in a very contextual moment.
[💎@06:55] You can use a push notification or email to have users come into the app, before showing the in-app message adapted to the segment. That way you chain these campaigns together to leverage the strengths of these different channels.
[💎@07:40] Best use cases for in-app messages:
There is often tension between the growth marketing team and the design team re: in-app messages because you are "getting up in users' face" so you better deliver value. However they routinely see insane conversions from them.
Segmentation is crucial and you might want to understand probabilities of users reacting a certain way. This is the "next level" of personalization, using AI, propensity scoring, etc.
Andy hasn't seen this really well done by any product yet and has seen several smart teams struggling to build propensity/prediction models.
You can get pretty far with that kind of logic before going into trying to build a deep machine learning model.
[💎@20:47] People are very willing to answer surveys and seem to actually like being asked for their opinion about things.
Custom recommendations also work really well.
[💎@22:00] When it comes to in-app messages something important is to have trigger points, not just target based on a segment. But keep in mind the smaller reach you might get if you go with something too narrow: you want to get statistical significance.
Example: segment of users that are on the 3rd day with the trigger point of adding something to their cart.
In terms of infrastructure: do not build it yourself. If really on a budget, you can use Firebase.
Andy believes in-app messages are the golden channel for mobile right now.
It is a small user interaction unit that is delivered from a server-side platform (Braze, LeanPlum, CleverTap, etc.). The way it behaves is down to the marketer and some platforms allow more flexibility than others:
Platforms allow to build out what's essentially a small HTML webview.
In-app messages target people that are already using an app.
Just like push notifications and e-mail, in-app messages are typically deployed through a marketing automation platform so you can segment how you wish and measure the impact.
Other key difference: with in-app messages not only you are able to reach active users, but they would typically be triggered after a specific event (doing an action, landing on a screen) so you can show them in a very contextual moment.
[💎@06:55] You can use a push notification or email to have users come into the app, before showing the in-app message adapted to the segment. That way you chain these campaigns together to leverage the strengths of these different channels.
[💎@07:40] Best use cases for in-app messages:
There is often tension between the growth marketing team and the design team re: in-app messages because you are "getting up in users' face" so you better deliver value. However they routinely see insane conversions from them.
Segmentation is crucial and you might want to understand probabilities of users reacting a certain way. This is the "next level" of personalization, using AI, propensity scoring, etc.
Andy hasn't seen this really well done by any product yet and has seen several smart teams struggling to build propensity/prediction models.
You can get pretty far with that kind of logic before going into trying to build a deep machine learning model.
[💎@20:47] People are very willing to answer surveys and seem to actually like being asked for their opinion about things.
Custom recommendations also work really well.
[💎@22:00] When it comes to in-app messages something important is to have trigger points, not just target based on a segment. But keep in mind the smaller reach you might get if you go with something too narrow: you want to get statistical significance.
Example: segment of users that are on the 3rd day with the trigger point of adding something to their cart.
In terms of infrastructure: do not build it yourself. If really on a budget, you can use Firebase.
