# Increasing Retention with Push, In-App and Email Part 3: Implementing the Strategy

- Link: https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/
- Published: 2019-12-19T10:20:46+01:00
- Author: Andy Carvell

_This is the third part of a three-part series. In the first part, I outlined _[_how to audit your mobile app retention efforts_](https://phiture.com/mobilegrowthstack/increasing-mobile-retention-a4b7ffd6b4e2/)_
and in part two, I wrote about _[_Developing the Strategy_](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-email-part-2-458daac45d6c/)

![Increasing Retention with Push, In-App and Email Part 3- Implementing the Strategy](
https://phiture.com/wp-content/uploads/2019/12/Increasing-Retention-with-Push-In-
App-and-Email-Part-3-Implementing-the-Strategy-min.png)

In the previous article, I outlined some different strategies that can be employed
to increase mobile app retention. I also zeroed-in on four approaches which are 
particularly suitable for using CRM / Mobile Marketing Automation as a tactical 
lever. These are:

 * Improving Activation Rates
 * Increasing Frequency of Use
 * Increasing Feature Adoption
 * Re-Engagement of Lapsed or Churned Users

In this final part, I’ll talk about how to tackle the implementation of each of 
these strategies through marketing automation of Push, In-App and Email campaigns.
I’ll also cover one critical pre-requisite for maximizing impact with these channels:
optimizing _reach_.

Disclaimer: Every app is different and the examples that I provide in this article
are illustrative rather than prescriptive. There is no one-size-fits-all approach
to CRM and readers are advised to iterate toward increasing impact with their push,
in-app and email efforts through continuous experimentation with creative ideas 
and data-informed hypotheses. Nevertheless, in this article, I’ll endeavor to outline
some tactics that might provide a useful starting point, or inspiration for your
own experiments.

Table of Contents

 * [Reach: Nurturing Opt-In Rates for Push and Email](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/#reach_nurturing_opt-in_rates_for_push_and_email)
 * [Improving Activation Rates](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/#improving_activation_rates)
 * [Analyze funnel drop-offs and create win-back campaigns](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/#analyze_funnel_drop-offs_and_create_win-back_campaigns)
 * [Experiment to uncover the right ‘Nudge Moments’](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/#experiment_to_uncover_the_right_%e2%80%98nudge_moments)
 * [Adaptive Onboarding (selective feature education)](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/#adaptive_onboarding_selective_feature_education)
 * [Welcome Emails: Still Worth Doing](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/#welcome_emails_still_worth_doing)
 * [Increasing Frequency of Use](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/#increasing_frequency_of_use)
 * [Gamification](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/#gamification)
 * [Increasing Feature Adoption](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/#increasing_feature_adoption)
 * [Re-Engagement of Lapsed or Churned Users](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/#re-engagement_of_lapsed_or_churned_users)
 * [A word about measurement](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/#a_word_about_measurement)
 * [Summary](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/#summary)

## **Reach: Nurturing Opt-In Rates for Push and Email**

In order to leverage Push and Email as channels, it’s necessary to secure — and 
ideally retain — permission to send push notifications (iOS platform. Android users
are opted in by default) and also for the user to provide their email address. It’s
a good idea to collect these permissions early, so that these channels can be used
to reach users who have failed to activate and are not seen in the app. It’s inadvisable
to wait too long to ask for Push and Email permissions; a large percentage (often
more than half) of a new user cohort will fail to activate successfully and churn
out of the app after their first session. Without push or email, there will be literally
no way to reach the user to help them complete the onboarding process.

Improving the reach of opt-in channels like Push and Email increases the efficacy
of all subsequent communications and will enable more impact to be delivered across
the entire lifecycle.

_Push Permissions_

Apple requires that iOS apps request permission from users in order to send push
notifications. To do this, the app must display a system dialog which ios known 
as an APN (Apple Push Notification) prompt. The APN prompt looks like this:

⌊The iOS system prompt (aka APN prompt) for push notification permissions ⌉⌊The 
iOS system prompt (aka APN prompt) for push notification permissions ⌉

_The iOS system prompt (aka APN prompt) for push notification permissions_

The APN prompt can only be displayed to users once; if the user selects ‘Don’t Allow’,
it’s not possible for the app to ask again, unless the user changes device or re-
installs the app. It’s therefore critical to show the APN prompt at a time when 
the user is likely to accept push notifications and hit the ‘OK’ button.

