Mastering Customer Retention Strategy

Now we're down to the last stage of the Retention Lifecycle: resurrected users. In this chapter, you'll apply many methods you've learned and compare resurrected user behavior with current and new users.

Why resurrected user retention matters

A resurrected user has returned to your product after being inactive or dormant for some time. Resurrected users are often overlooked in retention, but offer immense potential for improving overall retention and active user count. You can potentially resurrect all of your product’s dormant users, and if you're like most companies, that's a pretty big pool.

You’ve already acquired these users—so you have a better chance of reengaging them than convincing a new prospect to try your product. Often, you can spend fewer resources resurrecting users than trying to acquire new ones.

Resurrecting inactive users can help you flatten the retention curve and increase your baseline of active users, and in some cases, even inflect the curve upward.

Don't let users come back to a poor empty experience

Think about a resurrected user’s experience: When they return to your product after a period of inactivity, what do they see? If it's an empty state with little for them to engage with, they might close the app and never return.

Here we see two examples of empty states. In the screenshot on the left, we see no messages—but there's nothing else to interact with on the screen.

On the other hand, the screenshot on the right shows a travel app. The user has no “Recents and favorites” yet, but the screen encourages them to start with a prominent call to action to “Plan a journey,” and even offers a relevant promotion.

Think of any empty state as an opportunity to engage users and get them to perform an action you care about. For example, the app on the left could improve this screen with a call to action to send a message to a friend.

Take another example from mobile gaming—Words with Friends is a popular game by Zynga in which people play a Scrabble-esque game against their friends in real-time. Users who have been inactive on Words with Friends for a prolonged period don't have any active games with their friends. So if they return to the app, they don't have anything to engage with immediately.

The Words with Friends team realized that due to this poor user experience, most resurrected users didn’t re-engage well and didn't return to the app. They decided to send push notifications to the person's friends, encouraging them to invite that user to start a new game. That way, when users returned to the app, they had game invites waiting and were likelier to start playing again.

Providing a rich, resurrected user experience is a meaningful way to encourage them to re-engage and become current users.

What you'll learn in this chapter

The overall goal of resurrected user retention analysis is to learn how you can:

1. “Resurrect” or reactivate dormant users, and
2. Get them to become current users of your product

You also want to determine whether resurrected users are an excellent potential source of product growth.

We'll answer the following questions as we cover resurrected user retention analysis. Remember these as you work through this chapter and complete your analysis:

• Are there any behavioral personas of resurrected users that differ from current users?
• Can you identify any triggers for resurrection? How do metrics like retention and conversion compare those who do and don’t receive the trigger?
• How do resurrected users compare to new and current users regarding key behaviors and revenue?
• What is the ROI of resurrecting existing users compared to acquiring new ones?

Resurrected users diagnostic

Just like you did for new and current users, take the resurrected user cohort you created in Chapter 3 and plot your baseline retention for resurrected users.

It's helpful to look at longer-term effects, at least 1-2x your product's usage interval.

How do resurrected users retain compared to other users?

You should also compare this to your current and new user retention curves, enabling you to understand how your resurrected users perform relative to these other two groups.

Real-life example: Retention of resurrected users for on-demand delivery company

In the chart below, we've added the retention curves of current and new users for the on-demand delivery company. Although resurrected users don't retain as well as current users, they retain better than new users during the same period.

Remember, you should also look at retention for your critical event, not just for “active” users who may not be doing anything valuable in your product.

The second chart shows retention during the same period but with the company's critical event, 'Checkout,' set as the returning event. You can see that resurrected users have significantly better rates of returning and placing an order than new users during the same period, even many weeks after they initially resurrect.

In this case, resurrected users retain and place orders at much higher rates than new users. This indicates that resurrecting users could be a good source for gaining more current users and increasing revenue.

Here's a different situation for a product where the retention for resurrected users is very low, even lower than for new users. This could mean that the product isn't demonstrating value to resurrected users, so people don’t re-engage and just leave the app.

The good news is that this product has solid current user retention. For a situation like this, we recommend looking at what it would take to increase resurrected user retention and weigh that effort against the potential benefit.

Focusing on improving new user retention in the short term might make more sense for smaller teams with limited time and resources.

Determine the opportunity size of resurrected users

Now that you have your baseline resurrected user retention and understand how these users retain relative to current and new users, it's time to assess whether resurrected users could be a good source of product growth. Two calculations that help you determine the opportunity size are:

• The percentage of your active users that are resurrected.
• The number of potential resurrected users.

