Where it got messy
People searching for device repair need to identify a trustworthy service quickly. The experience had to answer urgent questions, communicate official expertise and perform well across traditional and AI-powered search.
Sales Website
When a phone breaks, patience is already running low. I shaped a fast, trustworthy service website that answers the obvious questions and gets people to the right repair channel with minimal detours.
My Role
Built around real people,
not perfect scenarios. Product thinking + craft
not perfect scenarios. Product thinking + craft
Interface studyScroll to unpack the thinking ↓
The setup
What was really going on.
The business needed to turn high-intent searches into qualified service requests. The experience had to establish trust quickly, answer device-specific questions and make the route to WhatsApp or an appointment obvious.
Key constraints
- High mobile traffic and time-sensitive intent
- Trust concerns around authorized repair
- Content needed to serve people, search engines and AI answer systems
What I designed
A conversion-focused information architecture connects service intent to clear calls to action. Structured, helpful content supports SEO and GEO while a fast responsive interface keeps the route to assistance frictionless.
What changed
The result is a more direct path from search to contact, backed by content that is useful to people first and structured for traditional and AI-powered search. Post-launch conversion data was not available for this case study.
How I worked
Messy problem, clear path.
- 01Conversion Rate Optimization
- 02Generative Engine Optimization (GEO)
- 03Content Strategy
- 04Performance Optimization
Discovery
Before opening Figma.
I started by listening for the moments where the experience stopped making sense.
Search-intent analysis, competitor benchmark, review mining, content audit and 5 first-click tests.
Visitors looked for proof of legitimacy, supported devices, price expectations and turnaround time before they were willing to contact the service.
Match each landing page to a specific repair intent and answer trust questions before presenting the primary conversion action.
Design rationale
Why it works this way.
Intent-led architecture
Device and service pages use the language people search for, with direct paths from the problem to eligibility, process and contact.
Trust close to the decision
Authorization evidence, service guarantees and customer expectations appear next to calls to action instead of on a separate institutional page.
Search-ready content system
Structured headings, concise answers, schema-ready content and strong performance improve comprehension and machine discoverability.
Test, learn, repeat
What feedback changed.
Five first-click tests and a mobile usability review shaped CTA placement, service naming and the quote-request flow. Performance checks were included throughout front-end implementation.
What we could verifyPost-launch performance and conversion metrics have not been added without verified analytics.
Selected screens
A closer look.
What I’d carry forward.
SEO, GEO and UX worked best as one content-design problem. The next phase would connect analytics events to search queries and run controlled tests on trust messaging and CTA timing.