One of many things Feedonomics enables you to do is easily write rules to parse, include, re-arrange meta data in titles. You can even then see the results of the optimizations through large performance gains.
Now Feedonomics lets you A/B test different titles for engines like Google Shopping, Bing Shopping, and many more!
The process to A/B test different product titles is as follows:
1) First choose a sub-selection of products
This sub-selection can even be all products if desired.
An example would be choosing products where the brand is equal to Black & Decker:
[brand] equal ‘Black & Decker’
2) Write the split test
The unique_id() function will give us a hex string starting with 1-9 or A-F, or 16 possibilities. So if for instance we wanted to only try putting the brand name first for 1/16 or 6.25% of the Black & Decker product titles, we could do something like this:
Rules for new title
if: unique_id([id]) begins_with ‘1’
then: [title] = [brand] [product_name]
Rules for old title
if: unique_id([id]) not_begins_with ‘1’
then: [title] = [product_name] [brand]
3) Set a custom label so that you can judge performance in the Dimensions tab
if: unique_id([id]) begins_with ‘1’
then: [custom_label_3] = ‘brand first’
if: unique_id([id]) not_begins_with ‘1’
then: [custom_label_3] = ‘title first’
4) Analyze the lift
Remember to normalize for your percentage split and use whatever methodology you want to get statistically meaningful data.
5) Profit!
Brian Roizen is the Cofounder and Chief Architect of Feedonomics, a full-service feed optimization platform that optimizes product data for hundreds of channels. He has been featured on numerous podcasts and eCommerce webinars, and regularly contributes to Search Engine Land and other industry-leading blogs. Brian graduated summa cum laude from UCLA with both a Bachelor’s and Master’s degree in Mechanical Engineering.
