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Best Practice: Pair Interest Targeting With Lookalikes For Better ROAS


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In today’s marketplace, many apps (especially games) have a short lifecycle. As a result, app marketers are tasked with aggressively scaling acquisition campaigns that don’t only hit install targets, but can deliver strong ROAS as well.

In this environment, lookalike targeting is at the core of many mobile UA campaigns. However, we’ve heard from many marketers with the most aggressive growth and ROAS targets that lookalike targeting is a necessary, but insufficient part of a good campaign due to two major limitations:

1.) Lookalike audiences dilute as you scale

We went into detail about the limitations of Facebook lookalike targeting in a previous article if you want a more in-depth look. In a nutshell, because Facebook’s ranks audience from your most qualified at 1% and descends in relevance as you scale out to the 2%, 5%, 10% and so on, your ROAS decreases as your audience grows.

2.) Lookalikes don’t translate to new markets or for new apps

If you lack the seed audience necessary to build an effective lookalike audience or you are extending into a new market, lookalike audiences don’t pack the punch you might hope fore.



Complement lookalikes with affinity-based interest targeting

By pairing lookalike targeting with an affinity-based approach to Facebook interest targeting, you can essentially create a floor for ROAS in a mobile UA campaign. This allows you to continue rapid acquisition of high value users at scale in a way that lookalike targeting alone can’t match.


How to get started


There are 3 phases to building an effective interest collection. Conquest and Intent based approaches are more traditional and rely on logic and guess and checks. These can be effective, but rely on optimizing spend after you’ve already spent money.

Affinity-based targeting, on the other hand, analyzes unstructured data to build-lookalike style audiences based on data beyond Facebook and allows you to optimize your targeting before you spend your first dollar.  


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Step 1: Build your affinity-based audience segment

There are tool-free ways you can build out Facebook interest collections for incremental scale that we touch on here. For the sake of this article, I’ll use Appnique’s Facebook UA suite to illustrate the process.

Analyze your install base

The Affinity Analysis tool looks at any app and processes a variety of signals to create high affinity audience segments that are then mapped back to Facebook precise interests for easy targeting. A good first step is to look at your existing install base and build a core audience segment based on your most active users.

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Analyze a competitor

If you are launching a new product or in a new market, analyzing the install base of a competitor is a great first step. It’s also a great tactic for adding additional scale to your audience. In the Appnique suite of tools, you can easily transition from analyzing your own app, to analyzing a competitor's in just a few clicks.

Step 2: Eliminate overlap between audience segments

To optimize your spend and raise the floor for your ROAS, make sure there is as little overlap as possible between your lookalike audience and interest-based collections that you’ve built. The Overlap Analysis tool lets you select each segment you want to analyze and visualize how much overlap exists and what your true unique reach is for a campaign.


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Step 3: Measure & optimize

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Once you’ve began running your campaign, check in on your interests to see which segments are driving the biggest returns. Invest more in the ones that are working, discover similar interests to add scale, and refresh the ones that don’t deliver.



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