Google Shopping and Product Listings
We have adapted our optimization approach from Bayesian statistics, which allows us to calculate the bids as precisely as possible in Google Shopping. With the help of specifically developed e-commerce approach, we can perfectly combine information about product features and performance:
We collect further information from the combination of product information and its performance
As we described in the comparison of bidding for Google Shopping and Google Text Ads, information about the category, price, brand, color, and size is directly available for the calculation of the bids. We can acquire further information from these features: our algorithm detects similarities between products and forms a meaningful group depending on these features. Inside of this group, products learn from the performance of other or similar products.
Up-to-date and Dynamic: Groups are created with each bidding
To be able to act on changes anytime and to tolerate the dynamic changes, ADFERENCE checks new relationships between products on a daily basis. Newly added products profits immediately from the history of another product in the group while the products that have been dropped out of the list are excluded from the group. Changes regarding a product have a direct effect on the amount of the bid.
Optimization approach for Google Shopping is based on a product-specific campaign approach
The grouping takes place at the product level. For this reason, this approach is only available if the products are available in the detailed campaigns. In the product-specific campaigns created by ADFERENCE, the products are optimally prepared for the formation of the learning relationships.
Would you like to test ADFERENCE for Google Shopping? Please write us an e-mail or give a call. We would be really glad to talk to you the features of the ADFERENCE campaign management. The first step in optimizing of your products' ads with ADFERENCE Shopping is to create a detailed campaign structure that optimally prepares your product for grouping.