How do you test and experiment with different extensions and formats?

1) Identify Extensions and Formats Start by familiarizing yourself with available ad extensions (like site links, callouts, and structured snippets) and ad formats (text ads, responsive search ads, image ads). Understand the purpose and benefits of each type. 2) Create Variations Develop different versions of your ads using various extensions and formats. Ensure each variation aligns with your campaign goals and target audience. 3) Implement A/B Testing Run A/B tests to compare different ad extensions or formats. Test one element at a time (e.g., compare two different callout extensions). 4) Optimize Based on Results Analyze the data from your tests to identify which extensions or formats perform best.

Choose Your Extensions and Formats: Identify the available ad extensions and formats supported by the advertising platforms you're using, such as Google Ads, Facebook Ads, or LinkedIn Ads. Consider the specific goals of your campaign and the preferences of your target audience when selecting extensions and formats. For example, if your goal is to drive website visits, you might consider using site link extensions or carousel ads.

Start by selecting the ad extensions and formats you want to test. Common extensions include site link extensions, callout extensions, structured snippet extensions, and call extensions. Consider the goals of your campaign. For example, if you want to drive phone calls, focus on call extensions.

The most crucial aspect of effective ad testing for optimizing ad performance is setting up your experiments methodically. 1/ Decide what you want to test—like increasing clicks or engagement. 2/ Pick different ad extensions (e.g., sitelinks, callouts) and formats (e.g., text ads, responsive ads). 3/ Make multiple ads, each with different extensions and formats. 4/ Ensure you can measure clicks, conversions, and other metrics for each ad. 5/ Launch the ads and let them run long enough to get enough data. 6/ See which version performs best and use that info to improve future ads.

When setting up experiments, consider employing geographic segmentation to customise your ad extensions and formats based on local preferences and performance metrics. For instance, utilise location extensions in advertisements targeting urban areas where providing driving directions and maps might increase the likelihood of a conversion. To apply this method effectively, divide your target audience into urban and rural segments, then assign different extensions to each group. Monitor and compare the performance of these extensions to identify which elements resonate best with specific demographics, thus optimising your ad impact.

Create multiple variations of your ads, each utilizing different extensions and formats. Ensure that the variations are comparable in terms of targeting, messaging, and other relevant factors. Utilize features provided by the advertising platforms to set up controlled experiments, such as A/B testing or split testing. Allocate budgets and impressions evenly across the different variations to ensure a fair comparison.

Create two versions (A and B) of your ad with different extensions or formats. Keep everything else (such as ad copy and targeting) the same. Use Google Ads’ native A/B testing features to set up your experiments. You can create experiments directly within your campaign settings

For comprehensive analysis, implement cohort analysis techniques to track how specific groups respond over time to changes in ad extensions and formats. This can reveal trends, such as increased engagement from a cohort when a new callout extension is added. Use this data to refine targeting and bidding strategies, focusing on cohorts that show the highest incremental improvements in engagement and conversions.

Analyze Your Results: Monitor the performance metrics of each ad variation closely, including click-through rates (CTR), conversion rates, cost per acquisition (CPA), and return on ad spend (ROAS). Use AI-powered analytics tools to analyze the data and identify trends or patterns in the performance of different extensions and formats.

Run both versions of your ad simultaneously to different groups within your target audience. Monitor key performance metrics, such as click-through rates (CTR), conversion rates, and cost per conversion. Use statistical significance tests to determine which version performs better.

Based on the analysis of your results, identify the extensions and formats that yield the best performance for your campaign objectives. Implement the learnings from your experiments by incorporating the most effective extensions and formats into your ongoing ad campaigns. Continuously iterate and optimize your ads based on new insights and changes in platform capabilities or audience behavior.

Once you’ve collected enough data, compare the performance of versions A and B. Identify which extensions or formats led to better results. For example, did site link extensions improve CTR or conversions? Implement the winning version’s insights into your ongoing campaigns

Here's What Else to Consider: Leverage AI-driven tools and algorithms offered by the advertising platforms to automate and optimize the selection of extensions and formats based on real-time performance data.

Audience Segmentation: Consider segmenting your audience based on demographics, devices, or locations. Test different extensions and formats for each segment. Ad Position: Test how extensions and formats perform in different ad positions (top of the page vs. bottom). Ad Scheduling: Experiment with scheduling your ads to run at specific times or days of the week. Landing Page Alignment: Ensure that the landing page experience aligns with the ad extensions. A consistent message improves user experience. Remember that A/B testing is an iterative process. Continuously test new extensions and formats to refine your ads and achieve better results over time. Good luck with your experiments!