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OpenClaw recipe

Attribution Method Selector (MMM vs MTA)

aka “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.

House RecipeWork8 min setup
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INGREDIENTS

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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

  1. Assess whether user-level journeys are observable for a meaningful share of conversions.
  2. Validate whether volume supports modeling (frequency, variance, seasonality).
  3. Choose a hybrid when needed: MTA where signals are strong + MMM for aggregate + incrementality for validation.
  4. 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
Tags:#attribution#measurement#mmm#mta#digital-marketing#strategy