Shopping Insights

A Case Study of

Helping retail and brand merchandisers understand trends and demand for products

Shridhar Reddy

View Shopping Insights

Shopping Insights

By analyzing keyword data from all Google searches by consumers throughout their shopping journey, Shopping Insights helps merchandisers and product planners understand which products and brands are popular among potential customers.

My contribution to the product

Shopping Insights’s design team consisted of 2 Product Designers and 1 shared UI designer. My specific contributions to the product are listed below.


How may we help retailers figure out the most important attributes of a product that customers are looking for?


How may we help brands and retailers plan the right assortment of products and brands?


How may we help merchandisers see the location and volume of demand for any product?

Product Attributes

Two competing solutions to the problem of showing which characteristics of a product are the most popular for retailer (or competitor) category so as to effectively plan an assortment.

Simple, minimal look. Only 2 sets of attributes visible at any given time
A more expansive look into the attributes.

Location demand

For merchandisers, it was crucial to know where the demand for any product is. This location card solved the problem with a heat-map like solution that is zoomable to individual counties.

Top Products in Category

How can we show the best products for any given category? And how would that work if the query is not a category, but a product or a product line. An elaborate set of logic rules lay beneath each type of query for this condition.

Final Outcome

6x email subscriptions increase

55.9% increase MAU in first month after product launch


Learning Outcome

Learning how the data is structured, manipulated and extracted had an outsize determination of the user experience of Shopping Inisghts.

Volume of data can be a burden. From a UX perspective, we often struggled with the balance of simplifying time, location and volume data for at-a-glance inference and yet allow for specific investigation.