You’ve activated your new users and introduced them to your product’s engagement ladder. How do you now make sure they continue to see value over time? In this chapter, we talk more about the engagement loop and the triggers you can use to engage and re-engage your current users. We also introduce stickiness as a way to measure your loop. We round out the chapter with a special case study on how Postmates uses product analytics and timely email campaigns with Braze to re-engage their customers.
An important part of the engagement loop is the journey that new users take from signup to the first exchange of value between themselves and the product. But the journey can’t
stop there. Users have to keep finding the product engaging and invest in it for real growth to happen.
But let’s take a step back. Why do we talk about engagement and growth as a loop in the first place?
Historically, when we think about moving users from one stage to the next, we talk about funnels. In fact, when we introduced new user activation in Sections 2.1 and 2.2, we alluded to the well-known AARRR funnel framework from Dave McClure.
As a model and learning tool, this funnel is a great starting point for thinking about product growth strategy. There’s a wealth of information on how to set strategy and tactics for each stage, what metrics to track, and who should be responsible for each part of the funnel. In reality, however, the product landscape is changing so quickly that growth for most successful products doesn’t actually look like this.
According to Brian Balfour, “The fastest growing products are better represented as a system of loops, not funnels. Loops are closed systems where the inputs through some process generates more of an output that can be reinvested in the input. There are growth loops that serve different value creation including new users, returning users, defensibility, or efficiency.”
To summarize a fantastic article authored by the team at Reforge, thinking about growth as a funnel leads to a few major problems:
– Strategic silos. Funnels cause us to think about channel distribution, product development, and monetization separately when they should be considered together.
– Functional silos. As we mentioned in Chapter 2, often, certain teams “own” certain parts of the funnel and the metrics aligned to it. Problems arise when teams don’t talk to each other and optimize for only their portion of the funnel.
– One-directional thinking. Funnels don’t provide a good picture of where outputs can be reinvested back into the product.
This is why our interaction framework for engagement is based on a loop, not a funnel. As we’ll see in the next couple sections, the most powerful way to grow your user base and re-engage your current users is to create self-perpetuating loops.
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What it is: An interaction framework that describes the actions and triggers your customers experience when they use your product regularly. See Section 1.5.
When to use it: When you’re testing how users move through your product and identifying the steps at which they derive value.
Why you should use it: To understand whether your product has the right elements to drive growth and re-engagement. To make smarter product decisions that enhance the customer experience and keep users coming back.
In Chapter 1, we gave an overview of the steps of the engagement loop and why the framework is useful. Recall that the steps of the engagement loop are:
1. Curiosity: A user finds out about your product through some means, becomes curious, and signs up. This is the acquisition phase of your product.
2. Aha moment: The new user finds value in your product, usually after or during the process of onboarding in the first few sessions. Usually this ‘aha moment’ is the first rung of your product’s ladder of engagement. In Chapter 2, we explain onboarding and the aha moment as the first two phases of new user activation.
3. Value exchange: The new user makes their first investment into your product and becomes activated. In Chapter 2, we name this as the last phase of new user activation.
4. Trigger: Different kinds of triggers prompt users to come back to the product and to keep using it. Current users then become engaged in recurring value exchange—i.e., they get more value with every product use and, in turn, invest more time and money back into the product.
5. Social proof: Once users are invested sufficiently in your product, they can help promote to future customers through incentivized referrals or social media shares.
Essentially, the Engagement Loop illustrates two interrelated concepts. The Loop as a whole illustrates what needs to happen to drive real growth in new users, as we defined it in Chapter 2. And the mini feedback loop between value exchange and Trigger describes re-engagement of your current users.
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According to Sarah Tavel, currently a General Partner at Benchmark and formerly a product manager at Pinterest, sticky products create a number of virtuous loops. While most people are familiar with the network effect, growth and re-engagement can also be modeled as loops.
