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    from raw data to a shipped change

    prove marketing ROI, one change at a time.

    The question from finance is never “what did the dashboard say”. It's “what did that change return”. Cogny gives every change a ticket and a verdict, measured in your own GA4, shop and CRM data, so the answer is a list, not a guess.

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    or from your own AI

    claude mcp add --transport http cogny https://app.cogny.com/mcp

    what AI marketing ROI means, and why last-click numbers lie

    AI marketing ROI is using an agent to connect what you spent and what you changed to what came back. Platform-reported conversions overlap and double-count. Last-click reports credit whoever touched the customer last. Neither tells you whether the budget shift you made on Tuesday was worth it.

    Cogny connects your ad platforms, analytics, shop and CRM, 72 integrations in all, and reads them together. Every change you ship in the Cogny app becomes a ticket, as do launches from your own AI (it offers to register other changes), and each ticket is measured against the outcome you trust: purchases in GA4, revenue in Shopify, deals in your CRM. Three days after an ads change, seven after content or SEO, it closes with a verdict.

    That doesn't give you a multi-touch attribution model. It gives you something a CFO can read: what was changed, when, by whom, what it was supposed to move, and whether it did. On Cloud, scheduled reports from over 70 templates put that on the calendar, and the BigQuery warehouse keeps the raw history.

    What was changed, by whom, what it should have moved, and whether it did.

    why most marketing teams can't prove their impact

    • Attribution black box

      Many touchpoints, conflicting sources, and no line from a decision to revenue.

    • Spreadsheet reporting

      Hours each week pulling Google, Meta, LinkedIn and CRM into one sheet that is stale by Friday.

    • Channel silos

      Each platform claims credit for the same conversion, so the totals add up to more than the business made.

    • The CFO question

      “What did we get for that spend?” Vanity metrics don't answer it.

    from scattered data to a record finance can read

    1. 01

      Connect

      Ad platforms, GA4, Search Console, your shop and CRM.

    2. 02

      Change

      Every change is proposed, approved and shipped as a ticket, with who authorised it.

    3. 03

      Measure

      Three or seven days later, before against after in the outcome you trust.

    4. 04

      Report

      The verdicts add up: a ledger of what returned and what didn't, plus scheduled reports on Cloud.

    ROI as a ledger, not a dashboard

    changeshipped inmeasured inresult
    Move budget from display to searchshipped in Google Adsmeasured in Shopify revenue · 3 daysROAS 2.1 → 2.6worked
    LinkedIn conversation ads to CFO titlesshipped in LinkedIn Adsmeasured in CRM pipeline · 3 days+2 opportunitiespartial
    Discount banner on collection pagesshipped in Shopifymeasured in GA4 margin · 7 daysorders up, margin downdidn't work

    Example rows, not customer data.

    from guesswork to a record of impact

    • Spend read against revenue

      Ad platforms joined to GA4, your shop and your CRM, so a change is judged on money, not clicks.

    • Every change on the record

      Each write is logged with the tool, the time, the result and who authorised it.

    • Scheduled reports (Cloud)

      Over 70 report templates on a schedule, built from the same connected data.

    • A BigQuery warehouse (Cloud)

      The raw history, kept in a warehouse you can query yourself.

    where AI marketing ROI changes the conversation with finance

    • B2B pipeline

      Long cycles make last-click useless. Cogny reads ad platforms against pipeline in the CRM, so a channel is judged on the deals it influences. A published B2B fintech case shows +53% influenced pipeline at the same spend.

    • E-commerce revenue

      Cogny reads ad spend against orders and revenue in your shop, not platform conversions. A discount that lifts orders and cuts margin shows up as what it is.

    • The quarterly review

      Instead of a deck about channels, you bring the ledger: every change shipped this quarter, what it was meant to move, and its verdict. Wins and misses in one list.

    what it doesn't do

    • It doesn't build a multi-touch attribution model or a forecast. It measures the changes you make.
    • It doesn't replace your BI tool's history. It adds a record of decisions and their results.
    • It doesn't claim results it can't see: if there is no baseline, the verdict is inconclusive.

    the record.

    Published case studies, each one linked.

    +53%influenced pipeline at the same spend levelLinkedIn data + CRM · 2026 YTDB2B fintech →50%of orders from organic search after six months, zero ad spendGA4 · Feb–Aug 2026Scandinavian activewear brand →

    what it costs.

    • Free $015 MCP calls a month and 50 one-time chat credits, no card
    • Solo $9unmetered in your own AI, fair use
    • Cogny AI $18150 credits
    • Cogny Pro $901,500 credits
    • Cloud $4995,000 credits, for teams

    Per month. Solo, Cogny AI and Cogny Pro have one seat each. Every change is recorded on every plan; Solo measures 3 a month, Cogny AI and Pro measure every one and add monthly credits. Teams need Cloud. Compare plans →

    what did that change return?

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