For Dutch Shopify fashion brands scaling from €100K to €300K/month. Upload your GA4 data. Know which channels drive incremental sales in minutes.
€99. Results in minutes. Full refund if you don't see it. 89% stay.
You're spending €120K/year on Pinterest. Lookbooks. Styling inspiration. Product discovery.
Pinterest dashboard says 1.8x ROAS. Meta dashboard says 4.5x. But what if Pinterest creates consideration that Meta converts 7 days later?
The math:
Pinterest "attributed" revenue: €120K × 1.8x = €216K
Pinterest incremental revenue: Test market shows 31% drop = €95K lost
Difference: €95K revenue Pinterest drives but doesn't get credit for.
Cut Pinterest = save €120K, lose €95K revenue, collapse funnel.
Keep Pinterest = justify "low ROAS" to CFO forever.
You're stuck. Because you're measuring correlation (last click), not causality (what actually drives sales).
Traditional attribution (correlation):
Meta had the last click → Meta gets 100% credit → Pinterest shows "low ROAS" → Cut Pinterest → Funnel collapses.
Behavioral intelligence (causality):
Pinterest creates consideration → Instagram drives engagement → Meta converts → That's a 14-day customer journey → Pinterest drives €95K incremental revenue → Keep Pinterest, scale it.
The formula:
Incremental Sales = (Revenue with Channel) - (Revenue without Channel)
Traditional attribution: Measures correlation (which channel touched the customer last)
Behavioral intelligence: Measures causality (which channel drives incremental sales)
95% accuracy vs 30-60% industry standard. 964 companies. 127 Dutch fashion brands already see their real numbers.
Customer saves Pinterest lookbook (Day 1) → Checks Instagram for styling (Day 5) → Clicks Meta retargeting ad (Day 14) → Buys.
Last-click attribution: Meta gets 100% credit. Pinterest shows "low ROAS."
Causal analysis: Pinterest drives 31% of this sale. Cut Pinterest = lose this customer.
Customer sees Instagram post (Day 1) → Saves to Pinterest board (Day 3) → Googles product (Day 10) → Clicks Meta ad (Day 14) → Buys.
Last-click attribution: Meta gets 100% credit. Instagram shows minimal ROI.
Causal analysis: Instagram drives 35% of this sale. Cut Instagram = 42% revenue drop.
Customer watches TikTok styling video (Day 1) → Saves Pinterest lookbook (Day 7) → Clicks Meta retargeting (Day 12) → Buys.
Last-click attribution: Meta gets 100% credit. TikTok shows "low ROAS."
Causal analysis: TikTok drives 28% of this sale. Cut TikTok = lose top-of-funnel awareness.
Pattern: Visual-first channels (Pinterest, Instagram, TikTok) show "low ROAS" in dashboards. But they drive 35-50% of incremental sales through multi-touch paths. Cut them = collapse your funnel.
Food & Beverage: 1-3 days. Beauty: 14-30 days. Fashion: 7-21 days. Multiple touchpoints across Pinterest, Instagram, TikTok before conversion. Last-click gives 100% credit to the final touchpoint, ignoring 4-8 prior interactions.
85% of fashion purchases start with inspiration content (Pinterest, Instagram, TikTok). But inspiration channels show "low ROAS" because they create consideration, not conversions. Cut them = kill product discovery.
Summer collections, winter collections, holiday sales. Demand spikes 3-5x during seasons. Attribution breaks during spikes because consideration cycles compress from 14 days to 3 days. Last-click over-credits conversion channels, under-credits inspiration channels.
Customers don't buy products. They buy outfits. Pinterest shows styling → Instagram shows social proof → Customer buys 3 items. Last-click gives 100% credit to Meta retargeting. But Pinterest created the outfit idea. Cut Pinterest = 31% revenue drop.
Bottom line: Fashion brands have inspiration-driven discovery, seasonal spikes, and styling-context purchases. Traditional attribution fails hardest here. Causal analysis works best here.
320%
Average ROI increase after seeing real attribution
95%
Accuracy vs 30-60% industry standard
89%
Stay because the data is undeniable
964 companies switched to behavioral intelligence. Not because we're great salespeople. Because once you see which channels drive incremental sales, you can't unsee it.
Pinterest creates consideration that Meta converts 7-14 days later. Last-click attribution gives 100% credit to Meta, but Pinterest started the customer journey. Formula: Incremental Sales = Revenue with Pinterest - Revenue without Pinterest. Cut Pinterest = 31% revenue drop in 14 days.
Upload your GA4 CSV and get causal inference analysis in minutes. Measures incremental sales: Revenue with Pinterest - Revenue without Pinterest. If Pinterest drives consideration that feeds Meta/Google conversions 7-14 days later, cutting it collapses the funnel. If Pinterest steals credit, cutting saves money. 95% accuracy.
Correlation: Meta had the last click, so it gets 100% credit (wrong). Causality: Pinterest created consideration → Instagram drove engagement → Meta converted (right). Causal analysis shows which channels drive incremental sales. Traditional attribution measures correlation. Behavioral intelligence measures causality.
Instagram creates engagement that converts 7-14 days later through other channels. Last-click attribution gives 100% credit to Meta/Google, minimal to Instagram. But cut Instagram? Revenue drops 35-42% in 14 days. Causal analysis reveals the true impact.
Yes. Upload your GA4 CSV and get results in minutes. Connect Shopify to enhance the analysis with revenue data. Requires 3+ months of historical data. 127 Dutch fashion brands already use it.
€99 one-time analysis. Upload your data, get results in minutes. If you don't see which channels drive incremental sales, full refund. No questions. 89% continue because the data is undeniable. Subscription: €299/month for continuous tracking.
Not guesses. Not correlations. Upload your GA4 data and see the real numbers in minutes.
Start now€99. Results in minutes. Full refund if you don't see it. 127 Dutch fashion brands already know.