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Depending on what engagement game you’re playing, your engagement loop might look different. But the most important characteristic of this Loop is that there’s an input that leads to value being created which results in some output that can be fed back into the loop. Thinking about your product engagement as a loop—an interconnected system of inputs and outputs—is the foundation for building a highly engaging, sticky product.
In the next several sections we will dive into why stickiness matters for your engagement
loop, best practices to measure product stickiness, and strategies on how to make your product sticky no matter what engagement game you’re playing.
First, here are some examples of what hypothetical engagement loops might look like some of the most engaging digital products to date.
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01 | Curiosity: View a friend’s Instagram photo on Facebook
Let’s say a potential user’s curiosity is piqued by a friend’s Instagram photo that showed up on her Facebook feed. She signs up for a new account and undergoes standard onboarding.
02 | Aha moment: Share a photo
The new user then lands on the first rungs of Instagram’s ladder of engagement where she follows her friends and consumes and likes content on her feed. She finds her aha moment when she first shares her own photo.
03 | Value exchange
The new user becomes activated when the first value exchange occurs: in exchange for entertainment and relevant content, the new user provides value to the business through ad engagement.
04 | Trigger: Push notification
Instagram’s stickiness is a result of consistent, repeated value exchanges between the user and product, until the new user becomes a habitual user. These value exchanges can be triggered through external cues like a timely push notification or email.
05 | Social proof: Invite friends
Finally, once the user has invested time and energy into engaging with Instagram content—possibly rising through the rungs of the engagement ladder by leaving more comments, sharing Stories, and initiating live videos—she may invite more people with her network to join Instagram. The loop then begins again.
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Dropbox is a workspace designed for creative collaboration. It brings a user’s files together in one central location and allows them to sync those files across devices. Features like Dropbox Paper, document scanner, comments, and version history are designed to increase team productivity and decrease busy work.
01 | Curiosity: Receive a Dropbox invitation
An engagement loop for Dropbox might begin with a potential user receiving an invitation from a friend or a team they need to collaborate with.
02 | Aha moment: Upload a file
This new user signs up for a new free account, undergoes onboarding, and then lands on the first rung of Dropbox’s ladder of engagement—uploading a file—which also happens to be the product’s aha moment.
03 | Value exchange
Since Dropbox follows a freemium model, this new user may need to see value several more times and climb more rungs of the ladder before he’s activated to a paying customer. It’s important to make these free features sticky and show value as frequently as possible so that conversion happens.
04 | Triggers: Email campaigns
The new, free user may have to be nudged through email campaigns or other external triggers to set up his devices with the Dropbox app..
As this new user takes full advantage of Dropbox’s free functionalities, he may convert to a paying user to unlock more features, increase storage space, or collaborate with others. This begins a cycle of value exchanges.
05 | Social proof: Invite collaborators
Finally satisfied, a regular user of Dropbox may be incentivized to invite friends and colleagues, thus setting the whole loop in motion again.
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Some transaction players monetize entirely on habit-formation rather than infrequent purchases. Ride hailing apps, meal subscription kits, and on-demand delivery services, for example, are products that serve to fulfill a users’ regular needs—e.g., getting from point A to point B, ordering food, buying groceries. Since these transactional apps depend on frequent purchases, It makes sense for them to think about their product in terms stickiness and engagement loops.
Postmates is a on on-demand delivery service for food, groceries, and alcohol. Let’s look at the engagement loop for their product.
01 | Curiosity: Receive a promo code
An engagement loop for Postmates might begin with a potential user receiving a promo code and signing up for a new account.
02 | Aha moment: Receive first order
This user has an aha moment after placing and receiving her first order.
03 | Value exchange
The new user becomes activated when the first value exchange occurs: in exchange for the convenience of on-demand delivery, etc., the customer pays a fee. Through repeated value exchanges, some customers might climb the ladder of engagement and sign up for a Postmates Unlimited subscription.
