Empower Your Marketing Confidence through Multi-Touch Attribution 

Multi-Touch Attribution (MTA) is a key method in the marketing arsenal, clarifying how each customer touchpoint drives a conversion or other desired outcome.  

The Marketing Attribution Think Tank (MATT), an MMA community of marketing and analytics leaders committed to people-based, accountable measurement, build MTA its first priority, publishing vendor capability reviews, developing the MTA Journey Map (an end-to-end implementation guide), and releasing additional resources that help marketers evaluate and adopt MTA solutions to build confidence in the marketing’s ability. 

In the State of Attribution Report 2024, 57 % of marketers said MTA is essential when paired with complementary methods such as Marketing Mix Modelling (MMM) and experimental design.  

Illustrations above is the reference to work 

 

Key Trends in Marketing Measurement & Attribution (M&A) 

  1. AI/ML Integration Gains Urgency
  • 1 in 3 marketers list AI/ML integration as a major concern. 
  • Half expect AI to have a “serious impact” on measurement & attribution (M&A) within 12 months. 
  • Anticipated near-term benefits: 
  • Faster analytics cycles (44 %) 
  • Tighter activation via bid-management systems 
  • Few expect AI to solve complex data-fusion or privacy challenges—still an open opportunity. 
  1. Raising the Perceived Value of M&A
  • 50 % are frustrated with the overall value their M&A programs deliver. 
  • 60 %+ struggle to quantify marketing’s total business impact (present results and long-term multiplier). 
  • Planned response: heavier investment in measurement talent, technology, and processes to build confidence in analytics across the organization. 

 

About Marketing Attribution Think Tank (MATT) 

MATT is a community of marketing and analytics leaders committed to building confidence in marketing’s ability to (predictively) drive growth, in a way that CFOs trust. 

Discover more on MATT and their initiatives: https://www.mmaglobal.com/think-tanks/matt  

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