# App Lifecycle Marketing 101

- Link: https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/
- Published: 2017-02-04T17:01:31+01:00
- Author: Andy Carvell

![Lifecycle Marketing 101 ](https://phiture.com/wp-content/uploads/2017/02/Lifecycle-
Marketing-101-min.png)

In this post, I’ll give a short introduction to the huge topic of lifecycle marketing
and discuss how to build a lifecycle marketing program from scratch.

#### **What Exactly Is Lifecycle Marketing?**

The term _lifecycle_ refers to the stages a user goes through as they interact with
a product over time. This is sometimes referred to as the _user journey_.

Every user experiences the product in their own way and form their own opinions 
about its value to them. Some people will become loyal, regular users while others
will abandon the product after trying it just once. Some users will become paying
customers, invite their friends to try out the product, or perform other valuable
actions, while others will become dormant. In an ideal world, as many users as possible
will have a great experience with the app and continue on the journey towards being
valuable, engaged users.

Lifecycle _Marketing_ refers to activities that provide targeted interactions with
users to help them through the stages of their lifecycle, typically employing some
combination of channels such as email, push notifications, and mobile in-app messages.
In some scenarios, other channels such as SMS, chatbots, re-targeting the user in
other apps, etc. also prove effective.

A lifecycle marketing program can be built up in stages. Typically the steps involved
would be:

 1. Mapping out the ideal user journey(s)
 2. Defining an initial set of hypotheses that can be tested with lifecycle campaigns
    aimed at nudging them along the way towards the ideal user journey with well-timed
    messaging
 3. Identifying users who are at specific points in their user journey
 4. Delivering the campaigns to these users and measuring the results
 5. Refining your understanding of the user journey by iterating on campaigns as hypotheses
    are proven / disproven by the results.
 6. Experiment with new campaigns to keep building engagement

> Start simple, and improve iteratively

Lifecycle marketing is an ongoing process of refinement. It’s advisable to go step
by step when setting up and testing initial campaigns, rather than trying to implement
a full set of interactions from the outset; many initial assumptions about the best
way to influence user behavior will be wrong and many elements of each campaign (
copy, timing, segmentation, choice of channel) will have plenty of room for improvement.

Table of Contents

 * [Mapping Out The Ideal User Journey](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#mapping_out_the_ideal_user_journey)
 * [Defining Initial Hypotheses And Campaigns To Test Them](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#defining_initial_hypotheses_and_campaigns_to_test_them)
 * [Consider Reach: Start At The Beginning Of The User Journey](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#consider_reach_start_at_the_beginning_of_the_user_journey)
 * [Setting Up The First Test Campaign](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#setting_up_the_first_test_campaign)
 * [Defining The Audience Segment](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#defining_the_audience_segment)
 * [Defining Initial Channel(S)](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#defining_initial_channels)
 * [Defining Initial Messaging: Format, Creative & Copy Variants](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#defining_initial_messaging_format_creative_copy_variants)
 * [Instrumentation For The Test](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#instrumentation_for_the_test)
 * [Running The Test](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#running_the_test)
 * [Watch Out For Negative Side-Effects](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#watch_out_for_negative_side-effects)
 * [Next Steps](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#next_steps)
 * [Some Strong Examples Of Lifecycle Campaigns](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#some_strong_examples_of_lifecycle_campaigns)
 * [Summary](https://phiture.com/mobilegrowthstack/lifecycle-marketing-101-21e874be642f/#summary)

## **Mapping Out The Ideal User Journey**

Although each user is unique, the product developer should have a clear idea of 
what constitutes an _ideal user journey_. There may be more than one type of ideal
user and hence more than one ideal user journey. For example, in a marketplace, 
there are buyers and sellers, both critical to the ecosystem but with radically 
different characteristics and engagement patterns. In this case, there would be 
at least two ideal user journeys: one for the ideal buyer and one for the ideal 
seller.

