Two Different Questions
Marketing Mix Modeling (MMM) and Multi-Touch Attribution (MTA) answer different questions:
MMM asks: "How much did each marketing channel contribute to overall sales?"
MTA asks: "Which specific touchpoints led to this conversion?"
Marketing Mix Modeling (MMM)
What it is Statistical modeling that correlates marketing spend with business outcomes over time. Think regression analysis on steroids.
Strengths - Works with aggregated data (privacy-friendly) - Includes offline channels (TV, radio, print) - Captures long-term brand effects - Not dependent on cookies or user tracking
Weaknesses - Requires lots of historical data (typically 2+ years) - Results are directional, not precise - Can't optimize individual campaigns in real-time - Assumes past patterns predict future performance
When to use MMM - You have significant offline spend - You need board-level strategic insights - Privacy regulations limit user-level tracking - You're planning annual budgets
Multi-Touch Attribution (MTA)
What it is User-level tracking that assigns credit to each touchpoint in a customer journey.
Strengths - Granular, campaign-level insights - Can optimize in near real-time - Shows actual customer paths - Actionable for day-to-day decisions
Weaknesses - Requires user-level tracking (privacy concerns) - Only sees digital touchpoints - Ignores brand/awareness effects - Cookie deprecation is breaking it
When to use MTA - You're primarily digital - You need tactical optimization - You have the tracking infrastructure - You operate in a privacy-friendly jurisdiction
The Hybrid Approach
Most sophisticated advertisers use both:
1. MMM for strategy: Annual planning, budget allocation across channels 2. MTA for tactics: Campaign optimization, creative testing, audience refinement
Amazon Marketing Cloud, for example, lets you build both MMM and MTA models on the same privacy-safe platform.
My Take
If you're just starting: begin with simple last-click attribution and basic channel reporting. Add complexity only when you have specific questions that simpler methods can't answer.
If you're mature: use MMM for the big picture, MTA for the details, and always validate one against the other.
The best model is the one that helps you make better decisions, not the one with the fanciest math.