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  2. Predictive Analytics for Telekom Marketing Campaigns Predictive Analytics for Telekom Marketing Campaigns

Predictive Analytics for Telekom Marketing Campaigns

The project develops a semi-automated predictive analytics solution on a big data platform that supports marketers in the telecom sector in designing and executing online direct marketing campaigns.

Brief information

School:

Computer Science and Information Technology

Status:

Completed

Period:

01.01.2016 - 31.05.2017

Overview

Using an intuitively understandable user interface, marketers and campaign designers can oversee trends in the data and identify most influential customer attributes for a given campaign objective (such as customer retention or upsell). They can run what-if scenarios and get automatic recommendations for optimizing the campaign revenue based on up-to-date customer behaviour data.

In order to facilitate intuitive interpretability of prediction results, the underlying model is based on a Bayesian Network approach, which allows to track the influences of input variables to the target variable. The closed-loop approach allows for the predictive model to automatically adapt to changing customer behavior. The system is set up on a big data stack using SPARK streaming for online data processing.

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Facts

Type of project

Forschung

Internal organisations involved
  • Mobile & Smart Systems F&E
Funding
  • KTI-HSLU als Hauptgesuchsteller/in
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Links

  • consulteer ag

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Persons involved: internal

Project manager
  • Gwendolin Wilke
Member of project team
  • Michael Kaufmann
  • Pavol Svaba

Brief information

School:

Computer Science and Information Technology

Status:

Completed

Period:

01/01/2016 - 05/31/2017

Footer(s)

FH Zentralschweiz

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