Avatria was tasked with optimizing Anixter's eCommerce tracking, product catalog, and analytics without any backend development. The client's customers found the product navigation and search relevancy difficult to work with due to the following reasons:
Complex hierarchy (150+ categories)
Large catalog (1,000,000+ SKUs)
Many similar products with minor differentiation
B2B account specific product catalogs
Avatria helped the customer implement Enhanced Ecommerce tagging exclusively through the DOM and Google Tag Manager, without the need to do any backend development work.
As part of the A/B test setup, Avatria also setup Google Optimize for the customer and integrated the test data into Adobe Analytics via Launch, for further analysis of the results.
Machine Learning rankings were then applied to the site's "Trending" sort order via csv uploads and minor Solr configuration work. The team tuned the rankings twice during the A/B test and both tuning efforts resulted in significant gains for the Machine Learning variant.
After implementing Enhanced Ecommerce tagging, Google Optimize, and Avatria Convert, an A/B test was run to measure improvement:
- A/B Test Platform: Google Optimize
- Test Duration: 78 days
- Categories Tested: 10
- Control Variant: Solr Relevance
In addition to the metrics listed below, Avatria's solution outperformed the control group in 9 other metrics including: Buy to Detail Rate, List Clickthrough Rate, Adds to Cart, Average Order Value, Product Detail Views, Sitewide Online Orders, Checkouts, and Revenue Per Impression
