Analytics Case Study 3: A/B Testing & Funnel Optimization
Industry:
Ecommerce – The client, an online retail brand, was driving high volumes of paid traffic but struggling to convert users beyond the landing page. Despite solid engagement on-site, conversion through key funnel steps was inconsistent and below expectations.
Problem:
The marketing team lacked clarity on which page elements or user journeys were helping—or hurting—conversion. Specific issues included:
- High bounce rates on product pages and landing pages.
- Low add-to-cart and checkout initiation rates.
- No structured testing strategy or consistent use of A/B testing tools.
- Fragmented analytics data that didn’t clearly link user behavior to funnel drop-off.
Solution:
We implemented a structured A/B testing program and built a funnel analytics framework to identify, test, and optimize high-impact areas of the site. The solution included:
- Conducting funnel analysis to identify biggest conversion leaks.
- Running targeted A/B tests across landing pages, product pages, and CTAs.
- Implementing behavioral analytics to understand user interactions and pain points.
- Building dashboards to track funnel KPIs and A/B test performance.
Execution:
- Funnel Breakdown & Prioritization – Mapped out the full user journey from landing to purchase and ranked steps by drop-off severity.
- Hypothesis Development – Identified potential friction points (e.g. unclear CTAs, long forms, confusing layouts) and developed test hypotheses.
- A/B Test Design & Execution – Used tools like Google Optimize and VWO to run experiments on copy, layouts, images, and flows.
- Behavioral Analytics Setup – Deployed heatmaps, scroll tracking, and session recordings to observe user behavior and validate assumptions.
- Dashboard Build – Created a Looker Studio dashboard to monitor conversion rates, bounce rates, and test lift in real time.
- Iteration & Scaling – Iterated on successful tests and scaled learnings across other product categories and landing pages.
Challenges & Roadblocks:
- Test Velocity – Required careful traffic allocation to ensure statistically significant results without hurting baseline performance.
- Tool Limitations – Some testing ideas were constrained by the ecommerce platform’s flexibility.
- Cross-Device Behavior – Optimizing for mobile and desktop separately required distinct test tracks.
- Organizational Buy-In – Convincing stakeholders to run bold or unconventional tests required clear rationale and data-driven proposals.
Results:
- Increased conversion rate on landing pages by 28% through A/B testing optimized CTAs and layouts.
- Reduced funnel drop-off between product view and add-to-cart by 15%.
- Improved average order value by 10% via optimized upsell placements.
- Enabled the client to build a repeatable experimentation process, increasing test velocity by 3x.
Dashboard:
Key Takeaways & Learnings:
Testing is a long-term strategy, not a one-off tactic—building a culture of experimentation drives sustained growth.
Data-backed hypotheses lead to more effective A/B tests and faster conversion gains.
Funnel mapping and prioritization help focus efforts where they matter most.
Behavioral insights and analytics reveal what users do—not just what they click.
Related Strategy Work:
Business Analysis Case Study 1: Diagnosing Funnel Gaps to Improve Conversion Efficiency