What percentage of your active users are resurrected?

Calculate the breakdown of your active users during the period you're measuring. In Amplitude, you can do this using the Lifecycle feature. Here's a hypothetical example of active users during a week:

• 73% of the active users are current users using the app consistently. The product has a healthy user base, not new users who quickly churn.
• Nearly equal percentage of resurrected (14%) and new users (13%) indicates that the company is already successfully resurrecting users, whether organically or with targeted marketing efforts, and increasing their efforts could positively impact overall retention.

How many potential resurrected users do you have?

Next, let's look at the size of the potential resurrected user pool. Anyone who has used your product in the past but has not used it in the current analysis period is a potential resurrected user. A practical way to assess this opportunity size is to calculate the number of people who used your product sometime in the preceding six months but have not used it in the current period. Depending on your product type, usage interval, and any seasonality of your product, you may want to look at a period that's longer or shorter than six months.

In Amplitude, you can calculate this group of users with a behavioral cohort definition. Let’s suppose you're looking at the week of July 3 to 9, 2023. You would create a cohort of users who were active at any time in the last six months but were not active in the current week:

Returning to our example, this product has 1.3 million potential resurrected users. Think about this from an acquisition perspective. That’s 1.3 million people who have downloaded their app in the last six months but are currently inactive. They can re-engage them with a well-timed push notification or email. They’re much easier to reach than the potential new users that they're spending money to acquire.

Find behavioral personas of your resurrected users

Just like you did for new and current users, you should examine the behavioral personas of your resurrected users. Understanding these behavior patterns can show why users might be returning or what may have triggered their resurrection. For a refresher on behavioral personas, see Chapter 4.

Real-life example: Resurrected personas for on-demand delivery

An on-demand delivery company used Amplitude Personas to find clusters of users within their resurrected user cohort. They identified a few exciting personas listed in the table below.

The first two personas are especially encouraging—people in these personas place an order when they return to the app, and almost all remain retained two months later. Together, these personas make up 20% of resurrected users and use the product as expected when they return.

The other two personas, “Just browsers” and “Discount redeemers,” provide some interesting information.

Browsers

The “Just browsers” persona contains a lot of users, making up 21% of the resurrected user cohort. These people exhibit similar browsing behavior to “Browsers who order” but ultimately don't complete an order that day. As a group, they have pretty high 2-month retention at 74.52%, demonstrating that despite not placing an order that day, there's a high likelihood they'll return later.

Since 21% of resurrected users browse but do not order, improving the browsing experience could effectively boost resurrected user retention. If the company could convert more “Just browsers” to “Browsers who order,” not only would they get more revenue from orders on the day they resurrect, but this data shows that “Browsers who order” have much higher long-term retention as well (97% 2-month retention).

Discount redeemers

The “Discount redeemers” Persona showed several events related to redeeming an emailed discount on their next order.

Any time you're looking at the impact of discounts, you need to measure how well they incentivize users to place an order in the short term and become repeat customers moving forward. We'll look at that more in the next section.

Identify triggers of resurrection

The next step is to determine any measurable triggers of resurrection. These could be push notifications or emails that you send to your users. For example, if you already have some re-engagement campaigns targeted at users who have been inactive for some amount of time. If your product has a social component, you can base these notifications on actions from users' friends or networks, like the notification you get when someone mentions you on Twitter.

Your product might also have triggers that coincide with outside factors like holidays, sporting events, or weather. For example, you might notice users place more orders with an on-demand app during a week of heavy snow when people are less inclined to go outside to run errands. It's hard to confirm these factors in your data, but consider these outside influences when you notice spikes or dips in usage.

For resurrected users, we want to identify external triggers that brought them back to the product. Then we can measure how effectively they re-engage users and think of ways to improve.

Here are a few ways to identify triggers:

• If you have a website or web app, look at session UTM parameters and referrer data to look for common sources, like an email campaign or ad.
• If you perform a cluster analysis to determine behavioral personas, as we did in the previous section with the Personas feature, you can look for events within each cluster that could have triggered resurrection.

Analyze the paths of resurrected users using Amplitude's Journeys or a similar path visualization to explain why users return.

Once you identify potential triggers, compare downstream metrics to understand whether they have the intended effect; for example, compare critical funnel conversion rates and long-term retention for users who receive these triggers.

