Problem: The core flow of HelloShopper is a user requesting at certain item and our team of personal shoppers finding recommendations based on that criteria. After sending a set of recommendations, our shoppers needed feedback on those items if continued shopping was required for that request. Our first version of the feedback mechanism was a set of fixed responses (i.e. “Like it, but don't love it. Here's why…”) that users could select and add free text to. We found that mechanism had low engagement which left our shoppers in the dark about how to proceed with the request.

Solution: Create a mechanism that encourages the kind of feedback our shoppers can use to continue shopping.

Design: 
(1) When talking to the shoppers about what kind of feedback would be useful to them, a number of paradigms we’re discussed (thumbs up/down, number ratings, smiley/frown-y faces). In the end we decided that the hot/cold spectrum lent itself well to this problem since the question of “are we getting warmer” inherently helped describe why we needed feedback. 

(2) Our shoppers felt that just a rating would not be enough to help them continue shopping so additional information was required in order to submit feedback. 

(3) Once feedback was submitted, the mechanism turned into a chat feed where shoppers could respond directly to that feedback. These comments would appear in the chat view, tagged with the product picture. 

Results: We found that discovery and use of the feedback mechanism went up, however users were largely unwilling to give additional comments like the shoppers wanted. We also found that most conversions happened within the first set of recommendations sent and dropped off significantly with each additional shop. We decided to hold off iterating on the feedback mechanism and focus on nailing that first round of recommendations.