Effective Ad Creative Testing Strategies: How to Run A/B Tests in 2025

Erica Peacock

April 10, 2025

Marketers still rely heavily on traditional A/B testing for ad creatives—comparing two relatively similar ads side by side, deciding quickly on the “winner,” and repeating the cycle.

Over the past few years at Playbook Media, we’ve moved away from this method in driving growth for our clients.

Why? Because modern ad platforms do the testing better and faster.

Let me explain why we stopped manual testing and started trusting platform algorithms instead – and how we’re using the time we save by taking that approach.

The Machine Is Already Testing Everything

Meta, Google, and TikTok systems are testing 24/7. Every time someone scrolls past your ad—or clicks—the bidding and targeting algorithms are learning. They don’t need you to pick a winner. They’ll figure it out faster and with more input than any manual test ever could.

We’ve had clients ask if they should pause ads when performance dips, and our advice has been: Don’t touch it. Let it ride. High-performing creative will climb; weak creative will fall. That’s the whole point.

Stop Forcing Decisions That Should Emerge on Their Own

There’s a common temptation in marketing to “force” creatives that resonate with the marketing team, or micromanage things like Google sitelinks. But in these instances, data always wins over instinct.

When we try to guess what works, we get in the way. When we give the system more to work with, it prioritizes what people respond to.

Addressing Common Concerns About Automated Testing

When we discuss algorithm-driven creative selection, our clients often have understandable concerns. Let me address the most common:

“Am I losing control?”

Not at all. You’re still in charge of overall strategy, messaging, and creative concepts. Algorithms simply handle the rapid selection of which exact execution connects best with your audience.

“Will algorithms waste my budget?”

On the contrary, algorithms usually reduce wasted spending by automatically funneling budgets toward top-performing ads. They’re built to quickly stop spending on creatives that aren’t resonating. Note that this is a valid concern if the algorithms are allowed to cherry-pick low-quality users, but at Playbook we incorporate tools like CAPI and offline conversion tracking to train the algorithms to find the users who drive real bottom-funnel growth.

Quick Tips for Success with Algorithm-Driven Ad Creative Testing

Here’s what we recommend to make this process work smoothly:

Launch multiple distinct creative variations simultaneously.
Set specific performance goals and objectives.
Try to resist pausing or adjusting ads too soon; the algorithms need to serve different segments of your audience, on different days, at different times, and across different ad formats.
Monitor your results for future creative choices.

Your Job Isn’t to Choose — It’s to Diversify

Moving away from traditional A/B testing feels uncomfortable at first. But trusting platform algorithms frees up time to focus on creative strategy, diversity of messaging themes, diversity of creative media types, and bigger-picture marketing initiatives.

If you’re still manually testing two creatives against each other, consider making the shift. Letting algorithms do their job allows you to do yours even better.

Still want a guiding hand on the wheel and a partner that can feed truly differentiated creative into your campaigns? Contact our team at Playbook Media.

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About the Author

Erica Peacock

COO

Erica Peacock began her career in marketing in 2000 and has worked with hundreds of brands to both develop and execute high-performing growth strategies. After a 10+-year stint at leading performance marketing firm QuinStreet, Erica joined The DuMont Project as EVP. In 2018, she became Playbook Media’s first COO and has since spent her time developing her team and working hands-on with the agency’s clients to design, refine, and execute differentiated growth strategies.