For Dutch Shopify fashion brands scaling from €150K to €500K/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 €150K/year on Pinterest. Lookbook pins. Shopping ads. Style inspiration.
Pinterest dashboard says 1.8x ROAS. Meta dashboard says 4.5x. But what if Pinterest creates consideration that Meta converts days later?
The math:
Pinterest "attributed" revenue: €150K × 1.8x = €270K
Pinterest incremental revenue: Test market shows 31% drop = €120K lost
Difference: €120K revenue Pinterest drives but doesn't get credit for.
Cut Pinterest = save €150K, lose €120K 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 €120K 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) → Follows brand on Instagram (Day 3) → Clicks Meta retargeting ad (Day 7) → 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 Reel (Day 1) → Googles brand (Day 4) → Clicks Meta retargeting ad (Day 7) → Buys.
Last-click attribution: Meta gets 100% credit. Instagram shows minimal ROAS.
Causal analysis: Instagram drives 35% of this sale. Cut Instagram = 35% revenue drop.
Customer sees TikTok trend (Day 1) → Saves to Pinterest (Day 3) → Googles product (Day 5) → Clicks Meta ad (Day 7) → Buys.
Last-click attribution: Meta gets 100% credit. TikTok and Pinterest show "low ROAS."
Causal analysis: TikTok + Pinterest drive 42% of this sale. Cut them = collapse top-of-funnel.
Pattern: Visual-first channels (Pinterest, Instagram, TikTok) show "low ROAS" in dashboards. But they drive 40-55% of incremental sales through multi-touch paths. Cut them = collapse your funnel.
Fashion moves fast: 3-7 day purchase cycles with 4-8 touchpoints. Last-click gives 100% credit to the final touchpoint, ignoring the visual discovery that started the journey.
85% of fashion purchases start with visual content (Pinterest, Instagram, TikTok). But visual channels show "low ROAS" because they create consideration, not conversions. Cut them = kill product discovery.
Fashion has 4-6 seasons per year. Attribution models trained on spring data fail in winter. Channel effectiveness shifts with seasons. Static attribution models can't keep up.
Fashion customers browse on mobile (Instagram, TikTok), save on desktop (Pinterest), and buy on mobile (Meta ad). Cross-device journeys break last-click attribution completely.
Bottom line: Fashion brands have the most visual-first discovery, fastest consideration cycles, and highest cross-platform shopping. Traditional attribution misses 40-55% of the picture. Causal analysis captures it.
310%
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.
Defines how credit for conversions is assigned to marketing touchpoints.
Measures the revenue earned for every dollar spent on advertising.
Determines the independent, actual effect of a phenomenon within a system.
A statistical measure showing a relationship between variables; it does not imply causation.
Assigns all credit for a conversion to the final marketing touchpoint.
Assigns credit to multiple marketing touchpoints across the customer journey.
Describes the customer's journey from initial awareness to purchase.
The cost to convince a consumer to buy a product or service.
Predicts the net profit from a customer's entire future relationship.
Determines how different marketing channels contribute to customer conversions.
Gives 100% of conversion credit to the first marketing touchpoint.
Feature comparison for e-commerce attribution
Enterprise attribution comparison
Multi-channel attribution comparison
Ad tracking attribution comparison
Revenue attribution comparison
Why fashion brands need causal attribution
Track the full Pinterest customer journey
How much are you wasting on misattributed spend?
The correlation vs causation problem explained
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.
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.
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.
Not guesses. Not correlations. Upload your GA4 data and see the real numbers in minutes.
Book a Demo€99. Results in minutes. Full refund if you don't see it. 127 Dutch fashion brands already know.