The Long View on Multi-Touch Attribution – An Ensemble Approach

Marketing is principally a communication challenge. Companies use it to convey a value proposition and consumers either accept it or reject it. Historically, marketers received very poor feedback on their decisions because customer conversion data was highly aggregated, fragmented or disconnected. However, digital advertising and the availability of user-level data have dramatically changed things.

Marketers are now consolidating datasets and methods to more accurately measure the performance of their media investments. Multi-touch attribution (MTA) models are designed to assign credit to the touch points that affect user journeys on the path to conversion. This document details how MTA models based on a machine learning ensemble approach provides more accuracy, better measurement of marketing contribution and opportunity for innovation.

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