What Is Marketing Attribution? (The “Who Gets the Credit?” Problem)
Imagine a soccer team scores a goal.
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Player A stole the ball.
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Player B passed it down the field.
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Player C kicked it into the net.
Who gets the credit for the goal? In most stats, Player C gets the point. But the coach knows that without Player A and B, the goal never would have happened.
Marketing Attribution is the science of assigning credit to the specific marketing channels (touchpoints) that contributed to a sale. In the complex digital world, a customer might interact with your brand 20 times before buying. Attribution models help you decide how much “credit” (and therefore budget) to give to Facebook, Google, Email, or SEO.
I will break down the different models, why the default settings are usually wrong, and the “Dark Social” problem that is breaking tracking today.
The Problem: The Messy Customer Journey
In 2010, the journey was simple: Search Google -> Buy. In 2025, the journey looks like this:
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See an Instagram Ad on mobile (Don’t click).
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Search the brand on Google on a laptop 3 days later.
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Read a blog post (SEO).
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Sign up for the newsletter.
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Click a link in an email one week later and buy.
If you look at Google Analytics, it will likely say “Email” generated the sale. If you look at Facebook Ads Manager, it will claim it generated the sale because it showed the ad. This discrepancy is why you need an Attribution Model.
The Common Attribution Models
Different models tell different stories about your data.
1. Last Click Attribution (The Default)
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How it works: 100% of the credit goes to the very last thing the user clicked before buying.
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The Pros: Easy to track; standard in Google Analytics 3 (UA).
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The Cons: It ignores the top of the funnel. It makes Google Search/Email look like heroes and makes Social Media/Content look like failures.
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Analogy: Giving the goal credit only to the striker, ignoring the assist.
2. First Click Attribution
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How it works: 100% of the credit goes to the first channel that introduced the user to the brand.
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The Pros: Great for understanding “Discovery” and “Awareness.”
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The Cons: It ignores the nurturing process.
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Analogy: Giving the goal credit only to the player who stole the ball.
3. Linear Attribution
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How it works: Every touchpoint gets equal credit. (e.g., If there were 4 touches, each gets 25% of the sale).
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The Pros: More balanced.
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The Cons: It assumes everything was equally important, which is rarely true.
4. Time Decay Attribution
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How it works: Touchpoints closer to the sale get more credit than those further away.
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The Logic: The click 5 minutes before the sale is worth more than the click 5 months ago.
5. Data-Driven Attribution (The Gold Standard)
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How it works: Google uses AI to compare the paths of users who converted vs. those who didn’t, assigning custom weight to each channel based on its actual impact.
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Note: This is the default in the new Google Analytics 4 (GA4).
The Modern Crisis: iOS 14 and “Signal Loss”
Attribution relies on tracking users (Cookies/Pixel) as they move across the web. However, with Apple’s iOS 14 update and the death of third-party cookies, tracking is breaking.
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The Issue: If a user on an iPhone sees a Facebook ad, then opens Safari to buy, Apple blocks the connection. Facebook cannot claim credit for that sale.
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The Result: Ad platforms are “under-reporting” success. Your ads might be working, but the attribution software can’t “see” the link.
What Is “Dark Social”?
This is the blind spot of attribution. If I copy a link to a product and send it to you via WhatsApp or Discord, and you buy it:
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Attribution Software says: “Direct Traffic” (User typed the URL).
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Reality: It was Word of Mouth / Social sharing. Attribution tools cannot track private messaging apps, leading to an over-estimation of “Direct” traffic.
Conclusion
There is no “perfect” attribution model. “Last Click” tells you what closed the deal; “First Click” tells you what started it. Smart marketers do not rely on just one view; they look at the whole picture to understand the full story of their marketing funnel.