Developing a realistic understanding of an ideal user journey is different from 
simply imagining what a hypothetical perfect user would do. Careful analysis of 
real user behavior will lead to a deeper understanding of what differentiates valuable,
engaged users from disengaged or churning users. Even before the product is live
with real users, observation of test subjects via qualitative user testing can help
to identify key points in a successful user experience, as well as key stumbling
blocks or areas of confusion that might be improved through product changes or lifecycle
communications. Mapping out the user journey ahead of time also helps identify which
events and user attributes should be tracked in the analytics/marketing stack. Once
the product is live, analytics data provides a wealth of information about user 
behavior that can be analyzed to better understand what constitutes the ideal user
journey.

It’s helpful to break the user journey down into distinct stages or milestones. 
Here’s a hypothetical example for a fictional app, GenericApp, in which users can
browse, bookmark and watch video content, with the option to purchase various upgrades(
such as the ability to download videos for offline watching, remove advertising,
etc.) in the form of in-app purchases.

#### **User journey: key milestones**

![User Journey- key milestones](https://phiture.com/wp-content/uploads/2017/02/User-
Journey-key-milestones-min.png)

These milestones reflect a pretty ideal situation for the fictional app developer;
it’s likely a user that achieved all of these things in their first 30 days would
have had a positive experience with the app and return for more sessions (and possibly
purchases) throughout their lifetime. Even if they churn, they will have delivered
some value from the IAP. It should be noted that it’s not reasonable to expect a
high percentage of users to make purchases… in games, for example, it’s typically
5% or less of users that can be successfully monetized through IAP.

While not all users will make it through this engagement funnel or may take differing
amounts of time to reach certain milestones, it’s still useful to have the ideal
user journey as a target and to understand which actions within the app deliver 
value (either monetarily or because they are good predictors of higher retention).
While these milestones would ideally be informed by some strong data analysis (e.
g. running a regression to see which actions are the best predictors of retention/
monetization), there is value in setting and optimizing toward targets (e.g. 10x
video views in the first week) even if they are not scientifically derived.

The milestones themselves — and the methods used to nudge users towards them — will
evolve over time as a greater understanding of user behavior and mindset at each
stage of the funnel is achieved, through testing hypotheses either through A/B tests
on campaigns, polling/surveying users, or through further user testing. It’s better
to start somewhere with clear — if imperfect — goals, than just fire out emails 
and push notifications with a nonspecific goal of increasing engagement.

## **Defining Initial Hypotheses And Campaigns To Test Them**

Now that the ideal user journey is mapped out, the fun begins: what campaigns might
help users hit the milestones defined?

## **Consider Reach: Start At The Beginning Of The User Journey**

When starting from scratch, it’s highly advisable to focus on the new user experience(
i.e. the start of the user journey), since this is where [the majority of users will drop off and churn](http://andrewchen.co/new-data-shows-why-losing-80-of-your-mobile-users-is-normal-and-that-the-best-apps-do-much-better/).
A campaign aimed at increasing conversion to in-app purchases may deliver monetary
value, but the _reach_ of such a campaign will be several orders of magnitude smaller
than an onboarding campaign targeting new users. Firstly improving _new user retention_
will, over time, increase the audience for monetization-based campaigns further 
down the funnel, as well as delivering compound growth in the userbase.

In the hypothetical user journey of our fictional video app, some initial milestones
include completing the interactive tutorial (which hopefully gives the user a better
sense of what the product is about and how to use it), discovering and watching 
at least one video (hopefully enjoying it), and [registering for an account](http://www.mobilegrowthstack.com/engagement-retention/user-accounts-retention-engagement/).

Since this fictional app does not force a user to create an account before trying
out the app, it’s important to note that until the user completes this step, their
_email address_ is not yet collected, and hence email as a channel is not available.
Since this channel could magnify the impact of future lifecycle campaigns, it’s 
a great idea to drive as many people to create accounts early on with the channels
available.

A set of initial hypotheses might look something like this:

![initial hypotheses](https://phiture.com/wp-content/uploads/2017/02/initial-hypotheses-
min.png)

With just these three basic hypotheses, there are plenty of options for initial 
test campaigns and variants.

