Written: September 2023

Converting Catalog Data to Features for Users

To begin, I asked four main questions:

1. What type of data can the catalog provide? Mark, my PM, provided the following list of data we could pull.

   

   Screenshot of ticket for design discovery, includes list of available catalog data

2. How might this surface as features? I took Mark’s list and brainstormed a few ways in which each type of data could be surfaced, with a few questions on the technical restraints for each.

   

   Image of initial feature ideas

3. What did we learn from past explorations of historical pricing? Testing on similar features showed fairly divided sentiment around historical pricing graphs—it certainly caught the eye of many but some people loved it while others found it incredibly overwhelming.

   

   Screenshot of similar price history feature. This was tested in November of 2021.

4. What exists now? Our main competitors are Google Shopping’s Price Comparison and Honey’s Extension. For each type of data we could collect from the catalog, I took screenshots of competitors’ similar features, and used elements of each to ideate and describe what our ideal version may encompass. Notably, there were no direct competitors under the “Past Deals” category because this feature is reliant on UGC, which none of our competitors have.

   

   Screenshot of competitive analysis for each of the 3 features

Ultimately, it was clear that we had to go with fairly simple, literal depictions of the data for our MVP. This created a 3-feature list—each serving the purpose of educating the shopper in different ways:

1. Price Drop, with a historical pricing graph

   Amount lower than the typical price, and a visual representation of past prices

2. Price Comparison

   List of prices of the same item at other popular retailers, in real time

3. Past Deals

   List of past deals for the item, posted on Slickdeals

In short, users could see how the current deal stacks up against ones in the past and other retailers matching (or close to) the current deal.

First (and Second and Third) Iteration for a “Best Case Scenario”

The best way to describe getting to the first draft is messy.

States, constraints, and timeline were all unclear; we mocked the ideal state while keeping a few constraints in mind (i.e. keeping what we believed could be launched in the next couple of years and drawing a hard line on what we believed was more of a dream).

After many ideas, layouts, and combinations explored, we landed here at the end of our first proper round of iterations: