Attribution Model Comparison Template: Side by Side Analysis
See exactly how different attribution models tell different stories about your marketing performance. This template allows you to compare last-click, first-click, linear, and, most importantly, causal attribution side-by-side.
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By Joris van Huët, Founder & CEOUpdated 2 min read
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Stop Arguing About Attribution Models. Start Seeing the Truth.
How much time has your team wasted debating the merits of last-click versus first-click attribution? The truth is, you're arguing about which lie is more convenient. All rule-based attribution models are flawed because they rely on arbitrary rules to assign credit, not on a causal understanding of customer behavior. They are simply different ways of looking at the same misleading data.
This Attribution Model Comparison Template is designed to end the debate once and for all.
The Illusion of Precision
Rule-based attribution models give the illusion of precision, but they are built on a foundation of guesswork. This template will help you visualize just how different the story can be depending on which model you choose. You will see how:
- Last-Click over-attributes to bottom-of-funnel channels like branded search and retargeting.
- First-Click over-attributes to top-of-funnel channels, often ignoring the channels that actually nurture the customer to a sale.
- Linear and Time-Decay models simply spread the error around, giving you a false sense of fairness.
The Causal Ground Truth
By comparing the output of the rule-based models to the causal truth, you will be able to:
- Quantify the Error: See exactly how much each model is over- or under-attributing to each channel.
- Educate Your Team: Use the clear, visual comparison to get your entire team aligned on the limitations of rule-based attribution.
- Build a Business Case for Causal Analysis: Use the data to justify a move away from flawed models and towards a more accurate, causal approach.
Stop the endless debates. Download the template and see for yourself how a causal view can change everything.
Related Resources
Agency vs In House Attribution Numbers: Who Is Right
Causality Engine vs. Measured: Incrementality Testing Compared
Last Click vs. Data-Driven Attribution: Which Should You Use?
Frequently asked questions
Why is last-click attribution so common if it's so flawed?
It's simple to understand and easy to implement, but that doesn't make it right. It's a relic of a bygone era of digital marketing. We have a great article on this topic at /resources/the-demise-of-last-click.
Go deeper: Causal attribution, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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Terms in this article
- AttributionAttribution identifies user actions that contribute to a desired outcome and assigns value to each. It reveals which marketing touchpoints drive conversions.
- Attribution ModelAn Attribution Model defines how credit for conversions is assigned to marketing touchpoints. It dictates how marketing channels receive credit for sales.
- Causal AnalysisCausal Analysis identifies true cause-and-effect relationships in data, moving beyond correlation to show how marketing actions directly impact outcomes.
- Causal InferenceCausal inference is the set of methods for estimating how much an outcome changes because of a cause, rather than alongside it. It works by comparing what happened with an estimate of what would have happened without the cause.
- CausalityCausality is the relationship where one event directly causes another, essential for identifying specific actions that drive desired outcomes in marketing.
- IncrementalityIncrementality is the part of an outcome, such as orders or revenue, that a marketing activity caused: the extra results compared with what would have happened without it. It is a causal effect, not the number of conversions credited to a channel.
- Incrementality TestingIncrementality Testing measures the additional impact of a marketing campaign. It compares exposed and control groups to determine causal effect.
- RetargetingRetargeting is online advertising that targets users who have previously interacted with your website or content. Attribution analysis shows the causal role of retargeting in driving conversions and improving ad spend.