How Wave Money quadrupled installs at 12% lower CAC with Adjust

As Wave Money expanded its advertising channel diversification, the team wished to improve the efficiency of its paid media campaigns. While experimenting with a mix of platforms—such as Facebook, Google, local ad networks, and programmatic channels—the company faced difficulties in consolidating performance data from different sources for accurate analysis.

Biased attribution was significantly distorting campaign performance data. Each channel had differing definitions of an install, as well as varying tracking parameters, attribution windows, and attribution models. Additionally, text-based ads were often cannibalizing organic installs, further complicating the measurement of paid user acquisition and app conversions. These combined challenges made it difficult to accurately assess campaign effectiveness and optimize budgets. Ultimately, this was slowing the scalable, long-term growth Wave Money was striving to achieve.

Working in stages, Wave Money used a range of Adjust’s solutions to accomplish more sustainable, scalable growth:

1. To measure campaigns, mobile attribution provided the reliable, unbiased attribution that Wave Money needed. Clean data from acquisition through re-engagement campaigns allowed the team to see an accurate picture of the entire user lifecycle.
2. To analyze results, Datascape provided cross-channel insights in one report. The straightforward analysis revealed to the team that up to 35% of organic attribution was being cannibalized by a single channel when scaling campaigns. With this insight, they could optimize budgets more methodically.
3. To engage users, Audiences automated user segmentation based on in-app activity, enabling more precise targeting and cross-selling opportunities. TrueLink’s frictionless deep linking further allowed the team to deepen user engagement with seamless user journeys.

With Adjust’s data-driven approach, Wave Money scaled experimental platforms more confidently while optimizing cost per install (CPI). The company was able to:

• Increase installs by 404% through strategic scaling of experimental platforms alongside trusted channels.
• Achieve CPI 13% below projected costs.
• Lower customer acquisition cost (CAC) by 12%.
• Identify a local ad network with a 32% lower cost per registration (CPR).
• Increase marketing efficiency by 4%.