Conversion rate optimisation, diagnosed and shipped
CRO fails for one of two reasons: nobody knows where the funnel actually leaks, or somebody knows and the fix never ships. The agents close both gaps.
Conversion rate optimisation is usually described as a testing discipline, but for most stores the binding constraint is earlier than that. The funnel has three or four obvious problems that nobody has isolated, and the team has no capacity to ship fixes even when they are identified. Analyst does the isolating, Builder does the shipping, and the loop closes with a measurement rather than an assumption.
Diagnosis before ideas
A conversion rate is an average that hides everything useful. Analyst breaks it apart — by device, traffic source, landing page, and funnel step — until the loss is attributable to something specific enough to fix.
Step-level drop-off across view, cart, checkout, and purchase
Device splits, where mobile problems are usually hiding
Landing pages that absorb traffic and produce no revenue
Traffic sources whose conversion is far below their volume share
Fix the cause, then test the refinement
Testing a button colour on a page with a broken mobile layout is theatre. The agents fix structural problems first — layout, speed, clarity, missing information — and reserve testing for the genuinely uncertain choices, where the traffic volume can support a conclusion.
Measured against a real baseline
Every change records the state before it shipped, so improvement is not confused with seasonality or a change in traffic mix. Where a change cannot be cleanly attributed, the agent says so instead of claiming credit.
How it works
Isolate the leak
Analyst segments the funnel until the loss has a specific, addressable cause.
Ship the fix
Builder implements the page, layout, or copy change; Ops handles it when the cause is performance.
Measure honestly
The result is compared to the recorded baseline, and unattributable changes are labelled as such.
What you get
Funnel losses attributed to a specific cause instead of a blended average
Structural problems fixed before micro-testing begins
Changes measured against a recorded pre-change baseline
A continuous loop rather than a quarterly CRO project
Handled by these agents
Works with
Frequently asked questions
Do I need a lot of traffic for this to work?
For diagnosis, no — funnel breakage is visible at modest volume. For A/B testing, yes, and the agent will tell you when your traffic cannot support a conclusion rather than reporting noise as a result.
What is a good conversion rate?
The only useful benchmark is your own trend, segmented. Category averages hide too much — traffic mix, price point, and purchase consideration length move the number more than page quality does.
Does it replace a CRO agency?
It replaces the routine part: diagnosis, implementation, and measurement. Strategic questions — positioning, pricing, what you sell — stay with you.
How quickly do changes show results?
Structural fixes to a high-traffic page can register within days. Catalogue-wide work compounds over weeks. Anything claiming faster than your own sales cycle should be treated sceptically.
Keep reading
A/B testing
Test the genuinely uncertain decisions, sized honestly, instead of testing everything badly.
Improve mobile conversion
Close the mobile gap: thumb-reach reality, speed on real devices, and checkout friction.
Product page optimisation
Rebuild the pages that decide whether a visit becomes an order, ranked by revenue at stake.
E-commerce SEO at scale
Metadata, structured data, and content across a whole catalogue — not just the top twenty pages.
Put the team to work on your store
Connect your storefront, analytics, and email stack, set a goal, and let the agents run the work end to end. Start on the free plan with your own model key.