Real-life example: The impact of discount email offers

In the previous section, we discussed the “Discount redeemer” persona for the on-demand company. These discounts are sent via email to a subset of users who have been inactive for some amount of time.

We created a behavioral cohort of resurrected users who received the special offer, and found that 22% of all resurrected users had received a discount offer.

When we compared the critical funnel conversion rates for resurrected users who did and did not receive the special offer, we found a vast difference—94.5% of resurrected users who received a special offer completed an order, compared to only 26.5% for the rest of the resurrected users.

Almost every user who returned to the app after receiving a discount completed an order. The team also looked at the conversion rate from receiving a discount to launching the app and found that 58% of users who receive a discount offer launch the app within seven days.

The company wanted to look at the long-term impact because the special offer effectively got people to return and place an order. Do users just return one time with the special offer, or do they keep placing orders over time?

Looking at monthly retention moving forward, where the returning event is to “Complete order,” you can see that people who got the special offer retained at significantly better rates than those who did not—even many months later.

The discount program has a significant long-term effect on increasing purchases. The on-demand company decided to try expanding this program to more of their dormant users to encourage resurrection.

Notification spam doesn't work

It might be tempting to blast your inactive users with notifications or emails. But chances are these will be ineffective and only annoy your users, prompting them to unsubscribe—or worse, stop using your product forever.

Remember that external triggers, like push notifications, must be well-timed with a user's internal triggers and existing behavior. Notifications work best when they redirect existing emotions or behaviors to your product. They're even better when you can personalize them based on what you know about the user—whether it's preferences they've set or prior actions they've taken.

Compare resurrected user behavior to new and current user behavior

Once you identify triggers and behavioral personas, compare these to your current and new users. We recommend looking at long-term retention and critical funnel conversion rates. You can also measure revenue and use other methods from the Product Analysis Toolkit to help you assess the value of focusing on current users relative to other groups.

Real-life example: Compare long-term retention and critical funnel conversion rates

Continuing the on-demand company example from the previous sections, the company split resurrected users into two primary personas: Organic did not receive any email reactivation campaign, and Non-Organic received a reactivation campaign. Then they compared the retention of these two resurrected user personas to current and new user retention.

Here is the weekly retention chart, where the returning critical event is placing an order. Organic resurrected users have retention about 65% higher than new users, while non-organic resurrected users retain far better than new users—with 260% greater retention. These retention impacts are also long-term, extending 24 weeks out.

Compare critical funnel conversion rates

Comparing the critical funnel conversion rate for resurrected users to new and current users will show you whether resurrected users are helping your business goals. You can also identify any critical drop-off points for resurrected users and see what dropped-off users do instead of converting.

Here's the critical funnel comparing the same user groups during the current period. The funnel shows the conversion rate from opening the app to completing an order. Non-organic resurrected users have the highest conversion rate, at 94.6%. Organic resurrected users have a slightly lower conversion rate than new users: 28.2% compared to 33.2%.

For this company, reactivation email campaigns increase conversions during the current period and significantly impact retention and repeat orders over at least the next 24 weeks. This is a good indication that their campaigns are working, and they should explore sending campaigns to more of their dormant users.

In addition, this data shows that resurrected users have higher conversion rates and place more orders in the long term than new users, especially non-organic resurrected users.

Measure critical events and event properties

Remember, your critical event is the user action that represents that they’re using your product and getting value out of it (e.g., completing a game, placing an order, playing a song). When analyzing your resurrected users, investigate how much they perform your critical event, not just whether they return to the product.

Comparing critical events and event properties help you understand whether resurrected users have different behavioral patterns or perform these events at a different frequency than current users. This can help you determine whether:

• It's worth focusing on resurrecting more dormant users from a retention or monetization perspective.
• If there’s something unique to how resurrected users behave that you should use to tailor their experience upon return.

Compare engagement for critical events

One way to compare critical event engagement between different user cohorts is to measure the percentage of users in each cohort that executed the event. Remember also to graph any significant personas of resurrected users you've identified.

Real-life example: Critical events for a lifestyle product

The critical event for one Amplitude customer, whose product is a lifestyle app, is booking an appointment. Below you can see this critical event as a percentage of active users in each cohort. In other words, the percentage of each cohort (current, new, or resurrected) that booked an appointment each day.

Resurrected users have a lower rate of users booking an appointment compared to new and current users.