04 | Trigger: Special delivery deals
Postmates users probably don’t come back on a daily basis—the natural cadence of ordering groceries online is more likely to be weekly than daily. Postmates may send promotional emails or push notifications with special deals on a weekly cadence to trigger a new user to place another order, thus continuing the cycle of value exchange
05 | Social proof: Invite friends
After repeated use, the new user may be incentivized through free delivery credits to reach out to her network and invite their family and friends to use Postmates. The whole loop begins again.
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If you’re in the world of product development, you’ve probably heard the phrase “sticky product”. And you probably know that in this context, “sticky” doesn’t refer to the uncomfortable physical sensation on your hands. In a product setting, “stickiness” has evolved to be synonymous with engaging or addicting. And the prevailing assumption is that stickiness in products is the goal—that anyone building products is designing them so that the customers stick around.
Well we’re here to deconstruct stickiness as a metric and a concept and correct the assumption that all products should strive to achieve maximum stickiness.
TERMS TO KNOW
Stickiness is the frequency with which a user engages with your product. Specifically, it measures the number of days out of a given time period that a user was active or completed a specific action.
As a metric, stickiness is usually defined as the ratio of daily active users to monthly active users DAU/MAU and interpreted as on average, “people use the app X
out of 30 days in a month”. This definition of stickiness first rose to prominence in social gaming, alongside the exponential growth of Facebook. Facebook itself has incredibly high stickiness—historically over 50%. By the DAU/MAU definition of stickiness, this means that the average Facebook user is using the product more than 15 out of 30 days that month. As Facebook began to tout the DAU/MAU metric, more and more consumer apps also began measuring it as a core KPI.
Certainly, building a product around which users can develop a habit is important to businesses in every vertical, regardless of the engagement game they’re playing. But measuring stickiness as # of days used per month (DAU/MAU) does not work for every product. As we’ll see in the next section, the stickiness metric is only useful if it’s defined in a way that makes sense for your business.
Before you go measure your product’s worth on monthly active users, remember that stickiness is product-specific. It relates to your product’s natural usage cadence.
Some products like Twitter and Netflix—typically attention-game players—are naturally daily-use products. It makes sense that highly engaged users come back every single day.
Other products are naturally used on a weekly, biweekly, monthly, or even quarterly basis. These are typically transactional or productivity-driven products whose usage is tightly coupled to external cycles. Think e-commerce sites, tax software, enterprise resource planning software, expense reporting software.
The first step to measure what healthy stickiness looks like for your product—and how it compares to other similar products—you need to understand how customers naturally use your product. You need to calculate your product usage interval.
TERMS TO KNOW
Your product usage interval is the frequency (daily, weekly, monthly, etc.) with which you expect people to use your product.
Your own intuition about your product will help you figure out your product’s usage interval, but if you’re unsure, we share a framework for how you can better calculate it with data in Section 3.5.
PRO TIP
Is stickiness the right metric for you? Sometimes stickiness isn’t the right measure of user engagement or delivery of product value. Make sure you know what customer pain you’re solving and the business model in place before setting your KPIs. Here are 2 examples where tracking stickiness isn’t useful:
– E-commerce: You might not always think about stickiness in terms of frequency of visit in e-commerce; wallet share is what matters more. If customers visit your site only three times a year but make high value purchases, your “stickiness” number might be low, but the value exchange is still happening. Transactional companies like Airbnb fit into this bucket as well.
– Productivity software: If users are engaging repeatedly with your product they find it valuable, right? Not always. Users of B2B accounting software, for example, desire ease and efficiency; if these customers used the product less, that would be a win.
The DAU/MAU ratio is a useful measure of engagement if your monetization depends on users seeing value on regular basis with tight engagement loops.
A major shortcoming of the DAU/MAU ratio, however, is that it masks the variability among your users. Some of your users might be slightly engaged, while others are power users, but there’s no way to tell these groups apart from a single number.
