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Get a QuoteRedefine runs A/B testing, user experience audits, and funnel optimization for ecommerce brands turning traffic into revenue. We find where visitors drop off and fix it with data, not guesses.

Most ecommerce growth advice tells you to spend more on ads. Before you do that, close the gap between the visitors already arriving and the revenue you should be capturing from them.
We had 80,000 visitors a month and barely 1.4% were buying. That is 78,880 people leaving every month without spending a dollar.
The situation most ecommerce brands bring to us, traffic is not the problem.
Adjust the sliders to match your store. The right panel updates live with what a conversion rate optimization engagement could realistically return.
A realistic conversion rate optimization target is 50 to 100% improvement on your current conversion rate, achieved over 3 to 6 months of structured testing. The default target of 3.2% is conservative for a store starting at 1.8%.
This projection assumes no increase in ad spend. The same traffic, optimized. Every gain is pure margin improvement.
No commitment. No pitch. Call within 48 hours.
Conversion rate optimization is not one thing, it is a system of overlapping disciplines. We run all four together because each one feeds the next.
We install session recording, click heatmaps, and scroll depth tracking across your highest-traffic pages. Every drop-off point becomes visible before we write a single hypothesis.
We build, run, and analyze A/B tests across your highest-impact pages. No hypothesis goes live without a test behind it. No winner ships without statistical confidence above 95%.
Every store has a funnel. Most stores have never measured where exactly customers drop out of it. We map each stage, quantify the drop-off rate, and prioritize fixes by revenue impact.


Typical conversion rate optimization agencies run templates. We start with your actual visitor data. The three principles below are why results differ.
Every engagement starts with 90 days of session recording, heatmap data, and funnel analysis before we suggest a single change. Most agencies write recommendations from industry blogs. We write them from your actual visitor behavior.
Every A/B test runs until we reach 95% statistical confidence. We do not call early winners. We do not let gut feeling override data. If a test needs 28 days to be conclusive, it runs 28 days. Your store does not get worse changes shipped to it.
Every closed experiment ships with a revenue attribution report: how much the control generated, how much the winner generated, and the monthly revenue gain from shipping the winner permanently. You always know what conversion rate optimization is worth to you.
Real reasons brands wait on conversion rate optimization. Real answers. The audit covers anything we miss here.
Get My Conversion Rate Optimization AuditNo commitment. No pitch. Call within 48 hours.
Conversion rate optimization on an ecommerce store involves identifying where visitors drop off in the purchase journey and systematically fixing those points through structured testing. In practice, that means heatmap and session recording analysis, A/B testing on product pages, cart, and checkout flows, copy and user experience changes validated by data, and revenue attribution on every experiment. It is not one project, it is an ongoing optimization cycle that compounds over time.
The first 30 days are data collection and audit, we are watching your visitors, mapping your funnel, and writing hypotheses. The first tested winner ships in weeks 5 to 8. Compounding results (multiple experiments stacked) become visible between months 3 and 6. If you are expecting a new checkout button to triple your revenue in week 2, conversion rate optimization is not the right service yet, but if you want systematic, permanent improvement to your store's conversion over a full engagement, that is exactly what this delivers.
Meaningful A/B tests require enough traffic to reach statistical significance within a reasonable timeframe. The minimum we work with is 5,000 monthly unique visitors to the page being tested, below that, tests take too long to reach 95% confidence. Most of our clients have between 10,000 and 200,000 monthly visitors. If you are below 5,000, the heatmap and funnel audit work still applies, but full A/B testing infrastructure should wait until traffic grows.
Yes, for winning test variants to ship permanently, we need to implement changes in your theme or codebase. For Shopify stores, that means collaborator access. For headless or custom builds, we work through your existing deployment pipeline. We document every change before shipping it and require your approval before any update goes to production. You are never looking at a change you did not review first.
Every closed experiment gets a revenue attribution report: control revenue, variant revenue, statistical confidence level, and the estimated monthly gain from shipping the winner permanently. Weekly progress updates cover active tests, what is being monitored, and what the next hypothesis is. You always know what each experiment is worth, and what the overall conversion rate optimization engagement is returning per month.
Yes, but timing matters. A/B testing requires a stable baseline, if your site is mid-redesign, test results are unreliable. We run conversion rate optimization on your existing store while a redesign is planned, then run a fresh audit on the new design at launch before resuming full A/B testing. If a platform migration is underway, the funnel audit and heatmap analysis are valuable inputs to the new design brief and can be done in parallel.
Conversion rate optimization is one of the highest-leverage investments in ecommerce, but only when the conditions are right. Here is how to know.
Not sure where you land? Tell us your situation in the brief below and we will be straight with you about whether conversion rate optimization is the right next move.
No commitment. No pitch. A real look at where your store is leaking conversion, and what fixing it is worth.
Your team's time investment across a full engagement is typically 3 to 4 hours per week, one sprint review, async feedback on test variants, and a final sign-off on winners. We handle everything else.