MarTech Brief:
User Acquisition with Machine Learning

Hit your user acquisition targets faster and more efficiently with machine learning.

Acquiring users for mobile apps has become increasingly challenging in recent years, meaning your job as a marketer is more challenging than ever. The app marketplace has become extremely crowded, with millions of apps available for download. As a result, users have more options than ever before, making it difficult for app marketers to stand out and attract new users. 

Furthermore, many of these apps are free or low-cost, which has driven down the cost of user acquisition for some apps, but has also made it harder for marketers to justify spending more on acquiring new users.

And, of course, mobile app marketers are now facing new challenges with privacy changes that limit the amount of data they can collect about users. These limitations make it harder to personalize marketing campaigns and target specific groups of users. Moreover, with less data available, it’s increasingly difficult to optimize campaigns and maximize marketing ROI.

If you’re ready to overcome these challenges, it’s time to adopt new strategies and tools to attract and retain users. 

Read this helpful marketing tech brief to learn how machine learning can: 

  • Power today’s state-of-the-art marketing mix modeling so you can better understand your marketing channels’ effects and maximize ROI
  • Identify your best (and worst) performing campaigns — faster than ever — to make better campaign management decisions and avoid wasted spend
  • Optimize your campaigns to find more of your ideal users at a lower cost – even on iOS and despite SKAdNetwork constraints

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