Blog Lifetime value: A new way to calculate it

Lifetime value: A new way to calculate it

You're not getting LTV right.

The experts have a lot to say about the importance of Lifetime value (or LTV) and how to calculate it. It’s critical for app success. It can’t be stressed enough how important LTV is to growing a business. The ratio of LTV to customer acquisition cost (or CAC) “tells us everything” about a business’s health as it scales; CAC is out, LTV is in. LTV > CAC is so important, it’s become a mobile marketer’s go-to mantra. It’s “perhaps the most significant measure to benchmark” and conveniently one of the “easiest to figure out”...except when it isn’t. But for all of the writing out there on LTV and how to calculate it, no one’s talking about the thing that keeps you from getting accurate numbers.

Calculating LTV is harder than it looks — we know that. Yes, there’s an equation for it (LTV = ARPU [average revenue per user] x 1/Churn), but this is an oversimplification rather than a one-size-fits-all solution. There are multiple ways to calculate LTV, and they depend on key events that happen within your app — if your app’s method of monetization isn’t user-generated revenue, your method of tracking LTV will be different from, say, a subscription-based app. LTV is also a shifting, dynamic metric. As churn rate rises or falls, so does LTV — making it difficult to predict. It’s also a challenge to attribute value to individual users; they must be grouped into cohorts that accurately reflect a particular type of behavior in order for a marketer to apply their learnings to an upcoming ad campaign. But those aren’t the only reasons why your actual LTV calculations are difficult to pin down.

When you’re in your dashboard, you’re currently able to see either “installs” or “re-attributions.” Installs are users who installed your app and were never reattributed. Users who were re-attributed to a new engagement make the “re-attributions.” So if a user is part of a retargeting campaign, is served an ad and is reattributed to a new source, they’ll move over to re-attributions, along with all of their in-app activity. No matter how many sources they engage with, you’ll never see the effect this has on the LTV of their first source. If a user has been reattributed and you’d like to see their earlier sources, you’re forced to query a report and drag in user IDs, or set up callbacks in order to blend the LTV of the original source with any later re-attribution sources.

This means that it’s tough to get a sense of which clients from a particular acquisition source re-engage and are reattributed away from their original source (and conversely, those who never are). For users who are reattributed, it’s not possible to get the full picture of the LTV of their original, first source. What app marketers need is a new tool to help them understand their users’ engagement and re-engagement levels and the LTV of those first sources over the user’s actual lifetime.

We’re poised to solve this problem in a big way. Adjust wants to change how mobile marketers calculate LTV across the industry. Why are we tackling this issue? Without a clear understanding of LTV, you can’t set a marketing budget or develop retargeting campaigns aimed at higher-value users. Mobile marketers understand this - they know the power of being able to predict how much money a user ultimately spends in an app. Soon we’ll be launching a new tool that allows you to do just that. Stay tuned.

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