Recommendations for Marketing Campaigns in Telecommunication Business based on the footprint analysis
This work addresses marketing efficiency for telecom businesses, but it is incremental as it applies existing methods like combinatorial optimization and fuzzy logic to a specific case study.
The paper tackled the problem of optimizing marketing campaigns for a telecom operator by analyzing user mobility data from a region in Sweden to identify optimal geo-demographic segments and assess campaign potential, resulting in automated recommendations using fuzzy logic.
A major investment made by a telecom operator goes into the infrastructure and its maintenance, while business revenues are proportional to how big and good the customer base is. We present a data-driven analytic strategy based on combinatorial optimization and analysis of historical data. The data cover historical mobility of the users in one region of Sweden during a week. Applying the proposed method to the case study, we have identified the optimal proportion of geo-demographic segments in the customer base, developed a functionality to assess the potential of a planned marketing campaign, and explored the problem of an optimal number and types of the geo-demographic segments to target through marketing campaigns. With the help of fuzzy logic, the conclusions of data analysis are automatically translated into comprehensible recommendations in a natural language.