October 10, 2018
The State (and Future) of Digital Marketplaces
In our last Mobile Engagement Crash Course, we discussed how smart brands leverage Facebook to find, target, and engage the most promising and valuable mobile users. In this chapter, we’ll discuss how mobile marketers can use product analytics to better inform their mobile engagement strategies.
Ultimately, product analytics help mobile marketers better understand users. This information is vital for shaping campaigns to establish a holistic marketing strategy that delivers a seamless and consistent experience across multiple channels. Let’s focus on two critical insights product analytics delivers for mobile marketers: discovering virtuous actions and combating churn.
There’s a baseline level of analytics that every mobile company needs to get a handle on. Justin Bauer, Head of Product at Amplitude Analytics, a mobile analytics platform, explains that these data points can be sorted into three levels. The first level is the most simplistic— “plain old counters,” like number of users and active users, number of daily and monthly active users, average revenue per user, and more.
The second level consists of conversion metrics that tell brands where their problems are. These include traditional funnel metrics covering acquisition, onboarding, conversion, social sharing, lifetime value curves, and more. The third, and highest, level enables you to identify how to improve on those conversion metrics.
Justin calls this the “behavioral layer,” and describes it as the layer between the aggregated set of actions that an individual user might perform and the higher-level representations of those actions (what a funnel represents). Mining this data through product analytics can be crucial for unearthing the guiding lights for your mobile engagement plan.
Let’s face it, the major goals for most apps are pretty clear: purchases, checkouts, social shares, or ad impressions. The behaviors, or virtuous actions, that get users to these goals aren’t so clear cut and are nearly impossible to define without the help of product analytics. Product analytics allows marketers to identify the behaviors that matter the most and build engagement strategies that nudge users toward these key actions.
Keep in mind that these virtuous actions often may not line up with your gut instinct or initial hypothesis. For example, Justin spoke of a news app that was initially convinced the best measure of future success would be the number of times a new user followed different news categories. Through its product analytics, the news app discovered users with the highest LTV were those who went deep within a single news category. Armed with this knowledge, the news app changed its onboarding flow to encourage deeper engagement within specific topics. This led to higher overall retention rates.
The Kahuna Mobile Marketing Index shows just how big of an issue churn can be for app developers; in fact, up to 90% of app users can churn without a robust engagement strategy. Marketers can lean on product analytics to find out when users churn and leverage this knowledge to shape re-engagement campaigns—we’ve covered this topic in Mobile Engagement Crash Course #5: Creating a Dormant User Strategy.
But the key to this strategy is understanding how to interpret churn data specifically for your app category. Retention rates can vary dramatically based on the type of app you have, and marketers must adjust their engagement strategies accordingly.
For example, a social gaming app may have a 30-day retention rate that’s less than 5% because of the high-attrition nature of the app category. This means mobile marketers should be focused on early monetization campaigns. By comparison, a hardcore or mid-core game should have a much higher 30-day retention rate, and the early campaigns can be geared toward deeper levels of engagement and retention.
Understanding when engagement state transitions occur is also critical to combating churn. As a user moves to a dormant or unengaged state, this behavior can trigger tailored re-engagement campaigns. Justin spoke of an app maker that was utilizing time-based triggers for winback campaigns for its entire user base but wasn’t seeing effective results.
“If you see a big drop in engagement for power users, you want to try and have a conversation with them sooner,” said Justin. “Whereas with a passive user, you may not need to reach out as quickly.”
The app maker used product analytics to segment its users by engagement state and then used those states to trigger re-engagement campaigns. If a power user wasn’t seen in seven days, the first winback campaign would go out. For engaged users, the winback campaign would be sent 14 days after they dropped off, while passive users would receive the campaign 30 days after they were last seen in the app.
Ideally, you can develop a stellar onboarding campaign that gets the user to a position where he doesn’t churn at all. While there’s a natural attrition rate for any service, a mobile engagement strategy demonstrably increases retention rates. Thanks to its understanding of user behavior, Yummly knew its most engaged users favorite at least five recipes. Yummly leveraged a personalized push notification onboarding campaign with this goal in mind, and this increased new user retention by 119%, while increasing new user conversion by 1300%.
This is the last full chapter in the Mobile Engagement Crash Course, and we hope this series has helped you get up to speed on mobile engagement and demonstrated the tactics around creating a cohesive marketing strategy for your app. We will have a full recap of the entire series shortly. Stay tuned for the roundup and a new Crash Course series just around the corner!