Causality Engine Feature: Intelligence Adjusted Attribution is a marketing measurement method that uses Bayesian causal inference to determine the true incremental impact of each marketing channel. It moves beyond flawed last-click models to show you exactly how much revenue each channel is generating on its own, without being influenced by other channels.
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Causality Engine Feature: Intelligence Adjusted Attribution
Excerpt: Intelligence Adjusted Attribution is a marketing measurement method that uses Bayesian causal inference to determine the true incremental impact of each marketing channel. It moves beyond flawed last-click models to show you exactly how much revenue each channel is generating on its own, without being influenced by other channels.
Stop guessing what’s working. With Causality Engine, you can finally see your true ROAS and make marketing decisions with confidence. Our Intelligence Adjusted Attribution model gives you a clear picture of your marketing performance, so you can invest in the channels that are actually driving growth.
The Attribution Problem: Why You Can’t Trust Your Data
You know the feeling. Meta tells you it drove 100 sales. Google claims 80. Shopify reports 120. Who do you believe? The truth is, none of them are giving you the full picture. Each platform uses its own attribution model, designed to make its own performance look as good as possible. This is the classic “fox guarding the henhouse” problem. You’re left with a mess of conflicting data, unable to make informed decisions about your marketing budget.
Traditional attribution models, like last-click or multi-touch, are fundamentally flawed. They are rule-based systems that assign credit based on arbitrary rules, not true causality. They can’t account for the complex interplay between channels, or the fact that some channels may be cannibalizing others. The result? You end up over-investing in channels that aren’t actually driving incremental sales, and under-investing in the ones that are.
How Intelligence Adjusted Attribution Works
Causality Engine’s Intelligence Adjusted Attribution is different. We don’t use rule-based models. Instead, we use a sophisticated Bayesian causal inference engine to determine the true incremental impact of each marketing channel. Here’s how it works:
We start by building a causal model of your marketing ecosystem. This model takes into account all of your marketing channels, as well as external factors like seasonality and competitor activity. Then, we use a process called Bayesian inference to update this model with your data. This allows us to determine the probability that a given marketing touchpoint caused a conversion.
Mathematically, we can express this as:
P(Conversion | Touchpoint) = P(Touchpoint | Conversion) * P(Conversion) / P(Touchpoint)
Where:
P(Conversion | Touchpoint) is the probability of a conversion given a touchpoint.
P(Touchpoint | Conversion) is the probability of a touchpoint given a conversion.
P(Conversion) is the prior probability of a conversion.
P(Touchpoint) is the prior probability of a touchpoint.
By calculating this probability for each touchpoint, we can determine the true causal impact of each marketing channel. This allows us to provide you with a much more accurate picture of your marketing performance than traditional attribution models.
Benefits of Intelligence Adjusted Attribution
See Your True ROAS: Stop relying on inflated numbers from ad platforms. Our Intelligence Adjusted Attribution model shows you the true return on ad spend for each of your marketing channels.
Make Better Marketing Decisions: With a clear picture of your marketing performance, you can make informed decisions about where to invest your marketing budget. Stop wasting money on channels that aren’t driving incremental sales.
Refine Your Marketing Mix: Our Refinement Queue tells you exactly what changes to make to your marketing mix to maximize your return on investment. It’s like having a team of data scientists on your side.
Detect Cannibalistic Channels: Are your marketing channels working together, or are they competing with each other? Our Cannibalistic Channel Detection feature helps you identify and eliminate channel overlap, so you can get more out of your marketing budget.
Frequently Asked Questions
1. How is Intelligence Adjusted Attribution different from multi-touch attribution?
Multi-touch attribution is still a rule-based model. It assigns credit to multiple touchpoints in the customer journey, but it does so based on arbitrary rules. Intelligence Adjusted Attribution, on the other hand, uses causal inference to determine the true incremental impact of each marketing channel. It’s a much more accurate and reliable way to measure marketing performance.
2. How do you account for external factors like seasonality?
Our causal model takes into account a wide range of external factors, including seasonality, competitor activity, and even the weather. This allows us to provide you with a much more accurate picture of your marketing performance than traditional attribution models.
3. How long does it take to see results?
You can run your first analysis in just a few minutes. Our one-time analysis gives you a 40-day lookback, so you can see the impact of your marketing efforts over the past month. If you subscribe to our monthly plan, you’ll get a lifetime lookback, as well as access to our LLM chat interface.
4. What is marketing attribution?
Marketing attribution is the process of identifying a set of user actions (“events” or “touchpoints”) that contribute in some manner to a desired outcome, and then assigning a value to each of these events. It is a way of trying to understand which marketing channels are most effective at driving conversions.
5. How can I learn more about Causality Engine?
You can learn more about Causality Engine by visiting our pricing page or by reading our other resources, such as our article on the [/resources/feature-refinement-queue](Refinement Queue).
Related Resources
Causality Engine Feature: Budget Allocation Optimizer
Causality Engine vs. Ruler Analytics: Which Is Worth It?
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Key Terms in This Article
Attribution Model
An Attribution Model defines how credit for conversions is assigned to marketing touchpoints. It dictates how marketing channels receive credit for sales.
Bayesian Inference
Bayesian Inference updates the probability of a hypothesis based on new evidence. It refines marketing attribution by incorporating prior beliefs about channel effectiveness.
Causal Inference
Causal Inference determines the independent, actual effect of a phenomenon within a system, identifying true cause-and-effect relationships.
Causal Model
A Causal Model is a mathematical representation describing the causal relationships between variables, used to reason about and estimate intervention effects.
Customer journey
Customer journey is the path and sequence of interactions customers have with a website. Customers use multiple devices and channels, making a consistent experience crucial.
Marketing Attribution
Marketing attribution assigns credit to marketing touchpoints that contribute to a conversion or sale. Causal inference enhances attribution models by identifying true cause-effect relationships.
Marketing Mix
The marketing mix is the set of actions a company uses to promote its brand or product. It traditionally includes product, price, place, and promotion.
Multi-Touch Attribution
Multi-Touch Attribution assigns credit to multiple marketing touchpoints across the customer journey. It provides a comprehensive view of channel impact on conversions.
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Frequently Asked Questions
How is Intelligence Adjusted Attribution different from multi-touch attribution?
Multi-touch attribution is still a rule-based model. It assigns credit to multiple touchpoints in the customer journey, but it does so based on arbitrary rules. Intelligence Adjusted Attribution, on the other hand, uses causal inference to determine the true incremental impact of each marketing channel. It’s a much more accurate and reliable way to measure marketing performance.
How do you account for external factors like seasonality?
Our causal model takes into account a wide range of external factors, including seasonality, competitor activity, and even the weather. This allows us to provide you with a much more accurate picture of your marketing performance than traditional attribution models.
How long does it take to see results?
You can run your first analysis in just a few minutes. Our one-time analysis gives you a 40-day lookback, so you can see the impact of your marketing efforts over the past month. If you subscribe to our monthly plan, you’ll get a lifetime lookback, as well as access to our LLM chat interface.
What is marketing attribution?
Marketing attribution is the process of identifying a set of user actions (“events” or “touchpoints”) that contribute in some manner to a desired outcome, and then assigning a value to each of these events. It is a way of trying to understand which marketing channels are most effective at driving conversions.
How can I learn more about Causality Engine?
You can learn more about Causality Engine by visiting our [pricing page](/pricing) or by reading our other resources, such as our article on the [/resources/feature-optimization-queue](Optimization Queue).
