The Three Critical Steps To Grow Your App User Lifetime Value (LTV)

The lifetime value (LTV) of mobile app users has emerged as the most meaningful metric for evaluating the profitability of an app. In its most basic terms, LTV is the projected revenue that a user will generate during their lifetime - from the initial install to the final user interaction. Acquiring users with LTVs greater than the cost per install (CPI) is not only a strong indicator of effective mobile marketing, it is essential to the long-term success of an app.

Considering the importance of LTV, it would be ideal to have a well-established formula that’s applicable to all apps - but that’s not quite the case. The reality is that reliable LTV calculations are determined through a number of custom formulas and methodologies. In fact, organizations with multiple apps might even use a unique proprietary formula for each app when calculating LTV.

Despite the differing approaches to LTV, one component that remains consistent across all viable formulas is the reliance on post-install event data. Learning how to identify and optimize the post-install events that influence LTV enables mobile marketers to allocate ad spend more deliberately and acquire users that contribute most significantly to the financial components of their apps.

1. Identifying Relevant Post-Install Events

Identifying the post-install events most relevant to LTV is an endeavor app developers and mobile marketers may initially find challenging. The best place to start is by simply creating a list of all the post-install events you have the ability to measure (a factor which is entirely dependent on your mobile analytics provider).

A list of possible events might include:

Once this list has been established, it’s helpful to consider how each of these events relate to the following three primary LTV drivers:

Monetization: A measure of how much money a user spends over their lifetime (e.g. paid app installs, in-app purchases, or other revenue generating activities). Monetization might include calculations like:

• Average Revenue per User (ARPU)
• Average Revenue per Daily Active User (ARPDAU)
• Average Revenue per Paying User (ARPPU

Retention: A measure of user engagement (i.e. how frequently a user returns to your app). This includes the frequency of return (e.g. every day, week, month, etc.) and the duration (how long users remain in the app when they return).

Virality: The number of additional free users each user brings in through social media, word of mouth, or any other method, often measured over a specific period of time (i.e. daily, weekly, or monthly). Virality might be calculated using the K-score, a formula that factors in the number of invites a user extends, and the number of new users generated by those invites.

As an app developer or mobile marketer, you have the ability to define LTV in a way that makes the most sense for your apps. As you can see, the factors that influence LTV extend beyond just financial metrics. Including retention and virality components enables you to produce a more holistic and accurate representation of LTV (and you can also start to understand why there are so many customized approaches to the LTV calculation). Measuring the quantifiable events that correlate with the unique design, content, and audiences of your apps, will enable you to formulate meaningful LTV calculations that inform your ad spend decisions and ensure the long-term success of your apps.

2. Optimizing Events - Category Examples

The following table displays four popular app categories and relevant events that might be optimized to increase LTV:

To provide a few practical examples:

• A Gaming app might identify types of users that extend the most invites (measured by the Invite event).

• An Entertainment app that provides a streaming video service might identify types of users with relatively high streaming rates (measured by Content Viewed).

• A Lifestyle app with a retail store might use Purchase data to identify the types of users that are most likely to make in-app purchases.

• A Travel app might utilize Opens, Content Viewed, and Reservations to distinguish between users that just browse content and those that actually make reservations.

In each of these examples, post-install event data enables the mobile marketer to identify a certain behavior or user profile that directly influences the LTV of users. This knowledge can then be used by app developers and mobile marketers to ensure users with the highest LTV are acquired and retained.

3. Measuring Performance in a Single Dashboard

In order to build and maintain an active and engaged user base, modern mobile marketers utilize a number of paid and organic campaign strategies that span multiple marketing channels. Optimizing user acquisition and re-engagement campaigns based on the post-install event data is a skill that is applicable across all channels.

However, many mobile marketers have been forced to analyze and comprehend data that is dispersed across several distinct tools and dashboards. Working between multiple dashboards is not only inconvenient, it introduces opportunities for faulty data comparisons and inaccurate inferences to be made. When your data is not aggregated in a single place, you can’t make the side-by-side comparisons and data-informed decisions that enable you to accurately determine which campaigns are driving the best results.

Alternatively, when data from all your campaigns is centralized in a single dashboard, your ability to make astute comparisons and identify the partners and publishers that consistently deliver users with the highest LTV is greatly enhanced.

Key Takeaways

App developers and mobile marketers have come to realize that of the many success metrics, the lifetime value of users is the most proficient method for evaluating the profitability of an app. Acquiring users with LTVs higher than the CPI is essential to the long-term success of an app.

Despite its key role in mobile marketing, there is no industry-standard LTV calculation. In fact, it’s common for organizations to use more than one proprietary LTV formula. However, the one factor that remains consistent throughout all viable LTV calculations, is the reliance on post-install event data.

As an app developer or mobile marketer you have the ability to define LTV in a way that accounts for the unique components of your app. By compiling a list of all measurable events, and considering how each event relates to monetization, retention, or virality, mobile marketers can learn how to focus on relevant events and formulate meaningful LTV calculations that inform ad spend and produce higher-quality users.

About the author

Micah is the Vice President of Business Development and Operations at TUNE. Considered as first employee behind the MobileAppTracking product, he has contributed to the successes of becoming the standard of attribution analytics by building key client relationships and strategic mobile partnerships worldwide. Micah's story starts with a strong background in enterprise level SaaS sales, hyperlocal display advertising, performance marketing, and mobile marketing analytics. Today he is focused on identifying strategic initiatives while scaling business development and customer success teams in the US, Europe, and Asia. Micah also acts as an advisor for early stage mobile focused start-ups.