The APN prompt is not customizable; it looks the same in every app. In-App Messages
provide a great way to increase the chances of acceptance in the APN prompt, through
the use of “Push Pre-Permissioning”. Using an In-App Message to communicate compelling
reasons to enable push, then showing the APN prompt only to users who indicate they
will accept the permissions, is a tactic that often proves useful in increasing 
opt-in rates. Users who say “Not Now” in the In-App Message are _not_ shown the 
APN prompt and can be approached again later, in another app session, with another
in-app message (possibly touting different benefits of enabling push) to see if 
they are now ready to turn on push.

⌊A Push-Priming In-App Message in the Grabble app ⌉⌊A Push-Priming In-App Message
in the Grabble app ⌉

_A Push-Priming In-App Message in the [Grabble](http://www.grabble.com/) app_

Users who saw the APN prompt and selected “Don’t Allow” cannot be sent any push 
notifications. However, users who are still active in the app can be asked to turn
Push Notifications on in the iOS Settings app and can even be deep-linked directly
into the Settings App to make it as easy as possible for them to change their permissions.
This approach, which I call a “Push Win-Back” typically yields strong results; a
decent proportion of users who initially declined push are often willing to reconsider
once they have become more familiar with the app and appreciate the value it brings.

⌊A Push ‘Win-Back’ In-App Message in the Burner app ⌉⌊A Push ‘Win-Back’ In-App Message
in the Burner app ⌉

_A Push ‘Win-Back’ In-App Message in the Burner app_

The benefit of deploying push pre-permission and win-back campaigns as in-app messages(
versus natively) is manifold: targeting, triggering and messaging can all be AB 
tested and iterated towards higher performance (in this case: higher opt-in rates).

#### **Email Collection + Permissions**

In order to send users email, it’s necessary for them to provide their email address.
This is often collected as part of the signup process and might also double as a
unique account name / identifier. Note that users may provide invalid email addresses,
either deliberately or through a careless typo. In order to preserve the [email reputation](https://www.towerdata.com/blog/bid/116384/email-reputation-what-it-s-all-about)
of your domain — if reputation drops too low, emails you send will be automatically
flagged as spam and fail to reach users’ inboxes — it’s advisable to implement email
verification.

Companies such as [mailboxlayer](https://mailboxlayer.com/) and [250OK](http://www.250ok.com/)
provide solutions to streamline this process and catch bad email addresses before
sending out a verification email, but many services still require this ‘double-opt-
in’ of sending an email to the user asking them to confirm their email address. 
While increasing friction, email double-opt-in can also help to ensure you have 
the _active consent _of the user, an important component of [GDPR](https://en.wikipedia.org/wiki/General_Data_Protection_Regulation),
[CCPA](https://en.wikipedia.org/wiki/California_Consumer_Privacy_Act) and similar
privacy legislation.

⌊An example of an email double-opt-in (aka verification : account confirmation email)
from Freeletics⌉⌊An example of an email double-opt-in (aka verification : account
confirmation email) from Freeletics⌉

_An example of an email double-opt-in (aka verification / account confirmation email)
from [Freeletics](https://www.freeletics.com/en/)_

Email reach is a big topic in its own right. Check out this article by Ed Burrows
for a deep dive on how to [measure, model and improve email reach](https://mobilegrowthstack.com/building-an-email-growth-model-af958898397b).

## **Improving Activation Rates**

Activation is a critical step; onboarding new users effectively is always a challenge
and typically presents a great opportunity. Rarely does a growth team believe that
their onboarding is optimal; there’s almost always room for improvement.

Although the onboarding steps that lead to an ‘activated’ user are app-specific,
there are some CRM tactics that can be applied in most activation situations. In
this section, I’ll lay out some basic approaches that often help.

_Tackling Funnel Drop-Offs_

Start by mapping out the key activation steps in your app and ensuring that each
of these steps has an associated analytics event that is tracked. Create a funnel
visualization of the activation steps:

⌊Activation funnel example- in this case, activation is defined as making a first
purchase (quite an ambitious definition, but can make sense for transactional products)⌉⌊
Activation funnel example- in this case, activation is defined as making a first
purchase (quite an ambitious definition, but can make sense for transactional products)⌉

_Activation funnel example: in this case, activation is defined as making a first
purchase (quite an ambitious definition, but can make sense for transactional products)_

## **Analyze funnel drop-offs and create win-back campaigns**

In every activation funnel (assuming the steps are measured at a suitably high granularity),
you’ll see some friction points, where there are significant drop-offs between steps
in the funnel. If these drop-offs can be reduced (i.e. if more users can be helped
to the next step in the funnel), the overall activation rate will increase. This
approach can be used for any key engagement funnel: not just for activation steps.

