Understanding Attribution Models

Attribution models are essential for measuring how your marketing efforts contribute to a conversion. They determine how credit is assigned to different touchpoints in a user’s journey—from the first click to the final purchase.
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Understanding these models helps you make smarter decisions about where to invest your ad budget and how to evaluate campaign success. Tracking the right attribution models affect how you measure true performance, identify over or underperforming campaigns, and finally - justify marketing ROI.
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These models are commonly used and easy to interpret—perfect for getting started with attribution in your business.
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What it is:
100% of the conversion credit goes to the first campaign the user interacted with.
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Best for:
Measuring which campaigns are most effective at driving initial interest and awareness.
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Example:
A user clicks a Meta ad for your Spring Collection but doesn’t purchase right away. A few days later, they click a Google Shopping ad and make a purchase.
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➡ First Touch Attribution gives all the credit to the Meta ad.
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What it is:
100% of the conversion credit goes to the last campaign the user clicked before purchasing.
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Best for:
Understanding which campaigns are best at converting users when they’re ready to buy.
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Example:
A user clicks a TikTok ad introducing your brand, then later sees a Facebook retargeting ad and completes the purchase.
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➡ Last Touch Attribution gives all the credit to the Facebook ad.
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What it is:
Credit is evenly split across all campaigns the user interacted with before converting.
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Best for:
Getting a holistic view of how all your touchpoints contribute to a sale.
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Example:
A user interacts with a Pinterest ad → a Google ad → and finally a Meta ad before buying.
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➡ Linear Attribution splits the credit equally between the three campaigns, giving each ⅓ of the credit.

Once you’ve mastered the basics, these models offer more nuance by accounting for time or influence in a more dynamic way.
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What it is:
Each campaign or ad in a customer’s path to purchase receives 100% of the credit.
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Best for:
Understanding the assist value of every single touchpoint—even if they weren’t the last click.
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Example:
A user clicks 4 campaigns before converting. Each of those 4 campaigns receives 100% credit.
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➡ This model inflates total conversions, but helps you understand which ads play a supporting role.
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What it is:
In Time-Decay Attribution, credit is distributed by decreasing importance based on recency. That means the closer an interaction is to the final purchase, the less credit it receives. Earlier touchpoints are considered more influential in driving the conversion and are weighted more heavily.
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Best for:
Highlighting the value of campaigns that first captured a user's interest, while still assigning some credit to those closer to the final conversion.
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Example:
A user first clicks a Meta ad (10 days before), later engages with a Google ad (3 days before), and finally clicks a TikTok retargeting ad just before converting.
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➡ The Meta ad receives the most credit, Google gets less, and TikTok the least.
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What it is:
Gives 40% credit to both the first and last touchpoints, and distributes the remaining 20% across any middle interactions.
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Best for:
Balancing awareness with conversion influence, while still valuing the journey in between.
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Example:
A user clicks a Meta ad (first), then a Google and Pinterest ad, and finally a TikTok ad (last).
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➡ Meta and TikTok each get 40% credit, while Google and Pinterest get 10% each.

What it is:
Based on cooperative game theory, this model distributes credit fairly across all campaigns by calculating each one’s marginal contribution across every possible combination of touchpoints.
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Best for:
Capturing the value of stable, consistent campaigns and understanding the synergy between them.
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Example:
Even if a campaign isn’t first or last, if it consistently adds value in many different paths to purchase, it will receive meaningful credit.
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What it is:
Each campaign gets 100% of credit, just like Full Credit Attribution, but also incorporates view-through conversions from Facebook.
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Best for:
Capturing upper-funnel influence from video ads and impressions—not just clicks.
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Example:
If a user views your Facebook ad but doesn't click, then later purchases after a different campaign, that view still gets factored into attribution.
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We’ve also developed an additional model that go beyond what’s commonly used in the industry—designed to give deeper insight into the real value of your campaigns.
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​What it is:
A custom model that assigns more credit to higher-impact campaigns, such as:

Best for:
Rewarding campaigns that drive discovery and long-term growth.
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Example:
If a non-branded Google search campaign was first and a branded retargeting ad closed the sale, this model gives more weight to the non-branded one for initiating the journey.
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If you’re unsure which attribution model fits your goals or how to interpret your breakdown:

We’re happy to walk you through your Attribution Laboratory and ensure you get the most value from Le Pixel.
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