# Increasing Retention With Push, In-App & Email [Part 1]

- Link: https://phiture.com/mobilegrowthstack/increasing-mobile-retention-a4b7ffd6b4e2/
- Published: 2018-07-17T10:34:31+01:00
- Author: Andy Carvell

⌊Increasing Retention With Push, In-App & Email [Part 1] ⌉⌊Increasing Retention 
With Push, In-App & Email [Part 1] ⌉

_NOTE: This is part one of a three-part series. The second part is ‘_[_Developing a CRM strategy for increasing Retention_](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-email-part-2-458daac45d6c/)_’
The third part is ‘_[_Implementing the Strategy_](https://phiture.com/mobilegrowthstack/increasing-retention-with-push-in-app-and-email-part-3-implementing-the-strategy-b91e734cf99/)_’_

In this article, I’m sharing some practical tips on how to go about improving retention
in B2C mobile apps, employing strategic use of CRM as a lever for this improvement.

From my former role leading the Retention team at SoundCloud, I learned first-hand
how channels such as Push, Email and, particularly, in-app messages can deliver 
great impact on user engagement and retention.

After leaving SoundCloud and co-founding [Phiture](https://phiture.com/retention/),
myself and the team have been exploring the possibility of systemizing the use of
these channels and developing a repeatable playbook for [user retention](https://phiture.com/retention)
that works across different app categories. After a period of heads-down work with
clients to deliver on this goal, I felt it was time to share some of the learning
and the approach that I’ve seen works well across different types of apps and environments
with varying levels of tech and process sophistication.

Table of Contents

 * [A Quick Retention Primer](https://phiture.com/mobilegrowthstack/increasing-mobile-retention-a4b7ffd6b4e2/#a_quick_retention_primer)
 * [Engagement vs Retention](https://phiture.com/mobilegrowthstack/increasing-mobile-retention-a4b7ffd6b4e2/#engagement_vs_retention)
 * [Start with an Audit](https://phiture.com/mobilegrowthstack/increasing-mobile-retention-a4b7ffd6b4e2/#start_with_an_audit)
 * [Audit Phase 1: Tech + Data Audit](https://phiture.com/mobilegrowthstack/increasing-mobile-retention-a4b7ffd6b4e2/#audit_phase_1_tech_data_audit)
 * [Audit Phase 2: Retention + Engagement Data Analysis](https://phiture.com/mobilegrowthstack/increasing-mobile-retention-a4b7ffd6b4e2/#audit_phase_2_retention_engagement_data_analysis)
 * [Natural Usage Frequency](https://phiture.com/mobilegrowthstack/increasing-mobile-retention-a4b7ffd6b4e2/#natural_usage_frequency)
 * [Identifying Drivers of Retention](https://phiture.com/mobilegrowthstack/increasing-mobile-retention-a4b7ffd6b4e2/#identifying_drivers_of_retention)
 * [Audit Phase 3: Existing CRM (Lifecycle + Activity Notifications) Review](https://phiture.com/mobilegrowthstack/increasing-mobile-retention-a4b7ffd6b4e2/#audit_phase_3_existing_crm_lifecycle_activity_notifications_review)
 * [Coming Next: Creating a Strategic CRM Plan](https://phiture.com/mobilegrowthstack/increasing-mobile-retention-a4b7ffd6b4e2/#coming_next_creating_a_strategic_crm_plan)

## **A Quick Retention Primer**

Healthy retention is the cornerstone of growth; an increase in retention will deliver
compound returns over the long term and provide a sustainable foundation for acquisition
efforts.

⌊A Growth Accounting view demonstrates the value of healthy retention⌉⌊A Growth 
Accounting view demonstrates the value of healthy retention⌉

_A Growth Accounting view demonstrates the value of healthy retention (image adapted
from [here](https://www.slideshare.net/andyjy/data-driven-growth-amplitude-london-product-analytics-summit))_

The Engagement + Retention layer of the Mobile Growth Stack makes clear that the
key lever is Product; without a product that users find valuable, other activities
such as [lifecycle marketing](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/)
and activity notifications will not yield growth in the long run and can even be
counter-productive. However, if there is a reasonable level of Product-Market Fit,
these activities can be powerful levers for engaging and retaining users in greater
numbers.

