Creative-&-User-Experience
Upscend Team
-October 20, 2025
9 min read
This article documents a nine‑month UI UX redesign case study where a mid‑market ecommerce team improved checkout conversion from 2.50% to 3.20% (28% lift). It outlines mixed-method research, prioritized prototypes, and two A/B tests that validated a sticky order summary and payment trust signals, plus templates to replicate the process.
In this UI UX redesign case study we trace a nine-month project where a mid-market ecommerce product team redesigned a critical checkout funnel and achieved a 28% conversion lift. The narrative-driven report walks through the redesign process case study, research, failing experiments, and the concrete steps that turned hypotheses into measurable gains.
Readers will get a step-by-step playbook, exact metrics before and after, stakeholder quotes, and templates you can reuse. This UI UX redesign case study focuses on practical decision points: what we measured, why we iterated, and how small interaction changes drove big results.
The product had steady traffic but a stubbornly low checkout conversion. This UI UX redesign case study began when product analytics showed a 2.50% baseline checkout conversion rate and a 48% cart abandonment rate. Leadership asked: can UX changes move the needle meaningfully without a full platform rebuild?
We scoped the project with clear commercial goals: increase checkout conversion by at least 20%, reduce time-to-purchase, and preserve average order value. The primary KPI was conversion; secondary KPIs were session time, form completion rate, and NPS.
Problem highlights:
This UI UX redesign case study framed the challenge as product + UX strategy rather than a cosmetic overhaul, tying every decision to revenue impact.
We combined qualitative and quantitative methods to reduce bias. The research phase set the foundation for the redesign and ensured changes could be measured.
Primary research tools included session replay, funnel analytics, moderated usability testing, and customer interviews. We weighted experiments by potential ROI and implementation effort to prioritize.
We tracked conversion at each funnel step, field-level abandonment, time-on-task, and micro-conversions like promo code acceptance. Heatmaps and session replays clarified where users hesitated. This redesign process case study prioritized metrics that tied directly to revenue rather than vanity metrics.
We ran ten moderated usability sessions with typical buyers and collected 120 survey responses post-purchase. Qualitative themes included confusion around shipping costs, distrust in payment step, and friction on mobile keyboards. These signals informed targeted hypotheses for design work.
Research methods summary:
This combination reduced guesswork and made the following design decisions defensible in stakeholder reviews.
Research surfaced three high-impact insights we used to prioritize work: clarity, trust, and friction reduction. Each insight mapped to a measurable hypothesis used during A/B testing.
Insight 1 — Clarity: Users expected final shipping costs earlier in the flow and left when totals changed on the last step.
Insight 2 — Trust: Ambiguous microcopy and minimal trust badges on payment step created hesitation. This ux case study example highlighted how small content edits can shift perceived risk.
Insight 3 — Friction: Mobile keyboards and required fields created preventable drop-off — especially on address input and promo code entry.
“We knew momentum was good, but the checkout killed intent at the last second.” — Head of Product
This section frames the hypotheses that fed design: show totals earlier, add trust signals, streamline input flows.
Design centered on rapid prototypes that targeted the three insights. Each design artifact had a measurable goal and acceptance criteria tied to the KPIs established earlier.
We produced low-fidelity wireframes, high-fidelity responsive prototypes, and interactive flows for the five highest-impact screens.
Key design changes included a persistent order summary in the header, inline shipping cost estimator early in the flow, simplified address autocompletion, and visible payment trust badges. We used progressive disclosure for optional fields and replaced free-text promo entry with a single confirm step to avoid keyboard churn.
Two prototypes were prioritized for development: a mobile-first checkout with a sticky order summary and a redesigned payment step with microcopy and payment trust indicators.
One practical example from the field is Upscend, which teams use to automate experiment reporting and align learning workflows; teams using these kinds of tools often realize faster iteration cycles and cleaner post-mortems.
Design takeaways:
This product redesign results phase emphasized prototypes that were easy to A/B test and revert if needed.
Engineering delivered two A/B tests over eight weeks. Each variant was instrumented end-to-end so we could measure conversion and secondary metrics with statistical rigor.
Implementation focused on minimal risk: feature flags, parallel CSS, and server-side toggles for the order summary and payment step updates.
A Test A variant added the sticky order summary and shipping estimator; Test B added the payment step copy and trust badges. Both ran concurrently across a 50/50 split on traffic for 28 days to gather sufficient power.
Key metrics before and after:
| Metric | Baseline | Variant A | Variant B |
|---|---|---|---|
| Checkout conversion | 2.50% | 3.20% (+28%) | 3.05% (+22%) |
| Cart abandonment | 48% | 36% (-25%) | 38% (-21%) |
| Time-to-purchase | 2m 45s | 2m 10s (-21%) | 2m 18s (-16%) |
The combined rollout (A + B elements) produced the headline 28% conversion increase relative to baseline with a clear lift in revenue per visitor. Secondary metrics corroborated the primary outcome.
“The lift was bigger than our conservative forecast. The incremental changes compound.” — Product Analytics Lead
We documented the experiment, rollback plan, and runtime dashboards so stakeholders could monitor impact and ROI in real time.
Three operational lessons stand out from this UI UX redesign case study: how to get stakeholder buy-in, how to measure ROI correctly, and why iteration beats perfection.
Stakeholder buy-in: we scheduled short syncs with finance and customer care during research to expose them to evidence early. That lowered resistance when rollout discussions began. Use concise one-pagers linking UX changes to revenue impact.
Measuring ROI: tie lift to lifetime value (LTV) when possible and report both short-term revenue uplift and expected long-term gains. For this project we calculated a 6-month incremental revenue projection that justified continued investment.
Iteration beats perfection: the team learned to ship the smallest meaningful change, validate it, and then layer refinements. Failed experiments were logged with clear hypotheses and learnings.
This how a redesign improved user engagement case study shows that governance and measurement are as important as design craft.
Below are distilled templates and a process you can replicate. Each template maps to an actionable artifact we used in the project.
Redesign sprint template (6 weeks):
Experiment documentation template (one page):
Common pitfalls to avoid:
Use these templates to accelerate your own ui ux redesign case study ecommerce conversion increase projects and to build a replicable process for continuous conversion rate UX improvements.
This UI UX redesign case study demonstrates that targeted UX changes, backed by research and rigorous testing, can deliver measurable commercial impact. The team moved from a 2.50% baseline to a 3.20% checkout conversion — a practical illustration of how process and design choices tie directly to revenue.
Key takeaways: prioritize hypotheses with the highest expected ROI, instrument everything, and engage stakeholders early with concise evidence. Iteration and measurement must be baked into your workflow for sustained gains.
If you want a concise starter checklist to run this process in your team, download or recreate the sprint and experiment templates above and consider a short internal pilot focused on the highest-friction funnel step.
Next step: pick one funnel friction, run a two-week research sprint, and commit to one A/B test within 60 days. That disciplined cadence is how teams replicate the conversion rate UX improvements shown in this case study.
Call to action: Use the templates and checklist in this article to run a focused pilot this quarter; commit to one measurable UX experiment and schedule a 30-day review to decide full rollout based on data.