As well as intervening with messaging to improve overall funnel completion, it may
be possible to accelerate users through the funnel. When designing experiments, 
look at funnel stages with big drop-offs and also those with a long time between
funnel steps: in the best case, you can improve _and_ accelerate activation.

⌊An example activation funnel for a Meditation App (fake data) ⌉⌊An example activation
funnel for a Meditation App (fake data) ⌉

_An example activation funnel for a Meditation App (fake data)_

In the above example, we see that around 60% of users complete the app onboarding
flow within 2 minutes. This represents a huge opportunity to “win back” the 40% 
of users are dropping out of the funnel before completing onboarding.

One simple, but effective tactic is to send a push notification reminding the user
to complete the onboarding process. We can see from the average completion time 
that it would be fairly safe to send this message just a few minutes after the user
started the onboarding process; likely the user got distracted and may be easily
brought back to the app if reminded while the intent is still fresh in their minds.

⌊An example of a ‘win-back’ push campaign from Fishbrain ⌉⌊An example of a ‘win-
back’ push campaign from Fishbrain ⌉

_An example of a ‘win-back’ push campaign from [Fishbrain](http://www.fishbrain.com/)_

Email is another handy channel for win-backs: an onboarding win-back email could
provide more detail about exactly what steps the user needs to complete. In either
case, the message — when clicked — should deep-link the user back into the onboarding
at the point they left off.

## **Experiment to uncover the right ‘Nudge Moments’**

If a user is stuck at a critical step in the activation funnel (often the last step,
where they actually _do_ _the_ _thing_ the app is facilitating and hence really 
_get_ the value proposition), a gentle nudge may be all it takes to increase completion
rate, as well as lower the average funnel completion time. A nudge will perform 
best if it correctly anticipates a time of need (e.g. sent around mealtimes for 
food delivery apps, for example, or when the user is likely to be at home on the
couch for a streaming TV show recommendation) and all the more if it’s personalized
somehow using data collected in the onboarding process, the context of the advert
they clicked on, or from real-world data such as weather, traffic info or other 
live APIs.

A carefully-constructed nudge leverages intent data and is sent at a time (or — 
better — an algorithm that personalizes the time) that is proven to be above-averagely
effective by testing across multiple new user cohorts against viable alternatives.
The below example from Headspace leverages user intent data collected during onboarding(
user-selected time to meditate, user-selected reason for meditating) to create an
experience that is welcomed by its recipients rather than feeling like a clumsy 
plea to use the app.

⌊A carefully-constructed nudge leverages intent data and is sent at a time likely
to be effective ⌉⌊A carefully-constructed nudge leverages intent data and is sent
at a time likely to be effective ⌉

_A carefully-constructed nudge leverages intent data and is sent at a time likely
to be effective_

## **Adaptive Onboarding (selective feature education)**

While in-product onboarding experiences are often well-crafted and work well for
the majority of users, activation of new users is always a challenge. One massive
advantage of CRM-based approaches is that they can be targeted at specific segments
of users who seem to be struggling or disengaged. By employing ‘adaptive onboarding’,
users who activated already can be left alone, whereas those that need extra help
can receive it in a targeted way via Push, Email or In-App.

⌊An example of adaptive onboarding- highlighting the Search feature to users who
didn’t use it yet ⌉⌊An example of adaptive onboarding- highlighting the Search feature
to users who didn’t use it yet ⌉

_An example of adaptive onboarding: highlighting the Search feature to users who
didn’t use it yet_

The same tactic can be used to drive feature adoption at any stage in the lifecycle,
or when new features are introduced.

## **Welcome Emails: Still Worth Doing**

Welcome emails are not exactly at the top of the hype curve these days when it comes
to cutting-edge marketing, but they still work. A strong welcome email achieves 
a bunch of measurable and harder-to-measure objectives:

 * Setting the tone of a brand’s communication with the user and getting across 
   the brand personality
 * Reconfirming the user’s expectations about the value the app will deliver (these
   expectations having been created by the app’s store listing and any advertising
   the user encountered prior to downloading)
 * Providing additional information about the app’s features and benefits
 * Communicating the next steps to help the user onboard successfully
 * Bringing the user back into the app to continue their activation journey with
   a clear Call-To-Action (CTA)

In the case of Lyft, the CTA is ‘Take a Ride’: a smart choice given that their definition
of activation is almost certainly taking the first ride.