Instead of moving your DAU/MAU number through haphazard growth hacks, identifying your power users and exploring their behavior is a great place to start thinking
through a stickiness strategy. Luckily, the power user curve can help you do just that.
The power user curve—also called ‘non-cumulative stickiness’—depicts the proportion of users who were active in your product for exactly X number of days. In the example power user curve below, 17% of users were active for exactly one day out of the month; 10% of users were active for exactly 2 days; 7% of users were active for exactly 3 days, etc.
*The power user curve as depicted in Andrew Chen and Li Jin’s blog post “The Power User Curve: The best way to understand your most engaged users”*
TERMS TO KNOW
The power user curve or non-cumulative stickiness depicts the proportion of users who were active in your product for exactly X number of days.
The power user curve is a useful way to identify segments of users with different
engagement levels and understand the overall health of your product.
For products that drive value through repeat engagement, getting your curve to take the shape of a smile is a sign of healthy growth. This means that over time, you have a proportion of power users who are engaging with your product almost every single day (or whatever your ideal usage cadence is).
On the other hand, if you see your power user curve tapering off to the right, you might have to rethink your strategy. In Section 3.4, we will discuss a few fundamental questions you can ask yourself to set your engagement strategy.
But first, we’ll explore a key part of the engagement loop that drives product stickiness: triggers.
Triggers are a key way to re-engage users and nudge them to behave more like your power users. Put simply, they stimulate users to come back to your product and do something.
They play an important role in driving the cycles of value exchange for the example engagement loops we we reference in Section 3.1. The more effectively you can use triggers to help users see product value on a regular basis, the more
If you’ve read our Mastering Retention playbook, you might recall us talking about using triggers to “resurrect” inactive users (Mastering Retention, Section 7.3). This is the same deal.
In his book Hooked, behavioral designer and author Nir Eyal describes two flavors of triggers that habit-forming technologies use: external triggers and internal triggers.
1. External triggers are specific sensory stimuli that companies/products use to nudge users into taking action.
2. Internal triggers are feelings and emotions that manifest in the mind and cue users to take action on their own.
External triggers are things like push notifications, emails, ads, and referral incentives that contain a specific call-to-action. A good external trigger tells a user what they should do next—this is the stuff that marketing campaigns are made of.
Used in the right way and in the right place, external triggers can drive new user acquisition as well as re-engagement in a number of different ways. Here are a few examples of triggers and the purpose they serve.
| External trigger example | What purpose it serves |
|---|---|
| An invite from a coworker to a new Slack workspace | Acquire new users through referral |
| A mailer to a meal prep company’s current subscriber with five coupons to offer to friends | Acquire new users through referral |
| A well-designed home page with a prominent login button | Acquire new users |
| An email prompt from Dropbox encouraging you to set up syncing with one or more devices—doing so gets you more storage space | Drive new user activation |
| A tool-tip in your favorite B2B analytics product alerting you of a new feature to opt into | Drive adoption of a new feature; move user up the ladder of engagement |
| A product webinar | Drive adoption of a new feature; move user up the ladder of engagement |
You’ll notice that there are a number of different kinds of external triggers you can employ in your product. In the Section 3.4 we’ll go a little bit into how you can set up a strategy for using the right external triggers to improve your product’s stickiness and drive that cycle of value exchange.
*External trigger for new user acquisition: New Amplitude user receives an invite to collaborate with an existing user.*
*External trigger for new user activation: Email prompting a new Dropbox user to download the desktop app.*
*External trigger for new user activation: Email prompting a current Old Navy online shopper user to complete checkout.*
Internal triggers happen in the mind without external prompting. According to Eyal, an internal trigger occurs “when a product becomes tightly coupled with a thought, an emotion, or a pre-existing routine”
The stickiness of attention-grabbing social media products like Facebook, Twitter, Instagram now run almost entirely on internal triggers.
