The 4 best practices of A/B testing

The 4 best practices of A/B testing

Google Ads gives advertisers the ability to make changes on the fly. Improvements can elevate return on investment of the ads. A/B testing, which is synonymous with digital marketing Canberra-wide, exemplifies the versatility and dynamism of marketing communication in the digital age. However, you need to know how to make it work. All the data available is meaningless unless it is appropriately used. In this post, we discuss the pillars of effective A/B testing.

1. Know the problem to be solved

All ads are designed to feature solutions to problems people face, B2B or B2C. Unless you know what they are, even the best-written ad copy or most creative ad will not trigger interest and intent to buy. With the benefit of knowing the problem to be solved, in A/B testing you will be evaluating the best copy and other features of the ad that drives success.

2. A/B testing isn't about testing guesses

There is a tendency to throw everything into the ring to identify the winner. Some are nothing more than guesses or attempts to emulate other brands' success. This isn't only ineffective use of A/B testing but also ineffective use of resources. Variables to be tested must be valid assumptions relevant to your category, goals or emerging trends in marketing communication.

3. Have a clear KPI

This may seem obvious. Unfortunately, not every A/B test sets out with a clear KPI. Like in all advertising, success is measured by what you have aimed for the ad to achieve. Not all ads are designed to drive conversion or sales. Some may be to drive awareness, others to educate consumers. Be clear of your KPI before you undertake A/B testing.

4. Document the results

Again, this seems obvious but is often overlooked. Without proper documentation of the results, it makes the task of comparing outcomes almost impossible. From a simple worksheet to more sophisticated ways of tabulating results, document them.

Being able to change the features of your ads mid-flight is great. In A/B testing, the changes will take you closer to your desired outcome. Let us show you how. Connect here.

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