The Importance of A/B Testing in Digital Advertising

A/B testing is one of the most powerful tools marketers have to optimise ad performance and maximise return on investment. Whether you’re running campaigns on Google Ads, LinkedIn, Facebook, or TikTok, A/B testing helps you understand what resonates most with your audience—and where to invest your budget.

What Is A/B Testing?

A/B testing (also known as split testing) involves running two or more variations of an ad, creative, or campaign element to determine which version performs better. It allows marketers to make data-driven decisions rather than relying on assumptions or past performance alone.

For example, you might test:

• Two different ad headlines
• Static vs. video creative
• A broad vs. niche audience
• Manual bidding vs. automated bidding strategies

By isolating one variable at a time, you can gain meaningful insights that improve your overall campaign performance.

Why A/B Testing Matters Across All Platforms

A/B testing in digital advertising is not limited to one platform—it’s essential across all major ad channels. What works on Meta Ads might flop on LinkedIn, and a winning Google Display ad may need tweaking to succeed on TikTok.

With each platform having its own user behaviour and ad format, testing different creatives, audiences, and bidding strategies helps you adapt your message to suit the environment and maximise engagement.

Here’s how A/B testing can improve campaigns across different dimensions:

1. Testing Creatives

Your creative assets are often the first thing users notice. Use A/B testing to evaluate:

• Imagery vs. video content
• Different calls to action (e.g., “Apply now” vs. “Learn more”)
• Alternative ad copy lengths and tones

Even small changes in creative can lead to significant performance lifts.

2. Testing Audiences

Targeting the right people is just as important as the right message. A/B test:

• Broad vs. interest-based audiences
• Lookalike audiences vs. remarketing lists
• Demographic targeting (e.g., age, location, education level)

This helps you identify which audience segments are most likely to convert.

3. Testing Bidding Strategies

Budget allocation has a huge impact on ad success. Use A/B testing to compare:

• Manual CPC vs. automated bidding
• Cost-per-conversion targets
• Daily vs. lifetime budget pacing

By understanding which bidding strategy delivers better cost efficiency, you can stretch your ad budget further.

Best Practices for Effective A/B Testing

To get the most out of your A/B testing strategy, keep these tips in mind:

• Test one variable at a time – changing too many elements makes it hard to pinpoint what caused the performance difference.
• Run tests long enough to collect statistically significant data—typically a few days to a week, depending on traffic volume.
• Monitor metrics that matter – clicks and impressions are good indicators, but conversion rates, cost per result, and ROI offer deeper insights.
• Apply learnings and retest – continuous testing ensures your campaigns keep improving over time.

Conclusion

When done correctly, A/B testing in digital advertising removes the guesswork and leads to smarter, more effective campaigns. It’s not just about finding a winning ad—it’s about building a culture of optimisation that drives sustained results.

Need help planning or managing your A/B testing strategy across platforms? At Next Level Higher Ed, we specialise in digital marketing for universities. Get in touch at hello@nextlevelhighered.com to find out how we can help your institution reach the right students, in the right places, at the right time.