⌊Engagement + Retention Layer⌉⌊Engagement + Retention Layer⌉

_The Engagement + Retention Layer of the Mobile Growth Stack has Product at its 
core_

User retention is a complex, trailing metric. It’s not an easy number to move, and
it can be difficult to understand why it moves when it changes. Literally *everything*
affects retention:

 * **Changes to acquisition methods**, including targeting, messaging and channels
 * **Changes to the product **itself (especially changes that are exposed to new
   user cohorts, such as the onboarding experience)
 * **Changes to the way the product is positioned** and described in the app store,
   press coverage, company website: all of these surfaces are exposed to potential
   users who form their first opinions about the product and expectations about 
   the value it can bring to them
 * **Targeted Lifecycle Marketing** Campaigns and Activity Notifications sent to
   users over channels such as push, in-app messaging and email
 * **Interactions with Customer Support** or a broader user Community

It can’t be overstated that retention begins with awareness and acquisition; if 
initial expectations — formed in the app store or from press and advertising — are
not aligned with the reality users experience in the product, those users will not
successfully activate and will churn quickly.

_Given that retention is affected by so many factors, it is of critical importance
that experiments and activities designed to improve retention are properly instrumented
with control groups and long-term holdout groups_

## **Engagement vs Retention**

Engagement and retention are inextricably linked. User retention — users returning
for another session in the app—ultimately stems from engagement (what the users 
do in that session); without meaningful engagement, users will not stick around.
Understanding the dynamics of user engagement is therefore a key goal when seeking
to understand and then to influence retention.

## **Start with an Audit**

It’s really important to get a good understanding of the current situation from 
technical, analytics, qualitative, and strategic perspectives, before diving into
activities to try to improve retention. At Phiture, we structure our retention audit
into three distinct phases:

## **Audit Phase 1: Tech + Data Audit**

In this phase, we conduct a review of the enabling [tech stack](https://phiture.com/mobilegrowthstack/the-mobile-growth-stack-tech-layer-50-tools-and-sdks-for-mobile-marketers-e65df6ba719/)
and data integrations:

![Audit Phase 1- Tech + Data Audit](https://phiture.com/wp-content/uploads/2018/
07/Audit-Phase-1-Tech-Data-Audit-min.jpeg)

The objective here is to assess the current technical capability to measure retention
and its inputs, as well as the capacity to influence retention in a measurable way
with marketing automation over push, in-app and email channels.

A quick evaluation of the current capabilities covers these areas:

 * **Deep Linking:** are there deep links implemented that would enable messaging
   campaigns to take users to every screen and feature within the app?
 * **A/B Test Framework:** Is there a solution in place to do native A/B testing
   of product and UX changes?
 * **Attribution SDK:** are we able to attribute app installs to traffic sources?(
   This is important for analyzing the impact of acquisition efforts on retention)
 * **Analytics:** are users and user behavior being tracked in a way that enables
   cohort analysis, segmentation, funnel analysis, etc. ?
 * **Marketing Automation:** If there is some kind of CRM/Marketing Automation capability
   in place (either an in-house system or — more likely — a 3rd party marketing 
   automation solution), some additional things should be reviewed:
 * Push and email **opt-in rates**: are they being measured and how do they benchmark
   against similar apps?
 * Are the **Events** (things users _do_) and **Attributes** (things we know about
   the user, sometimes referred to as ‘user properties’) that are being sent into
   the CRM system well documented and consistently named and implemented across 
   platforms (iOS, Android + possibly others such as Web App, Smartwatch or client
   applications for connected devices such as Amazon Echo or Roku boxes)?
 * Are the Events and Attributes covering **key actions within the app** and suitable
   for segmentation, targeting, triggering, and personalization of messaging?

