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[D] attribution models

Hello,

Suppose I have the following data:

—A——–A——B——C—B———-A———–X

–B-A—-B——A——C—C—–B—X

A, B, and C represent different contacts or touch points between the firm and the customer. X is the desired event for the customer (for example, a purchase). The —— represents the time in between events.

What kind of attribution models can I build to understand the relationship between A, B, C, and X?

I can create variables based on the recency and frequency of A, B, and C. What else can I do?

I read somewhere that neural network (maybe recurrent neural network) can handle non-tabular data a lot better. Can I treat those sequences of events and their timing as non-tabular data and utilize them?

Please educate me or provide pointers. Thanks!

submitted by /u/sonicking12
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.