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Saved on Pinterest.
Credited to Meta.

For fashion brands on GA4, on any store platform. Upload your GA4 export and see what Pinterest, Instagram, Meta and every other channel caused, next to what last-click gave it, in 1–2 minutes.

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Full refund within 30 days, no questions asked. You keep the read. Prices exclude VAT.

One path, illustrated
  1. Saves a look on PinterestLast-click credit: 0%
  2. Follows the brand on InstagramLast-click credit: 0%
  3. Searches the product on GoogleLast-click credit: 0%
  4. Clicks a Meta ad and buysLast-click credit: 100%

Last-click pays the final step and nothing else. The causal read asks what each step caused.

Why fashion attribution breaks. The pin that started it never gets the click.

Fashion buyers browse, save and compare, often on a phone and then a laptop, before one ad finally gets the click. Last-click hands that ad the whole sale.

So Pinterest and Instagram look like poor spend and the closing Meta ad looks like your best. Cut discovery on that evidence and next season's Meta sales have less to close.

  • Saves are not clicks

    A saved pin or a liked Reel can start a purchase that ends days later on another channel. Last-click only sees the end.

  • Seasons move the mix

    Collections, drops and sales change which channels matter from month to month, so a credit rule set once goes stale.

  • Phone to laptop to phone

    Buyers browse on one device and buy on another. When the thread breaks, last-click fills the gap with whatever touched the sale last.

The causal read asks a different question. What would sales have been without it?

Last-click asks who touched the sale last. The causal read estimates, from the GA4 history you already have, what sales would have been without each channel: incremental sales are sales with the channel minus sales without it.

The math, as an illustration:

  1. Pinterest costs €8,000 a month. Last-click credits it with €6,000 in sales: 0.75x, a clear candidate to cut.
  2. Switch it off and total sales fall by €24,000 a month, because the Instagram follows, searches and Meta clicks it started stop too.
  3. So Pinterest caused €24,000 on €8,000 of spend: 3.0x.

Last-click said cut it. The counterfactual says it pays for itself three times over. When a channel's sales would have happened anyway, the read says that too.

Illustrative round numbers, not a customer result. Your own read shows your channels.

What it answers for fashion brands

  • Is Pinterest driving sales, or just collecting saves?
  • Is paid social selling, or collecting credit for buyers who were already coming?
  • Where should the next euro go before the next drop?

Every channel gets a data-health score from 0 to 100 and a next step. A channel under 1% of credit on both methods is called too small to act on, not guessed at. How the read works.

This is what €99 buys. Your read, channel by channel.

Direct split back to the channels that sent those buyers. Last-click next to the engine. A data-health score and a next step for every channel.

31%

of last-click credit sat on Direct.

Direct is not a channel. The read splits it back.

Illustrative sample

Where Direct’s credit goes: Organic Search +9, Email +8, Paid Search +6, Paid Social +4, Cross-network +4

Last-click, Direct left outEngine, after the splitData health, 0 to 100
  1. Paid SearchAgrees
    Last-click, Direct left out: 34%
    Engine, after the split: 31%

    Data health 96

    Within 25% of last-click. Hold.

  2. Paid SocialEngine lower
    Last-click, Direct left out: 22%
    Engine, after the split: 14%

    Data health 93

    Cut spend a little in one region. Compare revenue after 14 days.

  3. Organic SearchAgrees
    Last-click, Direct left out: 18%
    Engine, after the split: 21%

    Data health 97

    Within 25% of last-click. Hold.

  4. EmailEngine higher
    Last-click, Direct left out: 11%
    Engine, after the split: 19%

    Data health 91

    Put a little more effort here. Judge it after 21 days.

  5. Cross-networkEngine higher
    Last-click, Direct left out: 9%
    Engine, after the split: 12.4%

    Data health 81

    Raise spend a little in one region. Compare revenue after 21 days. Data health under 90: move in steps.

  6. UnassignedFix tagging
    Last-click, Direct left out: 5.4%
    Engine, after the split: 2.1%

    Data health n/a

    No tracked source. Tag every link with a UTM source and medium, then run a new read.

  7. ReferralToo small
    Last-click, Direct left out: 0.6%
    Engine, after the split: 0.5%

    Data health 88

    Under 1% on both methods. Too small to act on.

Round numbers for illustration, not a customer’s read. Your read shows your own channels from your GA4 export, with your common paths to purchase and receipts that check every number against the file.

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Named results. Published with each brand's sign-off.

Three Dutch fashion brands so far. The read works the same way on any GA4 export, whatever you sell.

Read all five case studies

Fashion attribution, question by question.

  • Why does Pinterest show a lower ROAS than Meta for my fashion brand?
    Because Pinterest usually works at the start of a fashion purchase and Meta often at the end. A saved pin rarely produces the last click, so last-click hands the sale to the ad that closed it. A causal read estimates what sales would have been without Pinterest, sales with the channel minus sales without it, and sets that number next to what last-click gave it.
  • How do I know if cutting Pinterest will hurt sales or save money?
    Run a causal read before you cut. It estimates what each channel caused from your GA4 history, so you see whether Pinterest starts sales that Instagram, search and Meta close later, or collects credit for sales that would happen anyway. The Two Sisters asked exactly this: last-click said cut Pinterest, and the causal read kept it live.
  • What is the difference between correlation and causality in fashion marketing attribution?
    Correlation is what last-click measures: which channel was present at the sale. Causality is what a budget needs: which channel made the sale happen. A Meta retargeting ad can sit next to many fashion sales and cause few; a Pinterest board can sit next to few and cause many. Causal attribution estimates the second.
  • Can I see which channels drive sales for my Shopify fashion brand with GA4 data?
    Yes. The read runs on a GA4 export, so it works for a Shopify fashion brand and for any other store platform GA4 tracks. Upload a GA4 export (12 months or more reads best) and get a per-channel causal read in 1–2 minutes. No app to install, no pixel, no code.
  • How much does attribution analysis cost for my Shopify fashion brand?
    €99 once for a causal read on a GA4 export, refundable within 30 days, no questions asked. Pro is €299 a month, billed monthly, cancel any time, with automated GA4 ingestion and a lifetime look-back. Prices exclude VAT.
  • Why does Instagram show low ROAS but cutting it hurts my sales?
    Because Instagram often starts or warms a purchase that another channel closes. Last-click credits the close, so Instagram looks weak until you switch it off and the sales it was feeding slow down. A causal read estimates that effect in advance, from your GA4 history, instead of making you learn it by cutting.

Keep reading. The terms and comparisons behind this page.

New to the method? Start with causal attribution or why last-click misleads.

Your platforms guess.
We run the math.

Upload a GA4 export and see what each channel caused, next to last-click, in 1–2 minutes. The read is yours to keep.

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The free finding runs in your browser. Your file never leaves it. The full read is €99, refundable within 30 days, no questions asked. Prices exclude VAT.