Users don’t need prompting to open up these apps—we’re cued by our emotions or thoughts, to the point that using these apps feels like a part of our natural routine. Our brains have come to crave the feeling of fulfillment and reward that accompany using these products.
Some examples of how products use internal triggers are:
– Browsing Facebook when you feel lonely
– Checking Twitter first thing in the morning after waking up
– Checking your email when you feel anxious
– Posting on Instagram when you want to capture memories
– Playing Spotify while working
Products start out with external triggers to initially attract and educate the user. Over time, as users invest more time and energy engaging with the product, it becomes a part of their lifestyle and they become a regular, committed user. Eventually, the product might become so habit-forming that users won’t need external triggers to keep them coming back.
Products that successfully develop internal triggers are ones that create value for the user continuously; with every value exchange, it becomes more stressful
for users to leave because of that loss of value they would experience. Company-wide B2B software like G Suite and Jira are great examples of this. When an entire company invests time and resources into learning the software, it becomes incredibly difficult to leave the product, even if there seems to be a better alternative. The product has successfully achieved stickiness.
“Simply, sticky products use the data a user creates while engaging with the product as fuel to make the experience even more engaging for that user (accruing benefits), and at the same time harder to leave (mounting loss).”
Sarah Tavel, “How to create a sticky product like Facebook and Evernote”
How do you know where to invest your time and money so that you get the most return on your investment while also continuing to delight your users?
Here are the questions you should ask yourself before setting your product’s stickiness or engagement strategy:
How frequently do people use your product? Ask yourself how often users should come back to see consistent value in your product. Can you justify why your product is a daily (or weekly, monthly, etc.) use product? Are you making any assumptions about your product usage? Calculate your product usage interval.
How sticky is your product now? Measure your baseline stickiness according to your product’s usage interval. If you can, benchmark your product’s stickiness against others’ in your industry or against yourself.
What does your power user curve look like? Plot the proportion of users who are active in your product every day or week over a select period of time. Does your curve ‘smile’? Does it taper off to the right? What hypotheses can you make about the shape of your curve?
Are there any early gaps in engagement? Check your signup, onboarding, and activation conversion rates for major drop-offs.
How can I make my current users behave like my power users? Dig into the behaviors and personas of your power users (more on this in Section 3.5). Do your power users take certain actions or paths, or some from certain marketing channels?
Where do your users come from? 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. Are you getting a ton of engagement from an Instagram ad or a promoted tweet? If so, it makes sense to go to where your users are and double down on paid social efforts.
What devices do your users use? Are you seeing higher engagement on mobile versus web? On iOS or Android? These differences can give you a clue as to what kinds of external triggers to test first—mobile push notifications and versus something else, for example.
Who are your users? This is the broadest but also the most important question you can ask before and during product development. Who exactly are your users? What do they are about? What pain are you solving for them? How well do you know your users today? [Take our quiz.](https://amplitude.typeform.com/to/Ey4YaE?)
You can begin to uncover user personas through interviews, surveys, and other qualitative means. You can also use a clustering algorithm on your existing user base to identify behavioral personas—groups of users who use your product and get value from it in distinctly different ways. For example, Instagram users might fall into two behavioral personas: “content creators” who upload photos and use hashtags, and “content viewers” who spend most of their time viewing others’ photos and Stories and “liking” content.
Once you’ve identified personas in your product, you can analyze which personas retain better and use the product more frequently. From there, you can begin to
think about which external triggers you can use to engage each persona or whether it might be worthwhile to try to nudge users of one persona to behave more like another.
In Section 3.5, we will outline how to find your user personas and analyze their stickiness in more detail.
What habits can you tap into? Think about where your product fits into your user’s life. Can you leverage routines or internal triggers they may already have to nudge them into re-engaging with your product? For example, if you’re a meal delivery service, sending a timely push notification about a new restaurant might bring a user to open up your app during lunchtime. We will see an example of this in our case study with Postmates and Braze at the end of this chapter.