It’s likely that some of these checks will turn up gaps in the tech stack, or in
the data integrations between some of the tools or data silos, resulting in some
homework to do to get things in better shape for measuring and influencing engagement
and retention. Things like getting deeplinks into shape or adding extra events, 
event properties and user attributes can likely run in parallel with the next phase
of the audit. If, however, there are significant gaps in analytics tracking, it 
may be necessary to rectify this situation before progressing further.

## **Audit Phase 2: Retention + Engagement Data Analysis**

This phase is all about deriving insight from the data, with the ultimate aim of
understanding the retention dynamics of the app and identifying drivers of retention.

It’s important to have a decent amount of reasonably clean usage data, stretching
back as long as possible (at least 6 months and ideally a year or more). This isn’t
always possible in a fast-moving startup environment where things get broken regularly
and when tracking is sometimes forgotten or implemented patchily. While it’s possible
to take a pragmatic approach and work with imperfect data, the insights yielded 
may be fewer and require further validation.

## **Natural Usage Frequency**

User retention strategy should be based upon a realistic expectation of usage frequency.
Only a few apps attain the status of an Instagram-like social network that commands
the attention of millions of users throughout the day and developing an understanding
of natural usage patterns will help when designing lifecycle campaigns and notifications
to reinforce — or in the best case, intensify or grow — this usage.

⌊Natural Usage Frequency for selected US mobile app categories⌉⌊Natural Usage Frequency
for selected US mobile app categories⌉

_Natural Usage Frequency for selected US mobile app categories. [Source](https://www.statista.com/statistics/739954/mobile-app-frequency-usa/)_

There will likely be different usage frequencies for different levels of engagement;
there will likely be identifiable segments (ideally mapped to psychographic personas)
that use the app in different ways, at different intensity. Analysis of the usage
data, in the best case, yields discernible engagement clusters that deliver two 
things:

 1. A _segmentation approach_ that will facilitate targeted communications to users
    of differing levels of engagement (e.g. casual users, power users, weekend users,
    etc.)
 2. A good understanding of the current maximum level of engagement within the app (
    i.e. ‘how much are power users engaging and with which features?’)

Number 2 gives a decent target to aim for when it comes to increasing engagement.
Further analysis of the differences (behavioral, demographic, acquisition source,
etc.) of users in these different clusters may yield additional insight that can
inform the strategy for increasing engagement and retention.

## **Identifying Drivers of Retention**

Next, it’s useful to look for early events that are predictive of longer-term retention.

There are a number of analytical methods that can be applied here, but the aim of
all of them is to tease out the behavioral differences (i.e. actions the user takes,
tracked as events) that differentiate highly-retained users from those that fail
to stick with the product. [Linear regression](https://en.wikipedia.org/wiki/Linear_regression)
is the most common approach to searching for relationships between one variable 
and those that are correlated to it.

In the best case, a simple linear regression demonstrates a high correlation between
one or more actions and longer-term retention of users who do these actions in their
first few sessions. In many cases, there won’t be a standout relationship, or the
data will show that (surprise, surprise) users who complete almost any action many
more times than the average user are strong candidates for being highly retained.
In other words, the most engaged users are also the most highly retained. This is
normal, so it’s important to look for ‘tipping points’ where users who complete 
a key action a certain number of times are significantly more likely to be retained
than those that complete it fewer times.[⌊Amplitude’s Compass feature⌉](http://www.amplitude.com/)

_[Amplitude](http://www.amplitude.com/)’s Compass feature (shown above) provides
reasonable out-of-the-box regression analysis. (It’s also usually possible to export
event data from other analytics setups to do this kind of analysis manually)_

There may well not be clear quantitative signals that indicate an obvious path to
higher retention. Even if the data does show that users who e.g. add 3x items to
their saved items list are higher retained, there are still the questions of whether
this is correlation or causation:

_Correlation:_ The users who do action X more times are more likely to be retained
simply because they display higher levels of engagement; they were interested enough
in the product to do the action more times.

_Causation:_ Users who complete this action experience more value from the product
and hence are more likely to continue to use it.