Each of these hypotheses could fairly swiftly be tested with a push notification(
for users outside of the app), an in-app message (for users who return to the app
for another session), or a combination (i.e. use a push to bring users back to the
app, then show all relevant users — whether pushed or not — the in-app message on
their next session). In-app messages are great, because they don’t require opt-in
from the user (unlike push), but they only work for users already in the app.

## **Setting Up The First Test Campaign**

It’s useful to test just one thing at a time and — if a hypothesis has been proven—
invest in further rounds of testing to improve results. Considering the overall 
reach of each channel, I would start with an in-app message (reaches 100% of target
audience on their next in-app session), prompting users to return to the tutorial
with a call to action that triggers the tutorial to restart/resume via a deep-link.

If the in-app message is driving more users to the conversion goal (and hence proving
the high-level hypothesis), it could likely be improved further with a push notification
for users who haven’t yet seen the in-app to bring them back in, but this could 
be a stage 2 optimization.

## **Defining The Audience Segment**

The target audience segment for the first milestone is relatively straightforward:
_all users who haven’t completed the tutorial (and haven’t yet watched a video)._
The bracketed clause is in place to avoid spamming users who are already engaging
despite not completing the tutorial. Targeting criteria are valid parameters to 
test, of course, so shouldn’t be assumed to be perfect on the first run.

## **Defining Initial Channel(S)**

In this example, to keep it simple, I’m going with an _in-app message_. If this 
doesn’t outperform the control group, we could test other channels, or declare the
hypothesis disproved and move on to a new idea.

## **Defining Initial Messaging: Format, Creative & Copy Variants**

In this step, an initial variant or variants should be created of what the user 
would be shown. In the case of push notifications, this might be as simple as one
line of short text. For emails or in-app messages, more visual formatting options
are available.

> Multivariate tests increase the pace of iteration towards a conclusion regarding
> the hypothesis.

Given that the initial objective is to test the hypothesis, it can be argued that
keeping things as simple as possible is best. That being said, if there are enough
new users in each daily cohort that a statistically significant multivariate test
could be conducted in a reasonable timeframe, testing multiple variants of the copy
or design (but not both at the same time!) provides more chances for the hypothesis
to be proved by one or more of the variants, and could indicate a clear winner that
would provide a direction for further optimization. If just one variant is tested
and does not perform, the team will need to decide whether this was down to using
the wrong messaging (and hence deserves another round of testing), or that the hypothesis
is clearly false i.e. _whether the main hypothesis was false, or whether the approach
used was the wrong one to prove the hypothesis._

Even in our example in-app message, there are multiple variables that could be tested:

 * Design
 * Copy
 * Call-to-Action (CTA)

For a first iteration, I would advocate keeping things relatively simple and testing
1–4 copy variants, with a single fixed design / out-of-the-box template. If none
of the variants outperformed the control group (a holdout group that does not receive
the message at all), I might test a couple of different CTAs or designs. If the 
second round still fails to significantly out-perform the control, it’s probably
time to declare the hypothesis disproved and think about a new way to increase tutorial
completion (including product-based options such as forcing users to complete the
tutorial before continuing).

## **Instrumentation For The Test**

Before running any variants of the test, measurement needs to be in place to accurately
identify and count the users served each test variant and the control group (who
are not served a message). In addition, it must be possible to discern whether a
user converted (in this case, completed the tutorial), by ensuring that the conversion
event is tracked. Note that using a control group allows post-facto analysis of 
many different behavioral factors, including checking whether the test group were
more likely to complete a specific action, were better retained, etc.

Mobile Marketing Automation frameworks massively simplify this task,but it’s perfectly
possible to set up this instrumentation around campaigns internally using engineering
work. The important thing is that everything is tracked and that new campaigns and
test variants can be quickly configured, enabling rapid iteration.

## **Running The Test**

The test should be run for long enough to generate a statistically significant result.
If the result is positive (i.e. one or more variants outperforms the control), it
would be advisable to put the winning variant into production (i.e. serving it constantly
to new users who qualify for the target segment) so that it’s delivering impact 
while a new test is being devised.

