We therefore set up a comparative strategy using Amazon Marketing Cloud (AMC) data:
1. Creation and isolation of the audience of individuals to be analyzed in Amazon’s Clean Room (AMC)
- On the one hand, we distinguish buyers who convert naturally thanks to performance levers from New-To-Brand brand buyers (NTBs), exposed to awareness campaigns, representing audiences that are further away from the brand.
- On the other hand, we also include the average buyers on Amazon (benchmark), for which we have reference data provided by the platform.
2. Analysis of audience membership of the different socio-demographic and consumer audiences on Amazon
This approach enables us to gain a more detailed understanding of the socio-demographic segments that convert naturally and those that require a stimulus via awareness campaigns. We also look at the buying habits of In Market audiences, reflecting the categories of interest of buyers on Amazon, applying the same strategy for the socio-demographic approach.
3. Assessing the specific characteristics of the given population in comparison with the buyer benchmark
The two types of regular and new audiences are compared with the average buyers in each category. This in-depth analysis enables us to determine a brand’s performance in certain categories. For example, if a brand wants to rejuvenate its image, this approach helps us to understand its position in this project by carefully examining the indicators for each age category, comparing the profiles of regular buyers with new buyers and the benchmark.