⌊Lyft Welcome Email⌉⌊Lyft Welcome Email⌉

_Lyft Welcome Email, via [ReallyGoodEmail](https://reallygoodemails.com/)_

## **Increasing Frequency of Use**

To increase a user’s average number of sessions within the app, the user needs good
reasons to initiate their next session. For some apps, these reasons come very naturally:
media apps that have regular fresh content and social apps where users interact 
with each other both provide rich pickings for **activity notifications**. For some
other apps, the opportunities to legitimately interact with the user in a non-spammy
way are more limited. In some cases, **gamification** tactics can prove highly effective
in maintaining and increasing user motivation.

As always with CRM — but perhaps especially when trying to increase usage frequency—
It’s worth keeping in mind that there are limits to the effectiveness of notifications
and lifecycle campaigns and no ‘growth tactics’ can compensate for a lack of substance
in the product itself.

Activity notifications — notifying the user about something external to them —are
by far the best lever for driving up usage frequency. Anyone who has used Facebook,
Twitter or Instagram has experienced launching the app multiple times in an hour
and possibly tens or hundreds of times in a day. Social apps that provide connections
and feedback signals from real people.

What’s worth noting about social apps is that the average user session is pretty
short: these are almost micro-engagements: checking messages, responding to a comment,
liking a new post, etc.

With analysis of user behavior in the app, it should be possible to observe such‘
micro-engagement’ sessions and, possibly, see some segments of users engaging more
deeply while others limit their usage to frequent micro-engagements.

_When you give users new entry points to the app (such as push notifications), reducing
the friction to interact with specific (especially social) functionality, you can
expect frequency to increase, and average session length to decrease._

An app is ripe for activity notifications if:

 * It has a lot of content, with new content becoming regularly available (e.g. 
   media, news, workouts, books, etc.)
 * It provides access to a social network of other users who can interact with each
   other, either directly or indirectly, through the app (e.g. direct or group messaging,
   posting, like, repost, comment on posts, etc.)
 * There are significant real-world events that are relevant to the user (e.g. traffic
   alerts, weather updates, concert announcements, etc.)

To implement an effective set of activity notifications, follow this checklist:

 1. Start by developing those notifications with the highest reach, according to the
    [RRF Framework](https://mobilegrowthstack.com/rrf-a-framework-for-building-impactful-notifications-73c7b91c45a7).
 2. Build or augment a back-end system that can trigger notifications based on events
    that are being fired within the system. At the very least, your backend system 
    needs to be able match events to users they are relevant for and to generate an
    API call to a marketing automation tool (or home-grown system) that can deliver
    the notifications.

⌊A high level abstraction of a smart activity notifications service⌉⌊A high level
abstraction of a smart activity notifications service⌉

_A high-level abstraction of a smart activity notifications service ([more on how to build one](https://phiture.com/mobilegrowthstack/fear-and-loathing-of-notifications-31dd117bb66b/))_

 3.  Ensure that each notification has an associated Deeplink implemented in the app:
    the notification should be a short-cut to the specific content, update or functionality
    that it relates to.
 4.  Test out each new notifications with its own control group, to measure impact.
    Be sure to measure negative impacts too, including opt-outs, complaints and decrease
    in usage. Also build a global holdout that is never exposed to any notifications,
    as well as a test group that receives all the notifications.

## **Gamification**

The concept of gamification comes from the video game industry. Game developers 
have known forever that players can be motivated by the idea of progress, high scores
and competition (either against themselves or others). Other digital products have
also had success with implementing such mechanics:

[⌊Headspace uses ‘RunStreaks’ (continuous days meditated) to encourage daily usage
of the app⌉⌊Headspace uses ‘RunStreaks’ (continuous days meditated) to encourage
daily usage of the app⌉[

_[Headspace](http://www.headspace.com/) uses ‘RunStreaks’ (continuous days meditated)
to encourage daily usage of the app_

CRM can prove highly effective at re-enforcing gamification mechanics, for example
through the use of reminders, congratulatory messaging. It’s often even possible
to implement rudimentary gamification in CRM without touching the product. In this
way, a growth team can rapidly prototype and test a gamification approach to see
if it delivers the desired uplift.

