Conversion Rate Optimization: Research Before Testing

Testing without research is guessing

Random A/B tests rarely produce meaningful wins. Research identifies where users struggle and why, giving you hypotheses worth testing.

Useful research methods

Combine quantitative and qualitative data.

• Funnel analysis in GA4
• Heatmaps and scroll maps
• Session recordings
• On-site surveys
• Customer interviews

Prioritise by impact

Score ideas by potential impact, confidence and effort. Focus on high-traffic pages close to conversion, such as pricing, product and checkout pages.

Respect statistics

Run tests for full business cycles and reach adequate sample sizes before concluding. Ending tests early is one of the most common causes of false wins.

Build hypotheses from observed friction

Combine analytics with support questions, sales feedback and usability observations. If visitors abandon a quote form, investigate its length, validation, accessibility and the uncertainty around what happens next. A useful hypothesis connects a specific friction point to a proposed change and an observable outcome. Changing a headline without knowing the underlying problem is a weaker starting point.

Prioritise repairs separately from experiments. A broken submit button, unreadable text or inaccurate price needs correction; it does not require an A/B test. For uncertain design choices, choose a primary outcome and guardrail metrics before starting. Guardrails can include lead quality, checkout errors or refund rates so a higher click rate does not disguise harm elsewhere.

Know when an A/B test is unsuitable

Low-traffic pages may take too long to produce a reliable experiment result. In that situation, use structured usability sessions, customer interviews and a carefully documented before-and-after change, acknowledging attribution limits. Where testing is viable, account for conversion delay, avoid repeated early checking and include complete business cycles. Implement changes only after reviewing both the evidence and practical risks.