Gdgt.com Buying assistance app

Picture a parent in a big-box store, staring at fifty routers, with no idea which one to pick. That's where this starts. I'll be straight about what it is: gdgt / Engadget was a take-home design exercise for a pair of consumer-electronics properties — a hiring exercise, not a shipped product. No launch, no metric at the end. The value on display is the thinking: how I made concrete decisions on a deliberately vague brief with no one to ask.

The ask was a single paragraph: design a companion mobile app that helps someone shopping for consumer electronics make an educated buying decision, using the rich product data gdgt and Engadget already had. The anchor scenario was the router shelf. That was it — no research, no personas, no KPIs, and critically, no ability to ask a single follow-up question. The exercise was quietly testing whether I could take a fuzzy question, state my assumptions out loud, and commit to a defensible answer. So I made the process the deliverable.

Before sketching anything, I decided the thing to nail was what information people actually reach for when making a buying decision they don't feel qualified to make. I couldn't run a study, so I answered from prior e-commerce work and a working model of non-technical shoppers: price, ease of use, and compatibility. Those became the principles every screen had to earn its place against.

My first instinct — search and click through products one at a time — I rejected fast: for someone staring at fifty routers, that's exactly the intimidating experience the brief was trying to fix. So I pivoted to guided entry points that meet the shopper where they physically stand: a curated Product Guide for the person who wants to be led, Search by Store so you only see what's carriable near you, and Scan UPC.

Scan UPC was the move I was proudest of: point the camera at the box in your hand and pull the exact record. It collapses the gap between the physical shelf and the digital data — the real friction in the scenario.

The product detail page is where the decision gets made, so I built it around what gdgt and Engadget do best: critic reviews with per-category breakdowns, user reviews kept separate, and a full-specs tab underneath. The principle: serve the primary user without amputating the power user — a trustworthy score at a glance for the non-techie, room to dig for the spec-hungry.

I translated the key screens into grayscale wireframes first — so the layout got pressure-tested before a single pixel was styled — then resolved them into a styled flow that leads with price and lets you refine by rating and category.

No launch, no metric, and I won't dress it up: after I submitted, there was no further contact. That's the honest ending. But the output was a complete point of view — a phone-in-the-aisle app with three entry points, price-led results, and a review-and-spec detail page, every assumption documented alongside. The lesson that outlived the exercise: stating your assumptions out loud is a design skill in its own right. On a vague brief, the answer isn't to guess the hidden intent — it's to reason from what you know, commit to a point of view, and make that reasoning legible enough to challenge.

See the full case study → https://design-case-studies.vercel.app/gdgt