A direct-to-consumer fashion brand doing healthy revenue on desktop but visibly underperforming on mobile, where most of its paid traffic landed. Growth spend kept rising while conversion drifted — a classic sign of leaks, not a demand problem.
Fashion · Demo case — sample project
DTC fashion brand
A direct-to-consumer fashion brand doing healthy revenue on desktop but visibly underperforming on mobile, where most of its paid traffic landed. Growth spend kept rising while conversion drifted — a classic sign of leaks, not a demand problem.
Slow product pages, a stack of overlapping apps, and weak upsell. Mobile conversion lagged behind desktop.
Rebuilt the product page for mobile-first speed, replaced three upsell apps with a single bundle app, and set up clean, trustworthy tracking.
04 — Diagnostic
What the audit would surface.
- 01Mobile product page pushed add-to-cart below the fold behind heavy media.
- 02Three overlapping upsell apps injected ~280KB of render-blocking JavaScript.
- 03Purchase events fired twice, inflating ROAS and misdirecting ad budget.
- 04No trust signals near the buy button on mobile.
05 — Proposed architecture
How we’d build it.
- 01Mobile-first PDP rebuild in the theme with a sticky add-to-cart.
- 02A single custom bundle app replacing three upsell plugins, logic in Shopify Functions.
- 03Server-side purchase events deduplicated against the browser pixel.
- 04GA4 + server events wired to one clean measurement plan.
Theme/LiquidCustom bundle appGraphQL Admin APIGA4 + server events
06 — Implementation roadmap
Audit
Rank leaks by revenue impact across PDP, cart, tracking and app stack.
Conversion sprint
Ship the mobile PDP and cart fixes first — fastest payback.
Custom app
Replace the upsell stack with one owned bundle app.
Measure
Instrument before/after so impact is visible, not assumed.
Potential impact & risks
Estimated impact: faster mobile UX, a clearer cart, and tracking the team can finally trust. (Illustrative — no guaranteed numbers.)
- — Theme edits must be tested against existing apps to avoid regressions.
- — Event deduplication needs careful QA so neither pixel nor server double-counts.
- — Removing apps requires migrating any data or settings they held.
This is a demo case — sample project. Figures are illustrative and not a guaranteed result — your numbers will depend on your store, traffic and market.
Want a build like this — measured for your store?
Start with an audit. We’ll tell you whether the opportunity justifies the build.