An increasing amount of companies are offering help with predictive analytics, including
several who are either building it into their existing analytics products or providing
it as a service.

However you perform this analysis, the important thing is to do your best to validate
your findings with qualitative research; user interviews, in-app or email surveys
and in-depth user testing are all fantastic — and typically underutilized — ways
to get a better understanding of what makes users stick around and what turns them
off. (Check out this great practical [guide to conducting such research](https://mobilegrowthstack.com/user-research-from-a-product-perspective-4d45a568b513)
by [Adeline Lee](https://medium.com/u/9b61610c9ef4?source=post_page-----a4b7ffd6b4e2----------------------)
for more help on this topic).

The insights gleaned from this analysis phase input into the Retention Strategy,
which I’ll cover in Part II of this series.

## **Audit Phase 3: Existing CRM (Lifecycle + Activity Notifications) Review**

The final phase of a Retention Audit focuses on the current status of CRM activities.
The goal is to get a good grasp of what’s being done in terms of marketing automation,
what strategy is driving these activities, and what impact they are driving.

Typically, we see companies using one of the mobile-centric marketing automation
tools for push and possibly in-app messaging and often a separate tool for email.

In practical terms, this means:

 * Reviewing any **existing lifecycle campaigns**: what are they designed to achieve?
   Where do they fit in a broader understanding of the user journey? Is impact being
   measured properly against control groups and holdouts? Assuming measurement is
   in place, what is the contribution of each campaign — and the lifecycle program
   as a whole— toward key metrics?
 * As above for any **activity notifications** (triggered by external events rather
   than user behavior)
 * Checking if there is a** consistent naming convention** and organization in the
   dashboard of whatever marketing automation tool is being used?
 * What** level of personalization** is applied? Are there opportunities to personalize
   further? (Note that personalization is a key way to improve the [relevance](https://mobilegrowthstack.com/rrf-a-framework-for-building-impactful-notifications-73c7b91c45a7)
   of messages)
 * Are all **relevant channels** (typically Push, In-App, Email, and In-App notifications
   feed / inbox) being utilized?
 * Are **Notification Badges **being used effectively? (Check out this great read
   about the [impact of notification badges](http://jwegan.com/growth-hacking/long-term-impact-badging/)
   from [John Egan](https://medium.com/u/9abd1bd21e27?source=post_page-----a4b7ffd6b4e2----------------------),
   Growth Engineering Lead at Pinterest). Do these badges lead the user back to 
   somewhere relevant in the app (e.g. a notifications inbox), or simply dump users
   back into the app?

⌊Digging into campaign performance - Localytics⌉⌊Digging into campaign performance-
Localytics⌉

_Digging into campaign performance (Source: [Localytics](https://docs.localytics.com/dashboard/messaging.html#email-measure-and-optimize))_

Finally, and crucially, what’s the process around **ideation, creation, **[**testing, iterating, and scaling**](https://mobilegrowthstack.com/scale-iterate-or-kill-f4a8e8987d4e)**
of lifecycle campaigns** and activity notifications? Is there a clear structure 
and method being applied by the team or individuals involved? Are experiments scientific
and hypothesis-driven? Is meaningful iteration occurring? Is an internal playbook
being developed that will help onboard new team members, as well as communicate 
the program goals, rationale and effectiveness throughout the broader organization.

The output of this review is a thorough understanding of the current marketing automation
program, the process in place to deliver it and the impact it’s driving. This serves
as a fantastic input into the next phase: developing a strategy to improve retention
and a prioritized tactical plan to level-up marketing automation efforts in alignment
with that strategy.

## **Coming Next: Creating a Strategic CRM Plan**

In the next article in this series, I detail [how the results of this first phase are used to develop a comprehensive action plan](https://mobilegrowthstack.com/increasing-retention-with-push-in-app-email-part-2-458daac45d6c?source=your_stories_page---------------------------).

_I’m always keen to hear from other growth practitioners; please feel encouraged
to leave suggestions or insights from your own experience in the comments section._

_Thanks to Regina Leuwer. _