Strongmta.sql ⭐

: The script applies logic to filter out interactions that occurred outside a defined lookback window (e.g., 30 days) and identifies which touchpoints belong to a single conversion cycle [2, 5].

: A concatenated string or array of channels (e.g., Social > Search > Email ). strongmta.sql

In the context of Multi-Touch Attribution (MTA) models, the feature or step within a script like strongmta.sql is designed to transform raw, event-level marketing data into a structured format suitable for attribution modeling. Core Functions of the "Prepare" Feature : The script applies logic to filter out

: In many MTA workflows, the "prepare" step separates paths that ended in a conversion from those that didn't, allowing the model to analyze "null" paths for more accurate probability calculations [4]. Typical Structure of the Prepared Data Core Functions of the "Prepare" Feature : In

The "prepare" stage typically handles the heavy lifting of data cleaning and sessionization before any attribution logic (like Markov Chains or Shapley Value) is applied: