Monthly Marketing Report Template with Attribution Data
Stop guessing your monthly marketing performance. This template integrates Bayesian attribution data to reveal the true incremental value of your channels, helping you make smarter budget decisions.
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By Joris van Huët, Founder & CEOUpdated 2 min read
Stop Reporting on Vanity Metrics
Your standard monthly marketing report is likely misleading you. It tells you about clicks, impressions, and maybe even last-click conversions, but it fails to answer the most critical question: which of your marketing efforts are actually generating new customers and which are just taking credit for sales that would have happened anyway? This is the fundamental flaw of rule-based marketing attribution.
This Monthly Marketing Report Template provides a clear, actionable view of your marketing performance. It moves beyond simple correlation and measures true causality, showing you the incremental lift each channel delivers. For Shopify brands in beauty, fashion, and supplements, this means you can finally quantify the real ROI of your ad spend and stop wasting money on underperforming campaigns.
The Problem with Standard Reports
Most marketing reports are built on a foundation of flawed data. They use attribution models like last-click or multi-touch that arbitrarily assign credit based on rules, not on causal impact. This leads to:
- Over-attributing to retargeting and branded search: These channels often get credit for customers who were already going to buy.
- Under-attributing to top-of-funnel awareness: The channels that introduce new customers often get ignored because they don't directly lead to a conversion.
- Inability to detect cannibalization: You might be paying multiple channels to fight over the same customer, eroding your margins.
A Better Way
Causality Engine uses causal inference on the GA4 history you already have to estimate what each channel caused.
Stop making decisions in the dark. Use this template to build a monthly report that drives growth, not just reports on it. Download the template to get started.
Related Resources
Frequently asked questions
How is this different from a standard Google Analytics report?
Standard reports use rule-based attribution (like last-click), which often misattributes sales. This template uses data from our causal inference engine to show the *incremental* revenue each channel generates, providing a much more accurate picture of performance.Do I need to be a Causality Engine customer to use this?
You can get a one-time analysis for €99. Learn more on our /pricing page.What is Bayesian causal inference?
It's a statistical method that allows us to determine the cause-and-effect relationships in your marketing data. Instead of just looking at correlations, we can determine the actual causal impact of each channel on your sales. We have more information in our /resources/what-is-causal-inference.
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 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.
- CorrelationCorrelation is a statistical measure showing a relationship between variables; it does not imply causation.
- Marketing AttributionMarketing attribution assigns credit to marketing touchpoints that contribute to a conversion or sale. Causal inference enhances attribution models by identifying true cause-effect relationships.
- 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.
- Vanity MetricVanity Metric is a data point that appears impressive but does not measure actual business success. It lacks a clear causal link to business objectives.
- Vanity MetricsVanity Metrics are measurements that look good but do not provide insight into business performance or aid decision-making. They do not reflect true impact.