Blog/Paid Media Strategy
Paid media attribution models explained — why last-click is wrong and what to use instead.
Attribution determines which ad gets credit for a conversion. The default in most platforms is last-click — which gives 100% of the credit to the final touchpoint and ignores every assist that came before it. This leads to predictable, systematic budget decisions: cutting top-of-funnel campaigns that look unprofitable and over-investing in bottom-of-funnel that looks excellent but is harvesting demand the rest of the funnel created. Use Data-Driven Attribution in Google Ads, 7-day click in Meta, and GA4 as your cross-channel reference.
Ahmed Ashraf
Founder, Traffiy · April 2026 · Google Premier Partner
“Last-click attribution tells you who closed the deal. It doesn't tell you who found the lead, warmed it up, and kept it engaged. Running on last-click is like paying only your sales team and wondering why marketing keeps leaving.”
— Ahmed Ashraf · $100M+ in budgets managed
Attribution models explained
The four models you need to understand.
Last-click attribution — the default and the problem
The last ad the user clicked before converting gets 100% of the credit. Simple, deterministic, widely used — and systematically wrong. It over-rewards branded search and direct retargeting campaigns (which capture intent already built by other channels) and under-rewards the prospecting channels that created that intent. The predictable outcome: brands cut TikTok and Meta awareness campaigns (which look unprofitable under last-click) and pour more budget into Google branded search (which looks excellent but was going to convert anyway). A self-reinforcing loop that limits growth.
First-click attribution — useful for prospecting analysis
The opposite extreme — 100% of credit goes to the first touchpoint. Useful for understanding which channels are best at introducing new customers to your brand, but equally flawed as a sole decision-making model. A user who discovered you via TikTok 6 months ago and only converted after 3 Meta retargeting ads and a Google branded search should not give 100% credit to TikTok. Use first-click reporting as a supplementary lens for new customer acquisition analysis, not as your primary attribution model.
Linear attribution — better, still imperfect
Equal credit distributed across all touchpoints in the conversion path. A conversion with 4 touchpoints gives 25% to each. Better than last-click because it acknowledges multi-touch reality. The weakness: it treats a casual ad view the same as the high-intent click that drove the conversion. Equal credit is not accurate credit. Linear is a useful intermediate model for accounts without enough data for Data-Driven Attribution.
Data-driven attribution — the right answer for most accounts
Google's machine learning model analyses your actual conversion paths — paths that converted vs paths that didn't — and assigns fractional credit to each touchpoint based on its real contribution. Available in Google Ads (Tools → Attribution) and GA4 (Advertising → Attribution settings). Requires a minimum volume of conversions to activate meaningfully (~300/month in Google Ads). For accounts below this threshold, Linear is the best available alternative until volume grows. Always use Data-Driven when eligible — it is the only model that adapts to your specific business rather than applying a universal rule.
Practical setup
Change in Tools → Attribution → Attribution model. Select Data-Driven if available, otherwise Linear. This affects how your conversions are reported and how Smart Bidding optimises.
Default 7-day click / 1-day view is correct for most accounts. Change at the ad set level in Attribution Settings. Keep view-through enabled — Meta's view-through data is more reliable than most assume.
Admin → Attribution Settings → Reporting attribution model. Set to Data-Driven. Use GA4 as your cross-channel neutral reference, not platform-specific reporting.
Attribution model reference
| Model | How it works | Overvalues | Undervalues | Best for |
|---|---|---|---|---|
| Last-Click | 100% credit to the final touchpoint | Bottom-of-funnel (branded search, retargeting) | Top-of-funnel (awareness, social) | eCommerce with very short purchase cycles only |
| First-Click | 100% credit to the first touchpoint | Top-of-funnel acquisition channels | Retargeting and conversion-stage touchpoints | Prospecting analysis only |
| Linear | Equal credit to all touchpoints | Mid-funnel touchpoints with low impact | High-impact first and last touchpoints | Basic multi-touch awareness |
| Data-Driven (DDA) | ML assigns credit based on actual path data | Nothing systematically — accounts for real paths | Nothing systematically | Accounts with 300+ monthly conversions |
3–7
Average ad touchpoints before a B2B conversion — none of which last-click fully credits
90%
Of accounts default to last-click attribution without realising or intentionally choosing it
7-day
Recommended Meta attribution window — click + 1-day view captures the full influenced conversion window
FAQ
Common questions about paid media attribution.
What is last-click attribution and why is it wrong?+
Last-click attribution gives 100% of the conversion credit to the final ad touchpoint before a purchase or lead. It is wrong because it ignores every earlier touchpoint that built awareness and consideration. If a user saw a TikTok ad, then a Meta retargeting ad, then clicked a Google branded search ad to convert, last-click gives Google 100% of the credit and TikTok 0%. This leads to cutting top-of-funnel spend (which looked unprofitable) and over-investing in bottom-of-funnel (which looks very profitable but is actually just harvesting demand others created).
What is data-driven attribution in Google Ads?+
Data-driven attribution (DDA) uses machine learning to analyse your actual conversion paths and assign credit to each touchpoint based on its true contribution to conversions. Unlike rule-based models (last-click, first-click, linear), DDA learns from your specific account data. It requires a minimum number of conversions to activate (300+ conversions per month recommended) but is the most accurate single-account attribution model available in Google Ads.
How should I set attribution in Meta Ads?+
Meta's default attribution window is 7-day click, 1-day view. This credits a conversion to a Meta ad if the user clicked the ad within 7 days or viewed it within 1 day before converting. For most businesses, 7-day click / 1-day view is appropriate. View-through attribution (1-day view) is particularly important for Meta because many users don't click but are influenced by seeing an ad — especially on mobile where scrolling is fast. Removing view-through attribution typically undercounts Meta's true contribution.
What is the best way to measure cross-channel attribution?+
No single platform tells the full cross-channel story — each platform's reporting only includes its own touchpoints. The best approach: use GA4 as a neutral cross-channel source (set to data-driven attribution), use platform-level reporting for within-platform optimisation decisions only, and run periodic incrementality tests (holdout experiments) to understand true causal impact by channel. Accept that some double-counting is inevitable in cross-channel reporting — what matters is directional accuracy, not perfect attribution.
Ahmed Ashraf — Founder, Traffiy
10+ years in paid media. $100M+ in budgets managed across Meta, Google, and TikTok. Google Premier Partner — top 3% globally. Every article on this blog is written from direct experience managing real campaigns.
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