The average number of times a user performs the event is another way to look at engagement. The following graph shows a similar pattern, with resurrected users booking fewer classes on average than new and current users.

Compare important event properties

Although the number of bookings made by users is an important metric for this company, the end goal is revenue. So, they also looked at “cart total price,” an event property for their booking event.

Graphing the average cart total price for each user group, they found that resurrected users spend more than new users on average for each transaction.

Although resurrected users make fewer bookings, they spend more per transaction. This company also has a large pool of potential resurrected users. We recommend dedicating some time and resources to resurrect users.

Compare stickiness and session metrics

In addition to looking at critical event patterns and event properties, you can look at stickiness and session metrics to understand other aspects of resurrected user engagement. We covered these metrics in Chapter 4, so review those sections for more detail on measuring them.

Stickiness and session metrics are another way to compare the engagement and behaviors of your resurrected and current users. Identifying differences enables you to form hypotheses about resurrected users and find ways to get resurrected users to behave more like current ones.

We recommend doing the following analyses:

• Compare the stickiness of your critical event(s) for resurrected, new, and current users.
• If session length is important to your business, compare session length distributions and average session length for resurrected, new, and current users.

Session Metrics

Graphing the session length distributions for resurrected vs. current users lets you compare their behaviors. Similar distributions indicate that resurrected and current users behave similarly, so getting them to become current users in the long term should be easier.

Real-life example: Mediation app uses session length to measure engagement

For the meditation app, session length is a good indicator of engagement. The more time users spend in the app, the more value they get from the product.

Looking at the average session length, the team found that current users, on average, have longer sessions than resurrected users.

When looking at the distribution of session lengths, they found that resurrected users have a much higher percentage of sessions that are less than 30 seconds. A user can’t accomplish much in this app in less than 30 seconds, so we can assume they aren't using it during that time.

Current users also have a much higher percentage of sessions that last 10 minutes or longer.

This data shows that current users spend more time in the app and have longer, more meaningful sessions than resurrected users. If this company wants to re-engage resurrected users, it should improve the resurrected user experience to encourage them to behave more like current users.

Compare revenue for resurrected, current, and new users

The bottom line for most businesses is revenue. Comparing the revenue for resurrected, current, and new users will help you decide whether resurrection efforts are worthwhile for your team.

Resurrecting a user will likely cost less than acquiring a new one. So, by comparing the potential monetization of resurrected users compared to new ones, you can determine the relative ROI and decide how to spend your resources.

We recommend comparing revenue metrics like:

• ARPU: Average revenue per user.
• ARPPU: Average revenue per paying user.

In the graph below of ARPU, resurrected users spend more per user than new users during the same timeframe and spend about the same amount as current users.

The ARPPU values are more similar but still show that per paying user, resurrected users are spending more than new users and similar amounts to current users.

Take action

Remember, resurrected user retention analysis aims to learn how to reactivate dormant users and encourage them to become current product users. You also want to understand the potential value of resurrected users, especially compared to resources spent acquiring new ones.

Although not always the case, several of our customers have seen resurrected users convert and retain better than new users and contribute more revenue per user. And since you've already acquired these users, the cost to resurrect them via a push notification, email, or special offer is likely less than your new acquisition cost. You'll need to do your own analysis to ensure this is true for your business, but it's certainly worth investigating as an often-overlooked source of growth. Here are some key questions to ask yourself as you form hypotheses:

• What percentage of your active users currently come from resurrected users, and what's the potential active user growth you experience by increasing the number of resurrected users?
• How can you tailor your resurrected user experience to increase the chance they’ll re-engage and become a current user?
• Is there an opportunity to trigger more users
• to resurrect to provide an overall lift in your retention and other core metrics?
• What are effective triggers that you can experiment with for resurrecting dormant users?

Track improvement over time

Keep the goals of resurrected user retention in mind as you form your metrics:

• Trigger dormant users to become resurrected users.
• Get resurrected users to become current users.

We suggest tracking these metrics over time to measure your progress:

• The percentage of active users that come from resurrected users.
• Long-term retention of resurrected users to understand what percentage become current users. You want to avoid strategies that only result in short-term spikes in activity.
• Efficacy of re-engagement campaigns, like push notifications or emails. Keep track of open and click-through rates, and downstream metrics like retention and critical funnel conversion rate for each campaign.
• Stickiness of critical events.
• Conversion rate over time through your critical path funnel.

Use the Resurrected User Retention worksheet to take notes and keep organized.