Understanding Conversion Layers and Executing Ad Experiments
Measuring and understanding relationships between variables within a search or display ad is extremely important. An often forgotten and normally unmeasurable stat is the relationship between the different stages, or “layers,” of the paid conversion process. It is frequently difficult to measure how the variable combinations within an ad impact results at each stage of the paid conversion funnel. Experimentation and measurement of these variable changes can be conducted through multivariate testing and analysis.
In the below funnel, we place ad variables into separate stages of the paid advertising process. As you can see, different variable settings — the settings you chose when creating a search or display ad — are geared toward specific goals. The right geotargeting or keyword groups can get the right people clicking, deliver them to the right environment and ultimately get them to convert. Changing ad copy or targeting in one layer can have a drastic impact on the layers below it in the conversion funnel.
Optimizing steps 1 to 4 can be done by creating multiple ad variations and measuring the impact that each change has on the funnel as a whole. Step 5 relates to making changes to your landing page itself. Sending the right people with the correct attention and expectations to a selected purchase environment can have a drastic impact on conversion rates. These steps can be optimized before the user arrives to your site.
It’s not easy to manually conduct these layered ad experiments and the multivariate analyses that follow. In order to measure the impact of a controlled variable for a high number of ad combinations, an experimentation technology is usually required.
If you are conducting a sale or promotion, a short-term revenue burst is probably your primary goal. Most advertising teams have developed a toolbox that includes ways to grab a user’s attention through digital ads. However, getting the attention of a potential customer is not the end goal. The end goal is conversion. Understanding the core relationship between message, call-to-action and landing page conversion is absolutely vital in improving your online sales funnel. Multivariate testing is the only way to know the true relationship between all levels of your conversion process.
Message, Audience, CTA & Conversion Type
Once you have gained the attention of your potential customer, you need to instruct them. Based on who your ads are reaching and the conversion that has been set up, your call-to-action may or may not be optimal. Advertisers need to know which ad message, CTA, audience and conversion type go well together. Managing users’ expectations about online action prior to visiting the point of conversion is extremely important. Misalignment at any stage will hurt conversion rate and waste ad dollars. To truly know the relationships of the variables within the context of a single ad variation, you must conduct full-factorial testing, which creates all possible ad permutations.
Steps to Finding Your Optimal Ads and Improving ROI Over Time
There are certain steps that advertisers must follow when conducting a multivariate analysis of their advertisements. The main points are listed below, but full understanding of the Ad Optimization Lifecycle is very important.
- Establish KPIs and Set Quantified Goals
- Set Experimentation Budgets
- Create Experiments and Build Ads
- Check Parameters to Ensure Data Quality
- Deploy Experiments and Collect Results
- Analyze Statistically Significant Results
- Optimize Budgets
- Automate Insights
- Test Continuously
Need more help? Tools like AdBasis can automate this process.