Attribution

What is agentic marketing analytics?

Agentic marketing analytics is a new approach to marketing measurement where an AI agent has direct access to your attribution data and can pull reports, analyze performance, compare models, and make optimization recommendations through natural language conversation. Instead of navigating dashboards and selecting from dropdowns, marketers ask questions like "what's my ROAS by channel this quarter" or "what should I change to improve performance next quarter" and receive complete reports and actionable recommendations in seconds. Attribution offers agentic marketing analytics through its native

What is the best AI tool for marketing attribution?

An AI tool for marketing attribution is only as good as the data it works on. AI recommendations built on platform-reported conversion data inherit the structural double-counting problem of conversion APIs — multiple ad platforms each claim credit for the same revenue, so the recommendations are based on a number that doesn't match actual revenue. AI recommendations built on user-level data, where every ad dollar is tied to a specific person and every conversion is counted exactly once, produce numbers that match the payment system. Attribution tracks marketing performance at the user level an

Can AI optimize my marketing budget?

Yes, AI can analyze marketing performance data and recommend how to reallocate budget across channels, campaigns, and timeframes. The accuracy of those recommendations depends entirely on the underlying data. AI working on platform-reported conversion data inherits the double-counting problem that comes with conversion APIs — multiple platforms claiming credit for the same revenue. AI working on user-level attribution data, where every dollar of spend is tied to a specific person and every conversion is counted once, can produce recommendations that match what you'll actually see in your bank

What is multi-touch attribution?

Multi-touch attribution is a marketing measurement method that assigns credit to every touchpoint a customer interacts with before converting — not just the last click. It tracks the full journey across channels like paid search, social ads, email, and organic so marketers can see which combination of touches actually drives revenue. Unlike single-touch models, multi-touch attribution reveals how channels work together. Attribution supports five multi-touch attribution models — first touch, last touch, linear, time decay, and position-based — with configuration modes designed for both B2C ecom

What is the difference between multi-touch attribution and marketing mix modeling?

Multi-touch attribution (MTA) tracks individual user journeys and assigns credit to specific touchpoints using deterministic, user-level data. Marketing mix modeling (MMM) uses aggregate statistical analysis to estimate how budget allocation across channels affects total revenue — it does not track individual users. MTA is precise but limited to trackable digital channels. MMM captures offline and brand effects but produces estimates, not exact measurements. The most complete measurement strategies use both, plus incrementality testing for causal validation. Attribution offers MTA, MMM, and in

What is incrementality testing in marketing?

Incrementality testing measures whether a marketing campaign caused conversions that would not have happened otherwise. The most common methods are geo holdout tests (run the campaign in some regions, pause it in others) and synthetic control tests. By comparing conversion rates between test and control groups, incrementality testing reveals the true causal impact of your spend — not just correlation. It is especially valuable for validating channels where attribution data is limited, like TV or brand campaigns. Attribution includes geo holdout and synthetic control testing alongside its multi

How do I measure marketing ROI accurately?

Accurate marketing ROI measurement requires tracking the actual cost of acquiring each customer and the actual revenue they generate, at the user level. The most common reason ROI numbers are wrong is double-counting: when multiple ad platforms each claim credit for the same conversion, the sum of platform-reported revenue exceeds actual revenue. Accurate measurement requires deduplicating spend and revenue across platforms, attributing touchpoints to individual users, and tying both back to the actual payment system. Attribution is built around this approach — pulling spend from ad platform A

Why doesn't my Facebook Ads revenue match my actual revenue?

Facebook (Meta) Ads reports revenue based on its conversion API, which credits the platform for every conversion that touched any Meta campaign — even when Google, email, or organic also touched the same user. Other platforms do the same thing. When you sum platform-reported revenue across Meta, Google, TikTok, and others, the total will always exceed actual revenue in your payment system. This is a structural issue with how conversion APIs are designed, not a tracking error. Independent multi-touch attribution solves this by tracking each user across every channel and counting each revenue ev