Here in the last section of this chapter, we will cover the analyses you can perform to understand your product’s stickiness.
As you do these analyses, keep in mind that stickiness, retention, and conversion are different dimensions of understanding user engagement. Stickiness should not be examined in a vacuum; it’s part of a broader tapestry of metrics you should measure and monitor. Otherwise, it becomes too tempting to try to “game” stickiness with a ton of push notifications or clickbait emails. Also, remember that healthy stickiness depends on how often your product realistically should be used: e.g. a tax product that is used once per year vs. a meditation app that might be used daily or weekly.
Measuring stickiness involves knowing two things: who your users are and how often they do something.
To illustrate how to do the analyses, let’s go back to AmpliTunes, the example product we worked with in Chapter 1 and 2. AmpliTunes is an iTunes-like music platform that lets users play and buy songs and videos. Let’s add the following to what we know about AmpliTunes:
– product usage interval: daily
– critical event: playing a song or video
This means that we want AmpliTunes users to come the product every day and perform the ‘critical event’ they derive product value from.
TERMS TO KNOW
– A product’s critical event is an action that users take in your product that aligns closely with the value you want your product to deliver. When measuring engagement metrics like retention and stickiness, it is more valuable to look at the users who perform this critical event as your pool of “active users,” as opposed to users who do any arbitrary action.
– The critical event is also usually closely tied to the value exchange in your product.
Now let’s get into the analyses.
How often do people naturally engage with product? It’s important to know this so that you can benchmark and analyze your stickiness and retention metrics appropriately. Keep in mind that not all products are daily-use.
If your product has a daily or weekly usage interval, you should measure weekly stickiness metrics. If your product has a biweekly or monthly usage interval, you should measure monthly stickiness metrics.
Here is a simple way to determine your product usage interval in Amplitude. Here’s how you would do it for AmpliTunes.
– STEP1: Create a new Retention Analysis Chart and set the return event to AmpliTunes’ critical event Play Song or Video. This ensures that only users who came back and performed this critical event will be counted as active and retained.
– STEP 2: Switch to Usage Interval View. This view shows the percentage of users who performed the Play Song or Video event with a median frequency of ‘n’ days.
– STEP 3: Identify the inflection point of the curve. This is the usage interval
*The setup in Amplitude.*
*Usage interval curve for AmpliTunes.*
Takeaway
The usage interval curve shows that roughly 50% of users play content with a median frequency of 1 day; about 70% with a median frequency of 4 days. The usage interval of AmpliTunes is most likely around 1-4 days.
For an in-depth look at calculating the product usage interval, see Chapter 2 of our first product analytics playbook Mastering Retention.
After you’ve figured out your product usage interval, you can begin slicing the stickiness of your product or feature.
You should think about measuring stickiness in terms of:
– general usage stickiness: How many days out of a week or month did users do anything in your product?
– critical event stickiness: How many days out of a week or month did users do an action that gets to the core value of your product?
The first type of stickiness looks at the metric in terms of any kind of activity while the second type of stickiness looks at a specific, important action that you’d want highly engaged users performing in your product.
Let’s say we want to compare the stickiness of our product’s critical event across two different personas—users who engage by favoriting content and users who engage by creating new content. Let’s say we define our two personas as:
– content favoriters: users who favorite 10 or more pieces of content per month
– content creators: users who post content to the community 5 or more times per month
– STEP 1: In Amplitude, create a new Stickiness chart and choose to view the stickiness of the critical event (Play Song or Video).
– STEP 2: In addition to looking at all of your users, segment your users by those who favorited a song or video multiple times and those who posted community content multiple times within the last month.
– STEP 3: Calculate weekly cumulative stickiness. This will show the the proportion of users who did the critical event—Play Song or Video—on ‘n’ or more days per week.