_Gamification works best when it’s baked into the app (see above), but simple Gamification
mechanics such as Trophies, Runstreak Congratulations and even Goal Setting can 
be implemented and/or prototyped using CRM_

Classic gamification tactics include:

 * Setting Goals and then holding users accountable to them / showing progress towards
   them
 * Tracking and reporting on ‘streaks’ (periods of regular use / achievement) of
   indeterminate length
 * Congratulating the user on personal bests, achievements (of any kind) or other
   forms of progress (inc. runstreak milestones)

All of the above can be prototyped using CRM (using In-App Messaging, even goal 
setting and progress tracking can be implemented without any native app code) even
if they are ultimately implemented natively in the app. Even if the decision is 
made to build gamification in at product level, CRM serves as a great way to:

 * Remind users when a streak is about to expire or a goal is in danger of being
   missed — push notifications are a great channel to generate urgency in such circumstances
 * Congratulate users on achievements (Push, In-App Messages and Email all work 
   for this, especially in combination)
 * Provide regular ‘stats summary’ updates

Below is a section of a stats summary from pet tracking app [Whistle](https://play.google.com/store/apps/details?id=com.whistle.bolt&hl=en).
It provides various ‘quantified pet’ data points to motivate users to exercise their
pet (using the Whistle GPS tracker of course) more regularly. Human fitness apps
also employ such gamification techniques extensively in their CRM programs.[⌊Whistle — a fitness tracker for pets — uses gamification in it’s weekly stats summary emails ⌉](https://play.google.com/store/apps/details?id=com.whistle.bolt&hl=en)

_[Whistle](https://play.google.com/store/apps/details?id=com.whistle.bolt&hl=en)—
a fitness tracker for pets — uses gamification in it’s weekly stats summary emails(
pictured)_

## **Increasing Feature Adoption**

There are three reasons a user will use a particular feature:

 1. they saw it
 2. they tried it and..
 3. they found it useful when they saw it and tried it

Marketing Automation / CRM can be highly effective at increasing adoption. By targeting
users who have never used a specific feature with an email explaining the benefits
of it, many more users will be influenced to try it out.

⌊An example of a ‘new feature’ email from MailChimp ⌉⌊An example of a ‘new feature’
email from MailChimp ⌉

_An example of a ‘new feature’ email from MailChimp_

A new feature’s exposure rate (the %ge of users who actually see and interact with
the feature at least once) is often far below 100%. This means that product teams
spend a ton of time building features that users don’t even see, let alone love.

Companies often put a lot of effort into ‘launching’ new features in order to mitigate
this risk. While feature launches still have their place, this is an old-school 
marketing tactic. Only _current_ users will experience any launch communications(
often little more than an email and company blog post) and new users may not be 
exposed to the feature at all in the app onboarding. This leads to situations where
features are poorly adopted and have poor engagement metrics. Recurring feature-
education emails for new AND returning users (similar to adaptive onboarding, but
could be considered ‘adaptive engagement’) are long-term far more effective than
a one-off email blast trumpeting the launch of a new feature.

Naturally, it’s recommended to prioritize feature-adoption campaigns based on organic
discoverability metrics, which are quite easy to obtain by creating a segment of
_Users who never did Action X _and seeing what population of a monthly cohort that
is (spoiler alert: often a substantial %ge of users never use key features even 
once).

Even more effective than Email, In-App Messages can be deployed directly to active
non-adopters when they are in the app and can usher them (via a deep-link) immediately
to the feature to try it out.

⌊In-App Messages are the single best channel to drive awareness and adoption of 
new features ⌉⌊In-App Messages are the single best channel to drive awareness and
adoption of new features ⌉

_In-App Messages are the single best channel to drive awareness and adoption of 
new features_

Design teams often decry such ongoing feature-pushing in the app. The rationale 
is sound: ‘if the user needs to be _told_ about the feature, the app is not designed
well enough’. In a pragmatic world, this can be solved through the ‘adaptive’ characteristic
of a segmented targeting approach: only users who _have not discovered and tried
the feature organically_ (e.g. after 3 sessions in the app, or after 1 week, for
example) will ever see the in-app modal explaining the feature. If the app is designed(
or subsequently redesigned) such that everyone discovers the feature within that
window, the in-app campaign becomes redundant.

Even more effective than Email, In-App Messages can be deployed directly to active
non-adopters when they are in the app and can usher them (via a deep-link) immediately
to the feature to try it out.

CRM is less helpful in part 3 above (user finds the feature valuable / useful). 
This is beyond the scope of pure communication; for this, the feature must be implemented
in such a way as to increase the overall value of the product (for at least some
users). However, CRM _can_ play a role: educating the user about the benefits of
the feature, or highlighting great use cases from the user community can increase
understanding and interest.

