Strongmta.sql

: It standardizes timestamps, user identifiers (UIDs), and channel names across different platforms (e.g., Google Ads, Facebook, Organic Search) to ensure a unified view of the customer journey [1, 3].

Without this preparation step, MTA models cannot handle the high cardinality of raw clickstream data. It ensures that the input is and linearly ordered , which is a prerequisite for calculating the incremental lift of specific marketing channels [3, 5]. strongmta.sql

: A boolean or integer indicating if the path led to a sale (1 or 0). : It standardizes timestamps, user identifiers (UIDs), and

: 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 : A boolean or integer indicating if the