Takeaway
Comparing our two personas, we see that a greater proportion of content creators play a song or video on any given number of days per week. For example, over 75% of content creators played a song or video for four or more days per week, compared to only about 60% of content favoriters. If playing content is critical to driving the value exchange cycle in your product, then a potential next step would be to think about what triggers you can use to get more users to post community content.
*The setup in Amplitude.*
*AmpliTunes weekly stickiness chart for two different user personas.*
PRO TIP
How do you figure out user personas? Figuring out your user personas is an entire playbook of its own! If you are just getting started with this important task, we recommend you read Section 4.2 of our first product analytics playbook, Mastering Retention. Here are some tips to get started:
– Start with a qualitative approach and do some user research and user testing.
– Then, follow up with a quantitative approach and segmenting your user base by different user and event properties a we did in the example in Section 3.5.2; you can then bucket users based on the frequency at which they perform key events.
– Alternatively, you can use a clustering algorithm like Amplitude’s Personas feature.
Looking at the stickiness of different personas is useful if your product has multiple distinct ways of delivering value. You can also look at stickiness of certain user cohorts:
– behavioral cohorts: Are certain behaviors correlated with higher stickiness?
– acquisition date cohorts: Did a feature launch or marketing campaign affect general or critical event stickiness?
In Section 3.2, we talked about how your cohort of power users can help you better understand and set stickiness strategy. In Amplitude, you can build power user curve by viewing non-cumulative stickiness.
Let’s say we want to understand the behaviors that are characteristic of AmpliTunes power users. We’ll define power users as people who play a song or video almost every single day of the month.
– STEP 1: Create a new Stickiness chart and choose to view the stickiness of the critical event.
– STEP 2: Calculate weekly non-cumulative stickiness. This will show the proportion of users who played a song or video on exactly ‘n’ days of the month.
Takeaway
Note that there’s a slight “smile” to this curve because of the uptick at around 20 days. This means there is a small, but highly engaged proportion of users who are coming back everyday for roughly 20 days to play content in AmpliTunes. The next step would be to figure out what these power users are doing differently from other users, so you can drive more users to act like them.
*The setup in Amplitude.*
*Non-cumulative stickiness for users who play content.*
To contrast cumulative and non-cumulative stickiness analysis:
| Cumulative stickiness | Non-cumulative stickiness |
|---|---|
| AKA “Nth-day stickiness” | AKA “power user curve” |
| Shows you the proportion of users who were active for ‘n’ or more days. | Shows you the proportion of users who were active for exactly ‘n’ days. |
| Example: For a daily-use product Day 3 weekly stickiness shows you the proportion of users who were active on three or more days per week. | Example: For a daily-use product, Day 3 weekly stickiness shows you the proportion of users who were active on exactly three days per week. |
One way to develop stickiness strategy is to hypothesize what your power users do differently than other users. You can do this through qualitative research and path analysis of specific user groups. (We mentioned these analyses in Chapter 2 in the context of new user onboarding and activation; they can also be applied here.)
Once you’ve created a power user curve in Amplitude, you can build a cohort of users straight from the stickiness chart. Use Amplitude’s Cohort Comparison tool quickly see what the differences are between your “Power Users” cohort and your “Active Users” cohort.
Takeaway
Cohort Comparison shows you the proportion of users in each cohort who perform certain actions in your product. It’s a good way to easily spot differences between cohorts and begin to develop hypotheses about their behavior. In this example, you can see that 4x as many power users added friends or posted community content than other active users. You might then begin digging into whether it’s worth revamping AmpliTunes’ social features—making them more visible might make more users behave like power users.
*Saving your cohort of power users.*
*Comparing ‘power user’ and ‘active user’ cohorts.*
To review, we began this chapter by revisiting the engagement loop framework in the context of each of the three engagement games—attention, transaction, and productivity. We then zoomed into the value exchange <> trigger steps of the loop and specifically discussed engagement in terms of stickiness.
Next, we discussed external and internal triggers that help propel users through the engagement loop and put them in context of a larger strategy to increase product stickiness. Finally, we ended the chapter with analyses you can do to measure stickiness in Amplitude.
