Metrics

Attribution Inflation

The percentage by which reported ROAS exceeds true ROAS due to attribution errors and false positives.

Attribution Inflation quantifies how much advertising platforms over-report performance. Calculated as: (Reported ROAS - True ROAS) / True ROAS × 100%. Example: Meta reports 5.63x ROAS, Shopify shows actual 4.00x ROAS → 40.6% inflation. Causes include view-through attribution pollution, last-click bias stealing credit from earlier touchpoints, manual orders being attributed to ads, and platform attribution windows not matching actual customer behavior. Inflation rates of 20-50% are common with default Meta settings. High inflation leads to budget misallocation and over-investment in channels that appear more effective than they are. Mitigation: Use click-only attribution, shorter windows, compare platform data to source-of-truth (Shopify), and track manual orders separately.

Related Terms

Frequently Asked Questions

What is Attribution Inflation?

Attribution Inflation is the percentage by which a marketing platform's reported Return on Ad Spend (ROAS) exceeds the true, actual ROAS due to attribution errors and false positive conversions. It quantifies the over-reporting of performance by advertising platforms like Meta or Google. For example, if a platform reports a 5.63x ROAS but the actual revenue data from a source-of-truth system like Shopify shows a 4.00x ROAS, the attribution inflation is 40.6%. This discrepancy is primarily caused by factors like view-through attribution pollution, long attribution windows, and the inclusion of non-incremental conversions, leading to a distorted view of marketing effectiveness and poor budget allocation decisions.

How can marketers measure and mitigate Attribution Inflation?

Marketers can measure Attribution Inflation by comparing the ROAS reported by advertising platforms (e.g., Meta, Google Ads) with the true ROAS calculated from a single source-of-truth system, such as an e-commerce platform like Shopify. The formula is (Reported ROAS - True ROAS) / True ROAS × 100%. To mitigate it, marketers should adopt stricter attribution settings, such as switching to click-only attribution and using shorter attribution windows (e.g., 7-day click). Additionally, they should exclude non-incremental conversions, like manual or offline orders, from platform conversion events and regularly run incrementality tests to understand the true causal impact of their ad spend.

What is the difference between Attribution Inflation and View-Through Attribution Pollution?

View-Through Attribution (VTA) Pollution is a primary *cause* of Attribution Inflation, not a separate phenomenon. VTA Pollution occurs when credit is assigned to an ad that was merely viewed (not clicked) before a conversion, even if the ad had no causal impact. This creates 'false positive conversions' that inflate the reported ROAS. Attribution Inflation is the *result*—the overall metric that quantifies the total over-reporting of ROAS, which is driven by VTA Pollution, long attribution windows, last-click bias, and other attribution errors. In short, VTA Pollution is a specific mechanism that contributes significantly to the broader problem of Attribution Inflation.

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