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Two data-driven and statistically-oriented attribution models of an advertising campaign of a “Fortune 500 Automobile Manufacturer” are developed.

Python 100.00%

attribution-modelling's Introduction

Data-driven tractable attribution modelling

At this project, two data-driven and statistically oriented attribution models are developed; a Second-order Probabilistic Model (SPM) and a Bagged Logit Model (BLM). The analysed dataset corresponds to an automotive advertising campaign of “A Fortune 500 Automobile Manufacturer” that took place in the United States from June 15, 2009 to August 23, 2009.

Due to confidential agreement with the client, the analysed dataset is not provided. Therefore, the initial datasets regarding advertising activitites, impressions, clicks and conversions are not present. However, a sample draft of the preprocessed (network_impressions_modelling.csv) and transformed (dataframe_impressions_user_date.csv) datasets that were used during the attribution modelling part are provided.

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