MMM vs MTA Decision Helper
Pick the attribution method that matches your data reality
Helps teams decide when multi-touch attribution (MTA) is still useful vs when to lean on marketing mix modeling (MMM) or incrementality testing. Produces a decision with justification, a minimum data requirements checklist, and a 30-day validation plan.
INGREDIENTS
PROMPT
Decide MMM vs MTA vs hybrid for this business. Output: - Recommendation with rationale (why this method fits and alternatives don't) - What questions it answers / doesn't answer - Data checklist (what's required before implementation) - A 30-day validation plan (small pilots to confirm feasibility) Inputs: - Monthly spend by channel: - Monthly conversions + average order value: - Sales cycle length: - Tracking limitations (consent, iOS share, cookie loss): - Reporting needs (daily optimization vs quarterly planning):
How It Works
This recipe prevents wasted months implementing attribution systems that can't work with your traffic volume,
privacy constraints, or channel mix.
Triggers
- Leadership asks for "multi-touch attribution" but you suspect it's unreliable
- You need a defensible approach to channel contribution
Inputs
- Spend and channel count
- Conversion volume and sales cycle length
- Availability of user-level journey data (cookies, identifiers, consent rate)
Outputs
- Recommended approach (MTA / MMM / hybrid + incrementality)
- Data prerequisites checklist
- First 3 tests or pilots to validate the approach
Actions / Steps
- Assess whether user-level journeys are observable for a meaningful share of conversions.
- Validate whether volume supports modeling (frequency, variance, seasonality).
- Choose a hybrid when needed: MTA where signals are strong + MMM for aggregate + incrementality for validation.
- Create a measurement governance note: what questions each method can/can't answer.
Parameters
- Minimum conversion volume thresholds (user provided)
- Channel count and overlap
- Acceptable error bands for decision-making