In the dynamic world of digital marketing, making data-driven decisions is essential to maximise performance. Among the extensive tools available to marketers, Google Ads Experiments is a powerful instrument for refining strategies as well as maximising ROI (Return On Investment).
Creating experiments allows marketers to make informed decisions backed by data rather than relying on intuition or assumptions. It provides insights into what works best for their specific audience and objectives, ultimately leading to more effective and efficient campaigns.
What are Google Ads Experiments?
Google Ads Experiments allow advertisers to A/B test changes within their Google Ads campaigns in a controlled environment. A/B Testing, also known as split testing, is a method used to compare two versions of a marketing asset to determine which one performs better. By randomly splitting the audience and showing each segment a different version, marketers can gather valuable insights into what resonates most with their target audience.
After relevant changes are made to the test campaign, advertisers can choose the % split of traffic assigned to the test and original campaigns. This feature enables marketers to experiment with various campaign settings, bidding strategies, ad copy, landing pages, and more, while still maintaining the original campaign running concurrently.
Once an experiment is live, marketers are able to view a comparison of the key metrics between the two campaigns.
You may notice some metrics will have reached statistical significance, which is a crucial aspect of split testing. Statistical significance indicates the likelihood that the differences observed between the control and experimental groups are not due to random chance. In simpler terms, it helps marketers determine whether the observed results are reliable and actionable.
If statistical significance has not been reached, this could be due to a variety of factors. The most common factors are the duration of the experiment, the traffic split across the campaigns, and the overall volume reaching the experiment. For a smaller account, reaching statistical significance can take a considerable amount of time.
Variables to Test
There are countless variables to potentially test via an experiment. Below are some ideas:
- Ad Copy: Experiment with different messaging, CTAs, and value propositions to determine the most compelling message.
- Bid Strategy: Compare various bidding strategies like manual CPC, target CPA, or maximize conversions to optimise campaign performance.
- Campaign & Ad Group Structure: Evaluate different campaign and ad group structures e.g. splitting exact/phrase keywords at different levels.
- Landing Page: Test different layouts, designs, and content to enhance user experience and drive a higher CVR (Conversion Rate).
- Pricing/Offer: Experiment with different pricing strategies or promotional offers across different landing pages to find the most enticing incentives for customers.
To obtain reliable and conclusive results, it is paramount to create a fair experiment. This is achieved by controlling the variables associated with an experiment and testing only one element at a time.
Ending Experiments
Once experiments have run their due course, you can choose to either apply or end the experiment. If you choose to end the experiment, the test campaign will no longer be in use and all traffic will be sent back to the original campaign. If you choose to apply the experiment, you can either update your original campaign to reflect the changes made in the test campaign, or convert the experiment into a new campaign and pause the original campaign.
It’s important to be aware that when updating the original campaign, campaign level conversion goals do not get copied from the test campaign into the original campaign. Thus, make sure to manually add the relevant campaign level goals to the original campaign if necessary.
In conclusion, Google Ads Experiments empower marketers to make data-driven decisions that drive tangible results. By embracing experimentation and continuously refining strategies based on insights, marketers can stay ahead in the competitive landscape of digital advertising.
If you want help with your A/B testing or any other aspect of Google Ads, then please contact Starlight-Digital today using the form below.
