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May 31, 2021

The Perks of Targeting Late Bloomers in User Acquisition

Maya Caspi
Head of Product Marketing

User acquisition (UA) is key to rapid growth. Just like a successful stock portfolio manager, effective UA leaders use a diversification strategy to reach a wide range of audiences and expand their revenue potential. For UA leaders, this often means drilling down to the value and performance of late bloomer campaigns.

First thing first... what's a late bloomer again?

Late bloomers refer to users who are more likely to make a purchase later on in their user journey. Many of them are engaged users who simply need more time to convert. For example, they may use an app for a month or two before making an in-app purchase or signing up for the paid plan.

But finding these people isn't as simple as clicking "late bloomer" on a dropdown menu.

The current UA options available on ad networks don't offer the capabilities to target late bloomers. For example, Facebook's and Google's campaign optimization engines generate audience segments based on a short conversion window. They can identify early birds(users who purchase/convert within the conversion window) but fall short when it comes to segmenting late bloomers who don’t convert quickly.

These existing solutions allow you to optimize for install and in-app events but can't help you spot users with high lifetime value (LTV.) While you could target purchase events, you'd run into high CPA that makes scaling a campaign unfeasible.

Why should you go the extra mile to reach late bloomers?

We analyzed one of our gaming customers and found that 50% of their revenue comes from late bloomers who can't be reached through current targeting solutions. If you overlook this segment in your UA strategy, you could be leaving a lot of money on the table.

Here's why targeting late bloomers is a strategy you can't afford to ignore:

  • Lower acquisition cost: The cost per install (CPI) for late bloomers is closer to that of app install (AIO) campaigns than that of purchase (AEO) campaigns, which is often higher. This is also valuable as a geo penetration and organic app-store uplift strategies, to get competitive ROAS with 3-5x the volume of users

  • Diversification opportunities: You can diversify your campaign strategy to cover a larger portion of the customer journey and, therefore, acquire new audience groups that you might have missed, and increase your scale without suffering from diminishing returns on ad spend.

  • Higher long-term Return on Ad Spend (ROAS): The graph below compares the ROAS of late bloomers vs. early birds. The ROAS of late bloomer campaigns increases over time and in some cases may surpass that of early bird campaigns. (Note: the ROAS of early birds is higher during the conversion window, which can make late bloomer campaigns seem less effective.)

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  • More purchases over time: Late bloomers start purchasing later in the customer journey. They don’t necessarily purchase more but tend to stay around longer, leading to potentially higher LTV.

  • Much more effective (3-5x less) eCPA on key engagement and k-factor (friend invites) parameters

Accounting for user LTV just got a lot easier.

How can you target late bloomers if current solutions can't help you identify this lucrative segment?

This is where predictive modeling comes in. It can help you build a user acquisition strategy based on criteria such as payback period and future ROAS to unlock new opportunities that current ad network solutions can't deliver.

AI and machine learning technologies can predict each user’s future LTV, conversion, retention, and virality to inform your targeting strategy. You can effectively automate your campaigns as you unlock the true value of your users.

For example, the predictive model that we built for our gaming customer was able to uncover additional revenue by promoting to late boomers. In fact, our customers see an average ROAS uplift of 200% thanks to our predictive models.

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