This study delivers insights on which external sources - e.g. website click behavior, surveys, or social media data - can and cannot be used for data augmentation. A case study is performed to test the suitability of different sources in order to create a generalized practical guide for data augmentation in marketing. Data augmentation is a beneficial tool for companies to use external data, if the internal data basis for targeting is not sufficient to reach the customers with the highest propensity. This study shows that augmenting data from feasible sources leads to significant conversion lifts.…mehr
This study delivers insights on which external sources - e.g. website click behavior, surveys, or social media data - can and cannot be used for data augmentation. A case study is performed to test the suitability of different sources in order to create a generalized practical guide for data augmentation in marketing. Data augmentation is a beneficial tool for companies to use external data, if the internal data basis for targeting is not sufficient to reach the customers with the highest propensity. This study shows that augmenting data from feasible sources leads to significant conversion lifts.
Dr. Bettina Hüttenrauch obtained her doctorate degree at the Johannes Gutenberg Universität Mainz. She currently works as a project manager at a German airline and is responsible for building up the "Analytics Factory" for an advanced analytics program.
Inhaltsangabe
Introduction and strategic motivation to data augmentation in database marketing.- Literature review on data augmentation.- Methodological framework for data augmentation.- Test design for evaluating different source characteristics.- Analysis of data augmentation KPIs, case study results and test of hypotheses.- Limitations of data augmentation and outlook.
Introduction and strategic motivation to data augmentation in database marketing.- Literature review on data augmentation.- Methodological framework for data augmentation.- Test design for evaluating different source characteristics.- Analysis of data augmentation KPIs, case study results and test of hypotheses.- Limitations of data augmentation and outlook.
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