Disruptive email startup [Superhuman](https://superhuman.com/) is a complex product,
with many innovative features, keyboard shortcuts to learn in the desktop app and
many gestures / actions in the mobile app. [Superhuman](https://superhuman.com/)
sends an email _every day_ in an extended onboarding series, introducing features
and explaining their use cases.

## **Re-Engagement of Lapsed or Churned Users**

Re-engagement is typically hard to do, but — with the right value proposition and
the right messaging — it’s definitely possible to bring _some_ users back to an 
app after a period of inactivity.

In order to implement re-engagement successfully, it’s important to apply as much
knowledge as possible about _why_ users lapse. This provides the opportunity to 
conduct more targeted and relevant experiments, testing hypotheses about what might
bring a user back.

The above assertion is very easy to make, but much harder to effectively execute.
Gathering information from lapsed users is tough and should always involve qualitative
as well as quantitative analysis; behavioural analytics data alone will never explain
_why_ someone falls out of love with the product. Getting in touch with lapsed users
and offering them an incentive (voucher or cash) to provide more insight in a phone
interview is a classic approach that can yield a lot of insight.

During my time leading the Retention team at SoundCloud, we were able to increase
re-activation rates 5x (albeit from a low base) by personalizing re-activation pushes
with information about the last track a user had ‘liked’ in the app. For our re-
activation strategy, we segmented users into three buckets: those who had _liked_
a track (an indication of strong preference), those who had _played_ a track (weaker
indication of preference) and those who had never liked or played a track (i.e. 
unactivated).

As with other parts of the lifecycle, segmented approaches tend to perform best 
when tackling re-activation. It’s important to differentiate the formerly-active,
lapsed users from those who never successfully activated in the first place: the
former can hopefully be tempted to return with a reminder of the value they had 
experienced in the past, whereas the latter may benefit from additional product 
education, or respond to social proof / ‘[FOMO](https://en.wikipedia.org/wiki/Fear_of_missing_out)’
messaging.

## **A word about measurement**

When seeking to increase retention, LTV or any trailing metric, it’s essential to
maintain a holdout group that is not exposed to CRM efforts, in order to understand
the aggregate impact of the program. Impact measurement probably deserves its own
followup article, so I won’t go into huge detail here, suffice to say that a long-
term holdout group is the only way to see what’s going on with a slow-moving metric
like Retention.

Individual campaign experiments will be focused on leading conversion metrics that
are hopefully inputs/drivers of retention (i.e. driving users to take certain engagement
actions within the app) and should also be run with control groups, but campaign-
level experiments will not give you a good picture of longer term retention for 
those users who are exposed to the whole set of lifecycle campaigns and activity
notifications.

Moving a metric like M1 Retention is tough: you’ll see the results of your efforts
much quicker when focusing on early-stage retention of new users (i.e. improving
activation) and it’s satisfying to experiment early in the funnel because of the
fast feedback loop between experiment and impact on e.g. D1, D3 or W0 retention.
Low opt-in rates compound the problem, since CRM may only be impacting less than
50% of the userbase: it’s worth looking at the impact on retention of opted-in users
to see if things are on the right track, but ultimately success should be judged
on retention of each entire cohort; CRM efforts need to significantly outperform
the baseline in order to shift up the average. Expectations about the absolute impact
that can be made with CRM on monthly retention typically need to moderated (read:
adjusted downward): a 1 or 2 percentage point increase over a year should be considered
a significant win in most cases. Just as teams often over-estimate their ability
to move retention metrics, there’s also a tendency to under-value modest gains: 
improving retention even by a fraction of a percentage point will deliver compound
growth and increased LTV from every new cohort.

## **Summary**

Push, In-App Messaging and Email are fantastic levers for improving retention, assuming
a decent level of product-market fit exists. Different channels will be more or 
less effective, depending on the strategic goal. In-App Messages are highly impactful
and are increasingly replacing native dialogs and prompts due to the ease of iteration
that they afford. Whether trying to increase frequency of use, drive deeper engagement
or re-activate users, investing in a mobile CRM program (and continually investing
in channel reach) is a powerful weapon in the battle to improve Retention.

I’m always keen to hear from other growth practitioners; feel encouraged to leave
a comment to let me know how you’re leveraging CRM (or other tactics) to increase
Retention and LTV.