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GlossaryAttribution Model (PPC)

Attribution Model (PPC)

An attribution model determines how conversion credit is assigned to the different ad interactions a user had before completing a conversion. It decides which click gets the credit when a customer searches, clicks, leaves, and returns before converting.

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In short
An attribution model decides which ad click gets credit for a conversion.
Data-driven attribution (DDA) uses machine learning and is Google's default where eligible, and the best choice for most accounts with enough data.
Position-based attribution gives 40 percent to the first click, 40 percent to the last, and 20 percent across the middle.
Below roughly 300 conversions per month, Position-Based or Time Decay are reasonable alternatives to DDA.
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In depth

Attribution Model (PPC), explained properly.

•An attribution model decides which ad click gets credit for a conversion.
•Data-driven attribution (DDA) uses machine learning and is Google's default where eligible, and the best choice for most accounts with enough data.
•Position-based attribution gives 40 percent to the first click, 40 percent to the last, and 20 percent across the middle.
•Below roughly 300 conversions per month, Position-Based or Time Decay are reasonable alternatives to DDA.

What is an attribution model?

An attribution model determines how conversion credit is assigned to the different ad interactions a user had before completing a conversion. Most customers do not convert on the first click, they might search, click an ad, leave, come back through remarketing, search again, and then convert. The attribution model decides which click gets the credit. Think of it like a football team scoring a goal. Was it the striker who scored, the midfielder who passed, or the defender who started the move? Attribution models decide who gets credit.

Common attribution models in Google Ads

- **Last click:** all credit goes to the final ad click before conversion, ignoring everything that happened before. - **First click:** all credit goes to the first ad click. - **Linear:** credit is divided equally across all clicks in the journey. - **Time decay:** more credit to clicks that happened closer to the conversion. - **Position-based:** 40 percent to the first click, 40 percent to the last click, 20 percent split across middle interactions. - **Data-driven (DDA):** Google uses machine learning to assign credit based on actual conversion patterns. The most accurate model, but it requires sufficient conversion data.

The main attribution models

- **Last Click:** 100 percent credit to the last touchpoint. Simple but misleading for multi-touch journeys. - **First Click:** 100 percent credit to the first touchpoint. Useful for awareness measurement. - **Linear:** equal credit across all touchpoints. Fair but assumes all touches are equal (rarely true). - **Time Decay:** more credit to touchpoints closer to conversion. A reasonable default for long sales cycles. - **Position-Based (40-20-40):** 40 percent to first, 40 percent to last, 20 percent spread across middle. Balances awareness and conversion. - **Data-Driven Attribution (DDA):** Google's machine learning analyses your actual conversion patterns and distributes credit accordingly. Now Google Ads' default model where eligible.

Which model should I use?

Data-driven attribution is recommended for most accounts with sufficient data. For newer accounts, Last Click is simpler and more transparent while you build history. Switching attribution models can significantly change reported conversion numbers.

Why attribution matters

The model determines which campaigns appear profitable and which appear wasteful. Last-click consistently undervalues upper-funnel channels (Display, YouTube, social) and overvalues last-touch channels (brand search, retargeting). DDA usually produces the most balanced view, though it requires sufficient conversion volume to work.

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Common questions

Attribution Model (PPC): common questions.

Which attribution model is best?

Data-driven attribution (DDA) is now Google's default and the best choice for most accounts with sufficient conversion volume. Below the threshold (around 300 conversions per month), Position-Based or Time Decay are reasonable alternatives. Last-Click is the worst choice for multi-channel accounts because it consistently distorts performance signals.

Does attribution model affect Smart Bidding?

Yes, significantly. Smart Bidding optimises against the conversions reported under your chosen model. Switching from Last-Click to Data-Driven changes which clicks Smart Bidding considers conversion-driving, which changes which queries get prioritised. Plan for two to four weeks of relearning after attribution model changes.

Can I have different attribution models for different campaigns?

Not within a single Google Ads account; the model applies account-wide. You can run multiple Google Ads accounts with different models, or use GA4 alongside Google Ads to view different attribution models in parallel for analysis even if Google Ads itself only uses one.

How do I switch attribution models?

In Google Ads, go to Tools, then Attribution, then Settings. Choose the new model and apply. Expect a few weeks of disruption while Smart Bidding relearns. Do not switch frequently; each change resets the learning curve.

More terms
Alt TextBacklinksCanonical TagClick-Through Rate (CTR)Conversion Rate Optimisation (CRO)Core Web VitalsCumulative Layout Shift (CLS)Digital PRDomain AuthorityE-E-A-TGoogle Tag Manager (GTM)Interaction to Next Paint (INP)Knowledge GraphLargest Contentful Paint (LCP)llms.txtMeta DescriptionROAS (Return on Ad Spend)Schema markupSEO (Search Engine Optimisation)Technical SEOTime to First Byte (TTFB)XML SitemapZero-Click Search
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