Service / 18
We find the points in your funnel where prospects drop off and we fix them, measured against real revenue, not vanity engagement metrics. Continuous testing rather than six-week sprint-then-ghost cycles, senior people on every test design, no proprietary lock-in (everything runs on your existing GA4 and experimentation stack).
What it unlocks
Built for ecommerce and lead-gen accounts running enough traffic to test meaningfully (minimum ~5,000 monthly visits to the page under test), where revenue or pipeline lift is the metric, not click-through rates.
Capabilities
Engagement rhythm
Free diagnostic audit
Test hypothesis backlog
Continuous test cadence
Quarterly strategic review
What we do
Heatmaps, session recordings, scroll depth, and funnel-segment analytics applied to the pages that actually drive revenue. We tell you where prospects drop off, why, and which fixes have the highest expected revenue impact. Not a 60-page audit that reads well and changes nothing; a prioritised hypothesis backlog with sizing on each item.
Hypothesis-led tests with quantified outcomes. Runs on your existing GA4 + experimentation stack (Optimizely, VWO, Convert, or GA4 Server-Side experiments), no proprietary platform lock-in. Every test is sized for statistical significance before launch (no 'we ran for two days and saw a 4 percent lift, ship it'), and we kill tests cleanly when they do not pay back, rather than letting flat-lined tests run forever.
Cohort the funnel by traffic source, device, and audience. The 8 percent drop-off on a category page rarely matters. The 47 percent on the checkout step does. We tell you which is which, sized by recoverable revenue. Most accounts have one or two funnel steps doing 80 percent of the leakage; we focus there first.
Most paid traffic lands on pages that were not designed to convert it. We test message-match between ad copy and landing page hero, social proof placement, form length, hero structure, and CTA hierarchy. Channel-specific landing pages where the same generic page is leaving conversions on the table for Meta vs Google vs organic vs direct traffic.
Where ecommerce CRO programmes earn their fees. Field reduction in checkout (every field cut converts to a measurable conversion lift on most stores), payment-method ordering by what your audience actually uses, trust signals at the right moment (return policy near the buy button, not in the footer), abandonment recovery, and post-purchase upsell.
A 100ms slower LCP is a measurable conversion-rate hit. We treat performance as a CRO lever, not a separate technical exercise. Every test gets a performance check before launch (so the variant is not slower than the control), and we run quarterly CWV audits on the full site to catch creeping degradation.
How an engagement runs
Funnel analysis on your highest-revenue pages, heatmap and session recording review, top-line conversion rate by channel, device, and audience. Prioritised hypothesis backlog with expected revenue impact per item. We tell you which fixes are worth shipping first and which are noise. No commitment past the audit.
Top 10 to 15 hypotheses sized and prioritised. Test design and statistical sizing for the first three. GA4 conversion events audited or rebuilt to ensure the tests are measuring against the right outcome. Experimentation platform (Optimizely, VWO, Convert, or GA4) configured.
2 to 4 tests live at any time across PDPs, checkout, landing pages, and acquisition funnel. Winners shipped to production. Losers documented (the why-not-ship matters as much as the why-ship). Monthly report on tests run, results, revenue impact, and what is going into the queue next.
Every 90 days: which page categories paid back, where the test pipeline is dry, what changed in your traffic mix that opens new hypotheses, where next quarter's focus should sit. Real strategy from a real human.
The lay of the land
The standard CRO programme starts strong. Month one diagnostic audit, hypothesis backlog, three tests live by week six. By month four, the agency is running the same template tests they ran for last quarter's client (sticky CTA, sticky add-to-cart, reduce checkout fields, swap the hero image), and the wins are flatlining. By month six, you are paying for tests that nobody is excited about, the agency is sending you a Looker Studio dashboard nobody opens, and you start wondering whether CRO is even working for your business.
The fix is hypothesis discipline plus continuous diagnostic work. Run the template tests once (they will produce wins on most accounts in the first month) and then move on. The compounding tests are the ones that come from real research: session recordings of buyers in your specific category, support ticket data, sales call recordings, post-purchase surveys, competitor PDP teardowns. We feed that diagnostic work back into the hypothesis backlog continuously, rather than running the same playbook on autopilot.
The other failure mode is over-testing without enough traffic. CRO on a page getting 800 visits a month is mostly theatre; you cannot reach significance in a sensible window. We are direct about minimum traffic thresholds in the audit. If your page-level traffic is below 5,000 monthly visits, the test cadence will be slower and the recommendations will lean toward qualitative work plus structural changes rather than statistical A/B tests.
FAQ
Around 5,000 monthly visits to the page under test as a soft floor. Below that, A/B tests take too long to reach significance and you are better off making structural changes based on qualitative research (session recordings, support tickets, competitor teardowns). Above 10,000 monthly page visits, continuous testing compounds meaningfully.
No. We run on your existing experimentation stack (Optimizely, VWO, Convert, GA4 Server-Side Experiments) so when you stop working with us, you keep the data, the historical tests, and the configured platform. No proprietary lock-in or 'our platform' that disappears if you cancel.
Only if they are set up badly. We use server-side experimentation where the testing platform supports it, and client-side experiments are loaded with deliberate care to avoid the flicker-of-original-content (FOOC) problem that ruins both UX and CRO data. Performance is measured per test variant before launch.
PDPs and checkout are where most ecommerce CRO programmes earn their fees. PDP work covers above-the-fold structure, product imagery, social proof placement, FAQ accordion, urgency cues, mobile-specific layouts. Checkout work covers field reduction, payment-method ordering, trust signal placement, guest vs registered checkout flow, and post-purchase upsell. We work natively in your Shopify, WooCommerce, or custom platform rather than building parallel checkout flows.
Every test reports out with: statistical significance, conversion rate lift, revenue lift (extrapolated to monthly or annual), and a confidence interval on the revenue lift. We separate the question 'did the variant win' from 'was the win meaningful enough to ship'. Most agencies blur these; the difference matters because some statistically significant wins are revenue-neutral noise.
Yes. Onboarding audit covers the existing test history, the platform configuration, and the diagnostic data. Tests already live get reviewed and either kept, paused, or rewritten. The first 30 days is usually equal parts continuing the existing programme and tightening it; from month two we are running the cadence ourselves.
Yes. CRO that depends on you building every variant is not CRO; it is a consultancy with a recommendation deck. We build the variants in your platform (Shopify section overrides, WooCommerce template work, WordPress block work) so the test ships within a sensible window.