Attribution
Ecommerce
The Complete Guide to Marketing Attribution for E-commerce Brands in 2025
Last Updated: October 13, 2025
Right. Let's talk about the elephant in the room.
You're spending £50K a month on ads. Meta says you're crushing it—4.2x ROAS, baby! Google Ads? Even better—5.1x. TikTok's chiming in with a respectable 3.8x. By their math, you should be swimming in cash.
Except your bank account tells a different story. Your actual blended ROAS? Maybe 2.3x if you're lucky. And you're sitting there wondering if you've somehow broken mathematics.
You haven't. Welcome to the attribution crisis—where every platform takes credit for the same sale, and you're left holding the bag.
Here's what we're going to fix today.
Marketing attribution is figuring out which of your marketing touchpoints actually convinced someone to buy your stuff.
Not which ones happened to be nearby when they bought. Not which ones correlate with purchases. Which ones caused the purchase.
Think of it this way: A customer sees your TikTok ad. Clicks through. Leaves. Two days later, sees a Meta retargeting ad. Clicks again. Abandons cart. Then Googles your brand name, clicks your ad, and finally buys.
Quick question: Which channel gets credit?
If you answered "all of them, apparently," you're starting to understand the problem.
The average e-commerce customer touches 7–13 points before buying. That's seven opportunities for platforms to claim credit.
Without proper attribution, you're making decisions in the dark:
It's like playing darts blindfolded while three people shout contradictory directions. Entertaining, perhaps. Profitable? Not so much.
Here's the uncomfortable bit.
Meta says your ROAS is 4.2x. Google says 5.1x. TikTok claims 3.8x. Add those up and you should be printing money. But your actual blended ROAS? 2.1x.
This isn't a conspiracy. It's just how attribution works when everyone uses last-click attribution — meaning whoever got the last click before purchase takes full credit.
The problem? Multiple platforms can claim credit for the same bloody sale.
In 2021, Apple decided to make things interesting with App Tracking Transparency (ATT). Now platforms can't track iOS users without explicit permission. And guess what? Only 15–25% of people opt in.
The result? Your Meta dashboard is missing 40–60% of conversions. Google's missing 20–30%. And you're making budget decisions based on data with more holes than Swiss cheese.
Brilliant.
Multi-touch attribution (MTA) gives credit to multiple touchpoints in the customer journey — not just the last one.
Instead of one channel hogging 100% of the credit, attribution gets distributed based on each touchpoint's actual contribution. Revolutionary, I know.
What it does: Gives 100% credit to the first touchpoint that introduced the customer to your brand.
Best for: Measuring awareness channels (TikTok, YouTube, influencers)
The catch: Ignores everything that happened after. Like judging a film by the opening credits.
What it does: Gives 100% credit to the last touchpoint before purchase.
Best for: Quick decisions, simple funnels
The catch: This is what platform dashboards use — and why they over-report ROAS.
What it does: Distributes credit equally across all touchpoints.
Best for: Understanding the full customer journey
The catch: Treats all touchpoints as equally important. Spoiler: they're not.
What it does: Gives more credit to touchpoints closer to the conversion.
Best for: Longer sales cycles where recent interactions matter more
The catch: Undervalues awareness touchpoints that started the whole thing.
What it does: Gives 40% credit to first touch, 40% to last, and 20% across the middle.
Best for: Balancing awareness and conversion optimization
The catch: Arbitrary weighting — but a decent starting point.
What it does: Uses machine learning to assign credit based on real conversion patterns.
Best for: Brands with 1,000+ conversions/month
The catch: Requires data volume and technical setup.
The king of e-commerce metrics.
Formula: Revenue from Ads ÷ Ad Spend
Example: Spend £10,000 on Meta Ads → generate £42,000 in attributed revenue → ROAS = 4.2x.
What’s good?
Formula: Total Marketing Spend ÷ New Customers
Should be less than 30% of LTV — or you’re losing money.
Formula: Average Order Value × Purchase Frequency × Lifespan
Example: £80 × 3 × 2 years = £480 LTV
Blended ROAS: Total revenue ÷ Total ad spend. The truth.
Channel ROAS: Revenue per channel ÷ Spend per channel. Always inflated.
Trust blended. Question channel.
Channels: TikTok, Instagram, YouTube, influencers, display ads
Goal: Introduce your brand
Attribution challenge: Rarely get credit in last-click models
Channels: Retargeting, email, SMS, organic
Goal: Build trust
Attribution challenge: Hard to isolate impact
Channels: Google Search, direct, email, cart abandonment
Goal: Close the sale
Attribution challenge: Gets all the credit, despite earlier work.
Pros: Easy to implement
Cons: Broken by iOS14, cookies, ad blockers
Pros: Accurate, privacy-safe
Cons: Technical setup required
Impact: 10–30% more attributed conversions.
Use consistent naming! Example:yourstore.com/?utm_source=tiktok&utm_medium=paid&utm_campaign=spring_sale
Choose position-based attribution to start. Move to data-driven once you scale.
Connect:
Analyze weekly. Optimize budget.
Incrementality testing = measure what happens without your ads.
Example: Test group converts 3%, control 2%. That 1% is your real impact.
Causal inference = using data to prove cause-and-effect, not just correlation.
Combines multi-touch data + incrementality + ML models → reality-based attribution.
Close the gap between platform fantasy and financial reality.
Attribution vs Analytics?
Analytics = what happened. Attribution = why it happened.
Cost of software?
£50–200/month basic, £1K–5K+ enterprise.
Can I do it without tools?
Yes, but limited. GA4 helps. Tools are better once you spend £10K+/month.
Implementation time?
1–2 weeks basic, 4–8 weeks full setup.
Minimum data?
100 conversions/month for MTA, 1,000+ for data-driven.
Influencer attribution?
Use unique codes + UTM links.
First-party or third-party?
First-party = accurate. Third-party = convenient but flawed.
Offline sales?
Use promo codes, checkout surveys, or CRM matching.
Ready to see which marketing channels actually drive revenue?
Causality Engine shows you exactly which touchpoints matter — not just which ones were nearby.