## **Watch Out For Negative Side-Effects**

Note that the risk of over-communicating with the user increases with every new 
campaign created… there is a risk of diminishing returns and of user abandonment
or opt-outs whenever a user is contacted in a way that they deem intrusive or unnecessary.

Keeping an eye on potential negative influences on metrics such as opt-in rates (
for push and email), user complaints via customer service, and user churn will help
identify when users are being over-communicated with. However, most firms start 
out with too cautious an approach here; let the data inform any decision to scale
back lifecycle comms, rather than anecdotal evidence or fear. Above all, ensure 
that lifecycle campaigns are well targeted (i.e. relevant) and valuable to the user,
as evidenced by subsequent increased engagement.

## **Next Steps**

If the hypothesis was proved and a lifecycle campaign has been shown to increase
impact / get more users to complete a milestone, it’s likely that further optimizations
can be made by experimenting with:

 * Timing
 * Targeting
 * Copy & Creative
 * Channel mix

The upside of running further experiments will need to be weighed carefully against
the opportunity to create new campaigns for other lifecycle stages or milestones.
The team should also be open to the possibility that they are optimizing for a local
maxima when a bigger win could be achieved with a radically different approach (
e.g. removing the tutorial altogether and providing suggested content in the app
on the very first screen).

Lifecycle campaigns are limited only by your creativity and — in certain cases —
the level of technical integration required to insert or aggregate dynamic and personalized
content. Lifecycle marketing can be used to drive regular engagement, to re-activate
users who have stopped using the product, to advertise special offers, promote seasonal
content, inform users about new features… the list is endless!

## **Some Strong Examples Of Lifecycle Campaigns**󠀁[⌊Goodreads compliments its in-app onboarding with a welcome email⌉](https://www.goodreads.com/)󠁿

[_Goodreads_](https://www.goodreads.com/)_ compliments its in-app onboarding with
a welcome email._

[⌊Endomondo delivers monthly digest emails to remind and encourage users to keep
tracking their workouts⌉⌊Endomondo delivers monthly digest emails to remind and 
encourage users to keep tracking their workouts⌉[

[_Endomondo_](https://www.endomondo.com/)_ delivers monthly ‘digest’ emails to remind&
encourage users to keep tracking their workouts._

⌊a new feature announcement from twitter⌉⌊a new feature announcement from twitter⌉

_A new feature announcement from Twitter._

⌊a tinder push notification re-activates users by playing on FOMO⌉⌊a tinder push
notification re-activates users by playing on FOMO⌉

_A _[_Tinder_](https://www.gotinder.com/)_ push notification re-activates users 
by playing on FOMO (Fear of Missing Out) psychology._

[⌊iHeartRadio uses a modal in-app message to run a promotion⌉⌊iHeartRadio uses a
modal in-app message to run a promotion⌉[

[_iHeartRadio_](https://www.iheart.com/)_ uses a modal in-app message to run a promotion._

## **Summary**

This article scratches the surface of what it takes to build and operate a successful
lifecycle marketing program. A strong program will start with a good understanding
of and empathy with the typical user as they interact with the product at increasing
levels of fluency and engagement. While mobile marketing automation frameworks can
save a great deal of time & effort when building out a lifecycle marketing program,
the tools used are not as essential as the methodology practiced and a meticulous
focus on impact.

When implementing a lifecycle program, consider the reach of each campaign (onboarding
has more upside than anything that comes later, when many users have already churned)
and the mix of channels that could be used to deliver the message. As with any growth
activity, ensure the correct instrumentation is in place to measure the impact of
campaigns, be ready to iterate towards greater impact and keep an eye on opt-in 
rates.

In future articles, I will cover some specifics of the channels available to mobile
marketers, dive deeper into campaign measurement, and explain how to implement a
personalized activity notification system. If you have specific requests or questions,
please let me know by leaving a comment in the section below.
