Investigating the Attribution Quality of LSTM with Attention and SHAP : Going Beyond Predictive Performance

Investigating the Attribution Quality of LSTM with Attention and SHAP : Going Beyond Predictive Performance

Estimating each marketing channel’s impact on conversion can help advertisers develop strategies and spend their marketing budgets optimally. This problem is often referred to as attribution modelling, and it is gaining increasing attention in both the industry and academia as access to online track...

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Bibliographic Details
Main Author: Kindbom, Hannes
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2021
Subjects:
Digital marketing
Attribution modelling
Multi-touch attribution
Deep learning
LSTM
SHAP
Attention
Interpretability
Digital marknadsföring
Attributionsmodellering
Djupinlärning
Tolkningsbarhet
Computer and Information Sciences
Data- och informationsvetenskap
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302412

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302412

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