Overview
Attribution models determine how conversion credit and revenue are assigned across the marketing touchpoints that influence a customer’s journey. Because customers interact with multiple paid and owned channels before converting, choosing the right attribution model is essential for understanding true performance.
Polar provides a robust set of attribution models designed specifically for modern eCommerce and subscription brands running paid media. These models allow you to evaluate acquisition, retargeting, assist channels, and paid overlap with greater clarity.
In this article, we’ll cover:
What attribution models are and how they work
All attribution models available in Polar
When to use each model
How to interpret paid overlap and impact-based reporting
Section 1: What Is an Attribution Model?
An attribution model defines how conversion credit is distributed across user touchpoints within a defined attribution window.
Why This Matters
A typical journey may look like:
User clicks a TikTok ad
Returns via Google Search
Clicks a Facebook retargeting ad
Converts
Which channel deserves credit?
The answer depends entirely on the attribution model you choose.
Attribution helps you:
Allocate budget effectively
Identify true acquisition drivers
Understand retargeting impact
Avoid double-counting paid performance
Section 2: Standard Multi-Touch Attribution Models
These models distribute credit across all eligible touchpoints in the journey.
1. First Click Attribution
Definition: 100% of credit goes to the first touchpoint in the conversion path.
Best For:
Measuring acquisition effectiveness
Identifying demand-generation channels
Understanding new customer drivers
What It Tells You:
Which channel introduced the customer to your brand.
Limitation:
Ignores nurturing and closing channels.
By default, Polar Pixel metrics (added to Key Indicators) are calculated using the First Click model.
2. Last Click Attribution
Definition: 100% of credit goes to the final touchpoint before conversion.
Best For:
Optimizing performance marketing
Understanding conversion drivers
ROAS-focused decision making
What It Tells You:
Which channel closed the sale.
Limitation:
Undervalues upper-funnel efforts.
3. Linear Attribution
Definition: Credit is distributed evenly across all touchpoints in the journey.
Example:
4 touchpoints = 25% credit each.
Best For:
Balanced multi-channel analysis
Longer consideration cycles
What It Tells You:
How channels collectively contribute to revenue.
4. U-Shaped (Position-Based) Attribution
Definition:
40% credit to the first touchpoint
40% credit to the last touchpoint
20% split across middle touchpoints
Best For:
Businesses that value both acquisition and conversion
Brands running full-funnel strategies
What It Tells You:
Which channels drive awareness and which close.
5. Time Decay Attribution
Definition: Touchpoints closer to the conversion receive more credit than earlier ones.
Best For:
Longer buying cycles
Momentum-driven journeys
What It Tells You:
Which channels accelerate conversion as users move down-funnel.
6. Full Paid Overlap
Definition:
Each paid channel involved in a conversion receives full credit for that conversion.
If three paid channels influenced the sale, each receives 100% credit.
Best For:
Measuring paid channel participation
Identifying overlap across platforms
Understanding blended paid influence
Important:
Totals will exceed 100% because credit is not split.
What It Tells You:
Which paid platforms are present in converting journeys.
7. Full Paid Overlap + Facebook Views
Definition:
Same as Full Paid Overlap, but includes eligible Facebook view-through conversions in addition to click-based touchpoints.
Best For:
Brands running significant Meta spend
Evaluating view-through contribution
Measuring upper-funnel paid exposure
What It Tells You:
The broader influence of paid campaigns, including impressions that contributed to conversions.
9. Full Impact
Definition:
All channels (paid and non-paid) that influenced a conversion receive credit, allocated via a Shapley value computation across the touchpoints in the path.
Best For:
Understanding total channel participation
Identifying assist-heavy channels
Evaluating full ecosystem influence
What It Tells You:
Which channels consistently appear in conversion paths.
Section 3: Attribution Settings
The models above decide how credit is split across the touchpoints in a journey. Three additional settings control which touchpoints are eligible and how the resulting credit is dated. They apply on top of whichever model you select.
Is Paid Only: When enabled, only paid touchpoints are eligible to receive credit. Organic and direct touchpoints are dropped from the path before the model runs. Note that the Full Paid Overlap model already restrict to paid touchpoints by definition. "Is Paid Only" is a toggle you can apply to any model
Lookback Window: The lookback window sets how far back before a conversion a touchpoint can sit and still be eligible for credit. You can choose a fixed number of days or an unlimited window. It changes which touchpoints enter the path, not how credit is split among them.
Cash vs. Accrual: This setting controls the date credit lands on. Cash assigns conversion and revenue credit to the day the order was placed. Accrual assigns it to the day each contributing touchpoint occurred.
For the full detail on all three settings, see Understanding Attribution Settings.
Section 4: Choosing the Right Model
There is no universally “correct” model—each serves a different strategic purpose.
If Your Goal Is…
Goal | Recommended Model |
Identify acquisition drivers | First Click |
Optimize conversion efficiency | Last Click |
Analyze full-funnel contribution | Linear |
Balance awareness & closing | U-Shaped |
Weight recency influence | Time Decay |
Understand paid channel overlap | Full Paid Overlap |
Include Meta view-through impact | Full Paid Overlap + Facebook Views |
Measure total ecosystem participation | Full Impact |
How to Use These Models Strategically
Compare, Don’t Isolate
The real power of Polar comes from comparing models side-by-side.
For example:
A channel strong in First Click but weak in Last Click → Acquisition driver
A channel strong in Last Click but weak in First Click → Retargeting closer
A channel strong in Full Paid Overlap → Frequently assists conversions
A channel strong in Full Impact → Critical ecosystem contributor
Understand Overlap Inflation
Models like Full Paid Overlap and Full Impact intentionally inflate totals. They are not meant for strict ROAS calculations but for participation analysis.
Use them to understand:
Platform cannibalization
Retargeting overlap
Channel redundancy
How to adjust the Attribution Model within Channel Performance.
How to adjust the Attribution Model within a Custom Report.
Conclusion
Attribution modeling is foundational to smart marketing decisions. Polar provides a comprehensive set of models—from traditional First Click and Linear approaches to advanced paid-overlap and full-impact models—so you can analyze performance from every angle.
Key takeaways:
Different models answer different strategic questions.
Multi-touch models distribute credit; overlap models measure participation.
Paid-specific models help you understand cross-platform dynamics.
Comparing models provides deeper insight than relying on a single view.
We recommend regularly reviewing multiple attribution models in Polar to ensure your budget allocation reflects how customers actually convert.
If you have questions about which model best fits your growth strategy, our team is here to help.