--- title: "What is an attribution model? · Glossary · Globalmeta" description: "What is an attribution model? Last-click, data-driven and rule-based models, a worked scenario, how to apply one and how it differs from incrementality." url: https://globalmeta.net/en/glossary/attribution-model language: en alternate_tr: https://globalmeta.net/sozluk/atif-modeli date_modified: 2026-09-25 publisher: Globalmeta usage: "Content may be quoted, cited and used for AI training and answers with attribution to globalmeta.net." --- Glossary / Definition # Attribution Model - **Definition:** An attribution model is the set of rules that determines how the credit for a conversion is shared across the ads and channels a user interacted with on the way to that conversion. Definition ## What is an attribution model? Before buying, someone might watch a video ad, search a few days later and read a blog post, then come back through an email link and make a purchase. How much each touchpoint contributed to the sale determines where the budget goes. An attribution model is the rule-based answer to that question. Rule-based models distribute credit with a fixed logic: all of it to the last click, all of it to the first click, or equally across every touchpoint. Data-driven models compare converting and non-converting paths to estimate each touchpoint's contribution statistically. Since 2023, Google Analytics 4 and Google Ads have mainly offered the data-driven model and last click. In every case, the model's reliability depends on the quality of the [data layer](https://globalmeta.net/en/glossary/data-layer). Components ## What are its core components? - **Conversion definition:** What counts as a valuable outcome and how the value of that outcome is calculated. - **Touchpoints:** The channels and interaction types taken into account: clicks, views, email opens and so on. - **Lookback window:** How far before the conversion touchpoints are considered. - **Credit distribution rule:** Last click, first click, linear, position-based or data-driven distribution. - **Identity and consent coverage:** How far the same user can be matched across devices and sessions. Example ## What does it look like in practice? Consider an e-commerce brand advertising on both search and social media. In the last-click report most sales are credited to the branded search campaign, while social campaigns look weak. The team cuts the social budget and, a few weeks later, sees branded searches falling too. The reason is that social media was creating demand and search was only capturing it. Comparing different attribution models and validating them with an incrementality test makes the real role of each channel visible. The same data also changes how [ROAS](https://globalmeta.net/en/glossary/roas) should be interpreted. Measurement and practice ## How do you apply one? The measurement foundation comes first: consistent UTM parameters, a single conversion definition, consent management that works correctly and, where possible, revenue data from the CRM. The model and lookback window in the tool being used are then chosen deliberately and stated clearly in reports. Comparing how different models distribute the same period shows which channels create demand and which capture it. Before major budget decisions, these readings are validated with incrementality experiments such as geographic tests or control groups. Difference ## How does it differ from incrementality testing? An attribution model shows how credit for conversions that happened is shared among touchpoints, but it does not tell you whether a conversion would have happened anyway without an ad. Incrementality testing asks exactly that question: it compares similar groups that did and did not see the ads to measure the additional outcome the advertising created. Attribution is used for day-to-day optimisation, incrementality for major budget decisions. Reading both together is the common ground of our [performance marketing](https://globalmeta.net/en/services/performance-marketing) and [advanced analytics](https://globalmeta.net/en/services/advanced-analytics) work. ## Frequently asked questions **Which attribution model is the most accurate?** There is no single correct model for every situation. With enough data, the data-driven model usually gives a more balanced result than rule-based models; however, every model is an assumption, and major decisions should be validated with incrementality tests. **Why do advertising platforms report different conversion numbers?** Each platform sees its own touchpoints and uses its own lookback window and model, so more than one platform can claim the same sale. To see the overall picture, an independent analytics tool and CRM data should be the reference. **How do cookie restrictions affect attribution?** Because of users who decline consent and browser restrictions, part of the journey becomes invisible. These gaps are partly filled by modelling, so attribution reports should be read as best estimates rather than exact counts. ## Related reading ### Related services - [Advanced Analytics](https://globalmeta.net/en/services/advanced-analytics) — Service - [Performance Marketing](https://globalmeta.net/en/services/performance-marketing) — Service ### Related insights - [The Meeting Where Everyone Is Right](https://globalmeta.net/en/insights/the-meeting-where-everyone-is-right) — Insights · Can all performance marketing data really be seen in one place? - [Data-Driven Performance Marketing: How to Capture Higher Conversions](https://globalmeta.net/en/insights/data-driven-performance-marketing) — Insights · Digital growth now rewards measurable impact over mere visibility. A data-centric framework to improve conversion performance. - [Google and Meta’s New Advertising Algorithms](https://globalmeta.net/en/insights/google-meta-ad-algorithms) — Insights · From audience targeting to value proposition fit: how to update performance strategy under next-gen ad algorithms. ### Related terms [ROAS](https://globalmeta.net/en/glossary/roas) · [Data Layer](https://globalmeta.net/en/glossary/data-layer) · [Performance Marketing](https://globalmeta.net/en/glossary/performance-marketing) Next step ## Let's clarify what you have in mind. In the first conversation we clarify your current setup, the bottlenecks and what should come first. [Let's talk about your project](mailto:hello@globalmeta.net?subject=Discovery%20call%20%C2%B7%20Attribution%20Model) [hello@globalmeta.net](mailto:hello@globalmeta.net) · [+90 850 330 10 10](tel:+908503301010) · Monumento Plaza, Floor 15 · Kartal, Istanbul