Multi-touch attribution (MTA) is most effective when used in environments where accurate, event-level tracking is possible. You should rely on MTA when:
You need granular insights at the channel or campaign level
You want to understand the relative value of touchpoints across the customer journey
You have a robust tracking setup that captures clicks and conversions consistently
You are optimizing mid- and lower-funnel campaigns where digital engagement is measurable
MTA works well when paired with platforms that support conversion imports and allow custom data to influence bidding and budget decisions.
When to complement MTA with other models
MTA is one part of Funnel’s broader measurement framework. To avoid making decisions based on incomplete data, combine MTA with:
Marketing mix modeling (MMM) for measuring upper-funnel and offline channel performance
Incrementality testing to validate causality and assess true campaign lift
Platform-level attribution for tracking impression-based channels that MTA may not fully capture
This triangulated approach improves confidence in your marketing insights by leveraging multiple perspectives.
Known limitations in MTA
Despite its strengths, MTA has limitations that may affect accuracy:
View-based channels, such as display prospecting or TV, often go underrepresented if impressions are not tracked
Cross-device behavior can be difficult to link without deterministic identifiers such as hashed emails
Opt-out users and privacy regulations may prevent full journey capture, introducing bias into the model
Offline actions, like in-store purchases, are not directly measurable unless matched via CRM or point-of-sale data
Funnel’s attribution models include extrapolation methods to partially address these gaps, but some blind spots may still remain.
Making the most of MTA
To get the best results from MTA:
Use server-side tracking and high-quality user identifiers.
Feed MTA insights back into media platforms for smarter optimization.
Combine MTA results with MMM and testing outcomes during strategic planning.
Treat attribution weights as indicators, not absolutes, contextual interpretation is essential.
Understanding where MTA excels and where it needs support ensures that your measurement framework delivers accurate, actionable results.