Before wrapping up this chapter, take a moment now to reflect on your learnings. Consider the following:
– Draw out an example engagement loop for your product. What is the value exchange?
– What external triggers do you use? What internal triggers might exist?
– How frequently do people use your product?
– How sticky is your product overall? How sticky is your product’s critical event?
– Review the questions in Section 3.4.
See it in action
In the last part of this chapter, we share a case study from our customer Postmates and integration partner, Braze. The Postmates team was able to build an effective stickiness strategy with a unique external trigger using Amplitude and Braze. If you want to know what tools you should have in your engagement stack to improve engagement like Postmates, that’s coming up in our final chapter.
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DAU/MAU is an important metric to measure engagement, but here’s where it fails
Andrew Chen, General Partner at Andreessen Horowitz
The Power User Curve: The best way to understand your most engaged users
Andrew Chen, General Partner at Andreessen Horowitz
The Hierarchy of Engagement, expanded
Sarah Tavel, General Partner at Benchmark
Growth loops are the new funnels
Brian Balfour, Founder/CEO at Reforge
Engagement drives stickiness drives retention drives growth
Data Science Team at Sequoia Capital
Two-sided marketplaces and engagement
Data Science Team at Sequoia Capital
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CASE STUDY
Postmates is transforming the way goods move around cities. Their core product offering is a web and mobile platform that connects customers with couriers who offer delivery from local businesses in just minutes.
Postmates’ product North Stars are centered around making local inventory easily accessible to everyone. One way the Growth Marketing team supports these metrics is by making Postmates more sticky. The team has to figure out how to develop the right kind of triggers to help users repeatedly see the value of their platform, while also maintaining an impeccable customer experience.
According to data from Braze, users who receive messages from brands using a single channel (either email, push, or in-app messages only) saw average engagement levels that were 179% higher than users who received no messages at all. That means an email, push, or in-app message could be the difference between a lapsing user and an actively engaged customer.
Knowing this, Postmates sought a versatile engagement platform that could help them increase customer stickiness, build loyalty, and increase LTV through omni-channel messaging. And, just as importantly, they needed a way to measure how their customers were behaving in response to those messaging campaigns.
“You can make small incremental changes in messaging but the more transformative result
comes from better understanding your customer experience, and augmenting your product and marketing to work together, as opposed to doing both of those independently,” said Andrew Touchstone, Director of Growth Marketing at Postmates. “With Braze and Amplitude, we were able to bring marketing and product a lot closer together.”
A stand-out example of product and marketing at Postmates working hand-in-hand to drive customer engagement was their campaign with ABC’s The Bachelorette.
During this campaign, Postmates used Braze to deliver different types of “Bachelorette experiences” to their customers.
Postmates partnered with The Bachelorette to bring viewers free delivery for one night only. They launched the promotion via emails and social media posts including:
“Before the drama unfolds, open the Postmates app at 5 PM and look for your code. Then order in an epic viewing party and enjoy free delivery.”
“Then, share your order with us on social with #TheBachelorette and @Postmates for a chance to win 1 year of free Postmates! (Rules).”
The Postmates team used Amplitude to analyze resulting customer behavior, and Braze to make real-time campaign optimizations on the fly.
Touchstone, former Director of Growth at Postmates, described the Bachelorette campaign as a “product-based experiment to a marketing experiment.”
“We were testing how this messaging and this new product experience worked
together,” he said. “In Amplitude, we could view which experiment a customer was in, which marketing message they received, and how that changed their behavior downstream.”
Monitoring their campaign in real-time helped Postmates use their marketing
budget for this campaign far more effectively. Their behavioral insights from Amplitude helped them answer where in the campaign they needed more communication and which variants were resulting in the highest conversions. Braze then allowed them to iterate on their messaging in real-time, driving more effective customer engagement.
