The State of UA Automation and How it Affects UA Advertisers and Managers in 2020

WM Circle Logo

By: Wise Marketer Staff |

Posted on August 28, 2020

User acquisition has been a numbers game for a long time. Back in the old days, like 2017, the numbers were largely managed by people. All that changed in February 2018. Almost overnight, the duopoly’s algorithms evolved into something sophisticated enough to take over humans’ jobs. Google took back all control all at once at first, then dolled it back to us slowly. Facebook took the opposite approach, starting small, and has been incrementally nudging us all toward the near total UA automation we’re at now.

By: Brian Bowman, CEO of

Advancements in UA automation has had a profound effect on user acquisition advertising and user acquisition managers. We have far fewer levers left to achieve results with now than we used to have. And yes, UA automation has taken a lot of work away from us. And it will probably shrink the size of many UA teams.

But while some things are being taken away, other opportunities are opening up. Creative strategy, development, and testing actually end up being the primary driver of improvements to ROAS. Those things are still best done by humans.

The following is what UA managers should do to evolve into this very new environment, as well as elevate their level of UA automation techniques to become skillful masters. It’s an exciting time to be in user acquisition, but it demands a great deal of agility.

Advanced Testing Strategies When Resources are Limited

The best way to improve performance is to test new media buying ideas and structures, and you should be running multiple tests simultaneously. Some tests can be launched immediately, where other tests (like producing new video concepts) require time and creative resources.

Here’s a list of items you can test right now, without waiting for help from anyone else.

  • Creative: text, headlines and calls-to-action can be tested immediately without creative resources
  • Audiences: audience testing has a significant impact on performance and there are always audience tests that we can run:
    • Custom audiences
    • Lookalike audiences
    • Interest groups
    • Behaviors/Job titles
    • Demographics
    • Device type
    • Geographies
    • Facebook placements

Next Level Custom and Lookalike Audience Creation

Building custom and lookalike audiences is a constant part of audience expansion. By reaching net new users through audience expansion, you can significantly improve CPA / ROAS. Outside of creative testing, this is the most common method of significantly improving CPA / ROAS.

There is no limit to the volume of custom and lookalike audiences you can create. You can create custom audiences based off of different events like app starts, purchases, tutorial completions, revenue, etc. Here’s how:

  • For each event, can create custom audiences based off of the top 1% of users, top 10% of users, top 25% of users, etc.
  • For each event, create different custom audiences for users in the past 7 days, past 30 days, past 60 days, etc.
  • For each event and time range, target a different location like worldwide or the United States
  • For each custom audience, create lookalikes that are top 1% affinity, top 2% affinity, top 3% affinity, etc.

We see strong performance when creating a highly diverse set of custom audiences and then targeting the top 1% - 3% affinity across the various audiences. For audiences with overlap above 40%, it can be beneficial to group them in a single ad set, creating a “lookalike stack.” For lookalike audiences without high overlap, they should be tested as individual audiences as well as lookalike stacks.

Improving CPA and ROAS without Reducing Spend

The simplest way to improve CPA and/or ROAS is to reduce daily spend, as we generally see a correlation between lower daily spend and stronger CPA / ROAS. However, UA teams are generally tasked with improving CPA / ROAS without reducing spend, and the most common ways to do this are by producing new winners through creative testing, audience expansion, changes to targeting, and optimization techniques. Here’s how:

  • Creative testing: testing entirely new concepts with a different look and feel can improve ROAS massively.
  • Audience expansion: by reaching net new users from audience expansion, we are able to significantly improve performance.
  • Audience expansion through FB Analytics: in addition to leveraging Facebook Analytics to gather app insights, Facebook also allows for the creation of “non-standard” audiences through Facebook Analytics.
Changes to targeting has had a positive impact on CPA and ROAS.
  • Changes to Targeting: Changes to age, gender, location, placements and devices can all have positive impacts on CPA / ROAS and targeting tests should be run early so that future creative testing uses efficient targeting.
  • Campaign structure and optimization techniques

Facebook has rolled out a variety of new products over the past couple of years. Performance for these products is often inconsistent. Due to performance variance, these items should be tested periodically, but we can generally assume that best practices, on average, should be used as a starting point.

  • App event optimization vs Value optimization
    • Optimize towards a 1 day or 7-day post-click conversion window for AEO and VO campaigns
    • Min ROAS bids allow the advertiser to “bid” preferred ROAS percentages
    • Dynamic language optimization
    • Campaign budget optimization
    • Dynamic creative optimization
  • Optimization techniques
    • Pausing underperforming ads
    • Adjusting budgets to reduce spend from underperforming ads and shift spend to top-performing ads
    • Change bids to improve CPA / ROAS


This can be an exciting shift into UA management 2.0 if you’re agile enough to keep pace with all the changes. Instead of spending time and overhead on quantitative tasks, UA managers should pivot into creative strategy, development, and testing if they want to keep their jobs. Note that we do anticipate AI will eventually scale creative production beyond human capacity. It will eventually learn to create videos and develop copy in a greater capacity than people. But we are still years away from that reality. At least for now, creative is king, and humans can still do it best.