We begin with session recording and funnel analysis, observing precisely where visitors go, where they pause, and where they exit. Conversion failures typically originate from a specific point and cause in the funnel: unclear value proposition on the landing page, excessive purchase steps, inadequate social proof at the decision point, or a checkout experience that introduces friction at the worst possible moment. We find the highest-impact drop-off point first and start there, rather than optimizing everything simultaneously.

You need sufficient traffic to achieve statistical significance within a sensible time frame. This required volume depends on your present conversion rate and the scale of the intended improvement. Generally, impactful tests necessitate a minimum of 500 to 1,000 conversions for each variant to yield dependable data. Sites with lower traffic must be more selective about what they test — concentrating on the highest-impact pages and changes instead of running multiple concurrent tests that fail to reach significance. We size the testing program to your traffic reality.

We ensure implementation is integral to the engagement, rather than considering the audit itself as the final output. We don't just deliver a list of suggestions and withdraw; instead, we execute the tests, implement the successful changes, and manage the ongoing optimization program. The audit functions as the foundation for a continuous improvement system, not a document.

Both. Amazon listing optimization ( title, bullets, imagery sequencing, A+ content structure) is conversion rate optimization applied to the Amazon environment. The methodology is the same: hypothesis, test, measure, implement winner. The constraints are different. Amazon's testing tools are more limited than D2C, but the principle of continuous, data-driven improvement applies equally. We build the optimization program across both surfaces because that's where your traffic is converting, or not.