Challenge
An ever-evolving field, ecommerce personalization requires routine maintenance and modification to drive performance and achieve optimal results. Per best practice, Sophelle’s personalization practice leaders continually search for new ways to maximize client success.
Although Sophelle implemented a robust ecommerce personalization strategy for a home and personal product retailer, Practice Manager Ken Kantor noticed additional room for improvement on product detail pages.
Solution
In the world of personalization, retailers often adjust algorithms to group products by category. For example, when shoppers search for blue tee shirts, AI is traditionally programmed to show other tee shirts. Offering more options within the same category seemingly matches the customer’s original intent.
However, for this client, extensive analysis and testing through data modeling revealed a surprising finding in consumer behavior: shoppers gravitated toward products with similar features more than products in the same category. For instance, customers who viewed a linen pillow were likelier to purchase other linen products than they were to buy more pillows with different materials.
This new data analysis proved that consumers aren’t always shopping for a specific product type. Or, perhaps that’s how they begin their shopping experience, but then they change their mind along the way. This finding reinforces the benefit of personalization, as retailers can program AI to account for that change in customer intent.
Result
By altering personalization tactics, the retailer is estimated to increase their yearly revenue on product detail pages by $200k, a significant return on investment from the platform itself. While the client benefits from this success, Sophelle’s practice leaders returned to the drawing board to run tests and brainstorm more ways to maximize the retailer’s personalization strategy further.
