Attribution
Identifying which marketing channel 'deserves credit' for a conversion. Models: First-Touch, Last-Touch, Linear, Time-Decay, Data-Driven. Each model tells a different story.
In practice
Attribution is the trickiest problem in marketing. A customer saw a Facebook ad → searched Google → read a blog post → bought directly. Every platform claims credit. Reality: there's no perfect attribution.
Common misconception
'GA4 gives accurate attribution.' Since iOS 14, cookie-based attribution isn't reliable. 20-40% of conversions aren't attributed correctly. Solution: MER (total revenue / total marketing spend).
How to fix it
Attribution numbers don't add up? (1) Compare GA4 vs. Meta vs. Google — the numbers will differ, (2) rely on MER as 'ground truth,' (3) use UTMs for every campaign, (4) consider Northbeam/Triple Whale.
Example
A fashion store: Meta reports a 4.2 ROAS, GA4 reports 40% lower. MER: $90K / $19K = 4.7. High MER → keep going. The attribution debate becomes irrelevant.
Priority
Don't waste hours on attribution in the first 3 months. Calculate MER monthly. Above $15K in monthly spend, invest in an attribution tool.
Related terms
Keep learning. Metrics that touch the same area:
- ConversionAnalyticsA desired action a visitor takes — a purchase, sign-up, form submission. The basis for measuring marketing success.
- Conversion Rate (CR)AnalyticsThe percentage of visitors who completed a desired action. Average: 1-4% for purchases, depending on category.
- ATC – Add To CartAnalyticsThe action where a visitor adds an item to the cart. Average ATC rate: 8-10% of product page visits.
- Cart AbandonmentAnalyticsA customer added an item to the cart but didn't complete the purchase. Average: 70-75%. One of the biggest opportunities.
- Open RateAnalyticsThe percentage of recipients who opened the email. Average: 20-25% in eCommerce.
- Click RateAnalyticsThe percentage of recipients who clicked a link. Average: 2-3%. A CTOR (click-to-open rate) of 10-15% is a good target.
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