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Optimising the digital shopping experience for a home improvement retailer

A 3-week diagnostic across paint, kitchen, and timber. 153 ranked usability issues, four strategic questions, and Figma design variants for each.

Optimising the digital shopping experience for a home improvement retailer
Three weeks of audit and recommendations distilled into one playback.
Role
Product Designer
Client
NDA - Major UK Retailer
Date
Mar 2023 – Mar 2023 (1 month)
Team
Competitive researcher, lead designer/consultant, Freelance designer
Scope
Heuristic findings, annotated screenshots, Figma design variants, final playback deck
Output
153 ranked usability issues, four strategic "how might we" questions, Figma design variants for each
Tools
FigmaFigmaMiroMiro

TL;DR

Where we started. A national home improvement retailer wanted to know where the friction sat on three of its biggest categories before committing to roadmap investment.

What we did. Five-person team, three weeks, four lenses cross-referenced into one diagnostic. I owned the heuristic findings, the annotated visuals, the Figma design variants, and the final playback deck.

What landed. A prioritised problem map, four strategic questions to shape next steps, and design variants for each, so the team had something concrete to react to, not just a list of issues.

The audit

We audited the same journeys four ways, then pulled the findings into one ranked map.

Three categories that pull different shoppers. Paint, kitchen, timber. Within each, two journey shapes: people browsing for inspiration, and people who know what they want and need it done by Saturday. We modelled both, across all three, on desktop and mobile.

I scored every screen against Nielsen heuristics with a severity scale (Minor, Moderate, Severe, Unusable), logging 153 ranked issues by end of week three. In parallel, the team layered competitor benchmarks (direct rivals like Screwfix and B&Q, plus category specialists like Lick, Dulux, Magnet, Wren), six user testing interviews, and conversion-funnel data from Google Analytics.

Most severe issues clustered on PDP, basket, and checkout. The analytics agreed: add-to-basket conversion was 5.9% against an industry average around 11%.

Optimising the digital shopping experience for a home improvement retailer
Heuristic annotations marking friction points across the existing experience.
The recommendations

Each strategic question came with Figma variants the team could pull apart.

Findings needed to translate into something the team could act on. So I built Figma design variants against each of the four "how might we" questions we landed on. Options to weigh, not a single redesign to accept or reject.

Hick's Law on the basket: the existing flow asked shoppers to commit to delivery or click-and-collect on every item before checkout, slowing the whole journey. The variant moved that decision into checkout where it belonged. Mega menu: Interior Paint was buried mid-list despite being top-three for pageviews; the variant put it first. Paint PDP: bridging inspirational landing pages to product pages with a layout that surfaced both. Appointment booking: a streamlined form on the existing booking path.

One example of how small, targeted changes improved the experience.
Optimising the digital shopping experience for a home improvement retailer — before
Optimising the digital shopping experience for a home improvement retailer — after
Outcome

A sequenced starting point, not a wish list.

A prioritised problem map across three categories, four strategic questions to anchor the next phase, and Figma design variants for the team to choose between. I don't have visibility into what got picked up after handover. The engagement was scoped to give them somewhere to start, and it did.

Optimising the digital shopping experience for a home improvement retailer
Optimising the digital shopping experience for a home improvement retailer
Optimising the digital shopping experience for a home improvement retailer
Prototyped improvements across navigation, product pages, and checkout.

What I took from it

Heuristic findings land better when paired with design variants the team can react to.

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