Buying a bra online carries a little bit of an act of faith, this step process gets more difficult for the sports bra category: the sizing, fit, and texture are all highly dependent on a number of variables, somewhat unique and subjective to each consumer. Jockey wanted to tap into their vast knowledge base of how their underwear works toward guiding customers to the best garment. But this involves multiple data dimensions and could be a fairly tricky navigation through tables and multiple questions.
We built this AI-powered interactive app on our low-code development platform Interplay. The flow diagram is shown above. To build this app, we dragged-and-dropped those nodes together, configured each one, and then hit the ‘deploy’ button. Yeah, that quick. Among the nodes used were the following:
To address this challenge, Iterate designed an AI-based natural language FAQ: customers can ask a question in normal conversational English as if they were speaking to a sales clerk in the store. The AI returns a recommended product based on the best fit to address the customer’s question. Note: many common recommendation engines will send the ‘most popular’ or ‘best selling’ product, which is exactly what Jockey wanted to avoid.
To set up this AI-powered FAQ, our team did the following:
Retail, Apparel, Jockey
Eliminate confusion related to bra sizing