How do you use an AI agent to find your biggest funnel leak?
Short answer: Point an AI agent at one analytics export inside a ChatGPT or Claude workspace; have it compute each funnel step's conversion rate, compare each against benchmark, then rank the shortfalls by the euros freed if closed. The biggest leak is the step with the largest priced gap, not the lowest-looking rate.
The method, in one pass
Point an AI agent at one analytics export, have it compute each funnel step's conversion rate, compare each against benchmark, then rank the shortfalls by the euros freed if closed. The biggest leak is the step with the largest priced gap, not the lowest-looking rate. Copy is written last, and only for that one step.
The order matters. Most funnel reviews stop at the worst-looking percentage and start rewriting there. Pricing every step first moves the work to the leak that actually forfeits the most contribution.
| Funnel step | Current rate | vs benchmark | Euro value of closing it |
|---|---|---|---|
| Session → product view | 46% | +2 pp | — |
| Product view → add-to-cart | 9% | −3 pp | €1,900 |
| Add-to-cart → checkout | 38% | −14 pp | €2,100 |
| Checkout → orderBiggest leak | 68% | −7 pp | €6,800 |
Fix the priced leak, not the worst-looking rate. Add-to-cart → checkout shows the largest gap (−14 pp), but checkout → order forfeits the most euros. Rank by euros freed, then write copy for that one step.
What data does the agent need?
One CSV covering the full funnel: sessions, product views, add-to-cart, checkout starts, orders and returns, ideally split by period and device. Each column becomes a step; each step yields a rate. No tracking pixels, integrations or API keys are required — an export from the existing analytics tool is enough to run the walk.
How does it decide which step is leaking the most?
By two tests at once: which step sits furthest below its benchmark rate, and which shortfall carries the highest euro value once downstream rates and contribution per order are applied. A step can look dreadful yet leak little; another can look fine yet cost the most. Only the priced ranking settles it.
How does it price the leak in euros?
Multiply the percentage-point gap to benchmark by the volume entering that step, then by the downstream step rates, then by contribution per order. That chain converts a soft conversion-rate gap into a hard number: the euros a single step forfeits per period. Ranking every step this way surfaces the one worth fixing first.
Why price the leak before writing copy?
Because copy is cheap to write and expensive to aim wrongly. Pricing every step first directs effort at the one leak whose closure returns the most euros, not the step that reads worst or complains loudest. Without a euro figure, rewriting risks polishing a step that was never the constraint on orders.
What if the leak is not a copy problem?
Then copy is the wrong tool, and the priced diagnosis says so. A checkout leaking at payment may signal shipping cost, limited methods or a technical fault, not weak wording. The agent flags where the euros sit; a step failing on friction or price gets an operational fix, not a headline.
What this does not tell you
A priced ranking names the most expensive leak; it does not prove a rewrite will close it. Benchmarks are directional, not laws — a niche catalogue or a considered-purchase basket can sit below a generic benchmark and still be healthy. The method also assumes the export is clean: mislabelled steps, bot sessions or double-counted checkouts will mis-price the leak. And a single period can mislead; a seasonal spike or a paid campaign can move one step for reasons no copy change will hold. Treat the euro figure as a prioritisation, then verify with a controlled change before crediting the fix.
FAQ
How do you use an AI agent to find your biggest funnel leak?
Point an AI agent at one analytics export inside a ChatGPT or Claude workspace; have it compute each funnel step's conversion rate, compare each against benchmark, then rank the shortfalls by the euros freed if closed. The biggest leak is the step with the largest priced gap, not the lowest-looking rate.
What data does the agent need?
One CSV covering the full funnel: sessions, product views, add-to-cart, checkout starts, orders and returns, ideally split by period and device. Each column becomes a step; each step yields a rate. No tracking pixels, integrations or API keys are required.
How does it decide which step is leaking the most?
By two tests at once: which step sits furthest below its benchmark rate, and which shortfall carries the highest euro value once downstream rates and contribution per order are applied. Only the priced ranking settles it.
How does it price the leak in euros?
Multiply the percentage-point gap to benchmark by the volume entering that step, then by the downstream step rates, then by contribution per order. That chain converts a soft rate gap into the euros a single step forfeits per period.
Cocoon Productions, E-Commerce Agent Workflow method (analytics CSV to margin walk, affordable-CAC ceiling and priced funnel gap). Figures in the visual are illustrative, not client data.
