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Behavioural analytics for e-commerce

Find where your store loses people — and what fixing it is worth.

Conversionics reads your analytics and your shoppers’ behaviour together, ranks the pages worth your attention, and prices the fix. Where a number has no source it says so, by name. It never shows you a zero it had to invent.

What a finding looks like — example

/checkout/payment · 1,980 sessions · 61% leave at payment · $62.40 average cart

$7,537 / month recoverable

Ten per cent of what leaves that page, not all of it. The product prices what it can defend and shows the inputs — this one is an illustration, because we have no customers to quote yet.

Free while we’re in pilot. No card, no sales call.

This is the screen, not a picture of it

Every tile and bar below is drawn by the same component your Site Overview uses. Only the numbers are different.

Example data — a sample store, not a customer

Revenue$48,235
Average Cart$62.40
Sessions18,940
Bounce41.2%
Page views71,305
Visit time No sourceno session-duration metric is collected
Sessions by page — last 30 days
  • /11,240
  • /collections/sale6,430
  • /basket3,510
  • /checkout/delivery2,460
  • /checkout/payment1,980
Friction score — /checkout/payment64 +33 pts

Rising friction on the page that takes the money. That is the alert, not a report you have to go and read.

A number with no source is never a zero

Look at the Visit time tile above. It does not say 0 and it does not quietly disappear — it says No source and names what is missing. That is not a demo state we staged: nothing in the product records session duration yet, so that is the real answer for every site we have.

Four different answers, four different things on screen: a feature you don’t have yet, a number nobody can measure, a failure, and a real zero. Most tools round all four down to nothing and let you draw the conclusion.

Ad spend & ROAS

No advertising account is connected, so there is no spend to divide revenue by. We will not estimate one.

Unlocks when you connect an ad account.

Three steps to your first priced finding

No sales call, no implementation project. GA4 or Clarity alone is enough to start.

  1. 01Connect a data source

    Google Analytics 4 or Microsoft Clarity — either one lights up the first screens. The tag is optional to start.

  2. 02Pick your store & scope

    The sitemap crawls itself; you choose the pages that carry the money — checkout, basket, the collections that convert.

  3. 03Run the first analysis

    Friction and opportunity, located and priced — and honestly locked where the data is missing.

Every day without the tag is a day you can never analyse

The tag records behaviour raw and resolves the meaning later. Name a button next March and the answer covers every shopper who already clicked it — no backfill, no re-tagging, nothing to configure in advance. The limit is honest and it is 400 days. Tools that make you define a metric before it will count anything lose that time permanently.

It cannot leak what it never collected

Not a policy we could quietly change — there is nothing in the product that could do these things.

All of it written down, including what we cannot undo and the certifications we do not hold — privacy & security.

Free while we’re in pilot

We are taking ten pilot companies. No card, no contract, no per-seat maths — and you will talk to the person who built it rather than to an account manager.

There are no logos on this page and no testimonials, because there are no customers yet. One pilot store is running, and it is one we operate. Inventing the rest would break the only thing that makes the numbers above worth anything.

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