Tabarak Paracha
When does it make sense to focus on LTV per user rather than ROAS?
Why is time to profitability (TTP) one of the most crucial metrics for your business?
Our CEO and Co-founder, Christopher Farm, addresses these questions and shares effective strategies for optimizing your advertising campaigns as a guest on the App Masters podcast, hosted by Steve P. Young.
A new app developer often fixates on downloads as the primary metric after launching in the App Store. While downloads can be an appealing metric to track, over time, I’ve learned that if you aim to build a sustainable app, it’s crucial to focus early on attracting users who are willing to pay.
So installs are good, because to a degree you do need users. But really you want to focus on which users monetize for you. I tend to encourage our customers to really figure out which users are the most profitable very early on.
The first question (for UA managers) is whether they can get paying users, and the second is whether they can measure the lifetime value (LTV) of those users. Lifetime Value literally means over the lifetime of a user, how much they end up generating in revenue for you. You’ll see tags on LTV such as “Day 7” which means the cohort of users that have lasted 7 days in their lifetime so far.
As you can see in the slide above, everything is cohorted by the time of the install. So if, for example, on January 1st you get 100 users, those 100 users will stay in that cohort of January 1st. So LTV is just how much money each of these cohorts generate in that period of time.
One thing you’ll notice is that LTV is always increasing as it’s a cumulative number over a period of days. The reason for the curve is usually because the users are either churning out or paying less over time. So, marginally with every day that goes by, there will be less interaction with your app. We have seen every so often the inverse where you get a linear or exponential curve which means they spend more over their lifetime. But the typical scenario in gaming is that the game tends to become less and less interesting over time. The whole goal is to figure out how to get this curve higher, whether it is through your product or marketing activities.
Consider a scenario where you ran both Campaign A and Campaign B on Meta, with Campaign B yielding a lower Return on Ad Spend (ROAS). From this, you can infer that the users acquired through Campaign A are likely a better fit for your app than those from Campaign B. This might lead you to question if Campaign A targeted a different demographic, such as males, while Campaign B targeted females. To refine your strategy, set up your campaigns to A/B test these hypotheses. By creating varied campaigns, you can target different user mindsets, helping you better understand what appeals to your audience and why they engage with your app.
ROAS is simply the ratio of LTV to spend, indicating how much revenue you’re generating compared to the cost of acquiring users. As shown in the slide above, LTV can be generated through various channels, such as in-app purchases, subscriptions, and ad revenue, while spend typically is generated from ad networks. To optimize performance, it’s essential to compare LTV data across the different ad networks where you’re allocating your budget.
In the previous slides, we’ve presented data in aggregate. However, it’s crucial to also consider metrics on a per-user basis. For example, in Campaign B above, you break even on Day 30, when your cost per install (CPI) equals the LTV Day 30 per user. In contrast, Campaign A reaches breakeven between Day 7 and Day 30, allowing you to recover your investment more quickly. This is significant because once you break even and recoup your costs, you can reinvest that money into the campaign, accelerating your growth beyond what would be possible otherwise.
Watch the video above for the full story.
