CASE STUDY
Location | United States
A national rent-to-own retailer with thousands of physical locations and a high-volume e-commerce channel was struggling with friction on their product detail page (PDP)—the highest-intent surface in their funnel. Click-through rates on the primary call-to-action were below benchmark, and heatmap signals showed visual competition between the CTA, promotional banner, and product controls. Stakeholders disagreed on the right fix, but every change carried revenue risk. Opinions alone could not justify a deployment, making A/B testing ecommerce protocols the only viable path to a data-backed decision.
Royal Cyber partnered with the retailer to design and execute a structured experimentation program on Optimizely Web Experimentation. We engineered a controlled A/B/n test with two challenger variations against the original control—running for two weeks across 215,000+ visitors with a 50/50 traffic split. The winning variation delivered statistically significant uplift across every primary KPI: +2.7% on Product Web Orders, +4.3% on Finance Order Capture (FOC) Conversion, and +1.7% on Reservation Conversion. The variation was promoted to 100% of traffic and is now the live experience on their e-commerce site.
Below-Benchmark CTA Performance
Click-through rates on the primary PDP call-to-action were failing to feed downstream conversion targets, directly impacting revenue across all three monetization paths.
Visual Competition on the PDP
Heatmap and session-replay signals indicated that the CTA, promotional banner, and product configuration controls were competing for visitor attention, creating measurable friction.
Internal Disagreement on Design
Stakeholders had opposing views on the right design fix. Every change carried revenue risk, so opinions alone could not justify a deployment.
No Data-Backed Decision Framework
Without a structured experimentation program, every design change was a gamble. The organization needed the statistical rigor provided by A/B testing ecommerce to validate hypotheses before committing development resources.
Revenue Risk of Getting It Wrong
Even single-digit percentage changes translate into seven-figure incremental revenue annually. Modern A/B testing ecommerce frameworks were required to mitigate the risk of getting it wrong.
No Repeatable Testing Process
The organization lacked an ongoing experimentation operating model. Tests were one-off events rather than a continuous optimization engine.
+4.3%
Lift in Finance Order Capture (FOC) Conversion—Variation #1 winner
+2.7%
Lift in Product Web Orders—Variation #1 winner
+1.7%
Lift in Reservation Conversion—Variation #1 winner
100%
Winning variation promoted to live experience
95%
Statistical confidence on primary metrics within the planned two-week window
Controlled A/B/n Experiment Design
Royal Cyber engineered a two-week test running two challenger variations against the original control, with a 50/50 traffic split across 215,000+ visitors using Optimizely's deterministic hashing. This rigorous approach to A/B testing ecommerce ensured that results were confirmed at 95% confidence.
Statistically Rigorous Methodology
Optimizely Stats Engine with sequential testing controlled the false discovery rate, allowing valid "peek" results during the run without inflating Type I error. Decisions were made at ≥95% statistical significance.
Hypothesis-Driven Variation Design
Variation #1 simplified the visual hierarchy, elevated the CTA with higher color contrast, compressed the promo banner, and de-emphasized the filter rail. Variation #2 tested an alternate CTA placement with trust signals near the price block.
Flicker-Free Execution
Edge/CDN-delivered execution with pre-render variation application meant variations applied before first paint—visitors never saw a flash of control snapping to test version.
Weekly Experimentation Cadence
Royal Cyber ran a structured weekly process: hypothesis intake, design review, QA in Optimizely preview mode, production launch, mid-flight health check, and structured 14-day readout.
Enterprise-Grade Compliance
This streamlined A/B testing ecommerce workflow inherited PCI DSS, GDPR, CCPA, and HIPAA-ready posture from Optimizely. Role-based access with audit logging on every change.
Experimentation Platform
Optimizely Web Experimentation
Deployment
Asynchronous Optimizely JavaScript snippet via tag manager
Variation Authoring
Optimizely Visual Editor with custom JS/CSS
Traffic Allocation
Deterministic hashing on visitor ID (50/50 split)
Statistical Engine
Optimizely Stats Engine with sequential testing
Event Tracking
Custom Optimizely events for CTA clicks, FOC, Reservations, Product Web Orders
Performance
Edge/CDN-delivered, flicker-free pre-render execution
Compliance
PCI DSS, GDPR, CCPA, HIPAA-ready
Executive Insight
- Stakeholders disagreed on the right PDP design for months. Two weeks of A/B testing ecommerce settled the debate with statistical rigor—Variation #1 won across every monetization path.
- Heatmap signals showed visual competition between CTA, promo banner, and product controls. Simplifying the hierarchy and elevating the CTA drove measurable lift.
- The test ran for two weeks across 215,000+ visitors. Optimizely’s Stats Engine reached significance within the window—no extended waiting.
- The winning variation is now live. Every dollar of dev investment going forward is informed by test results, not opinions.
- Royal Cyber also delivered a repeatable experimentation operating model—the retailer can now run continuous A/B testing ecommerce cycles, not just a one-off win.
100%
Winning variation promoted to live experience
Audience
- E-commerce & Digital Commerce Leaders
- Optimization & Experimentation Program Managers
- Product & UX Leaders
- Marketing Analytics Teams
- Salesforce Commerce Cloud (SFCC) Store Owners
- IT & Digital Platform Owners
