<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Location data has become more and more accessible. Smartphone applications such as location-based services collect location data on a large scale. Up to now, most approaches have relied on past data, but new developments in machine learning and artificial intelligence will soon enable more dynamic real-time use of location data. Companies that embrace these technologies will be able to create competitive advantages. 
Location data offers great potential to improve a variety of marketing decisions such as targeted pricing and advertising, store locations and in-store layout. Location based advertising is currently the most common application. It allows targeting all customers within a certain distance of a store. Besides advertising, location data can be used for dynamic pricing decisions. Customers close to competitor’s locations can be charged a lower price for particular products via discounts in order to reduce switching costs. Indoor tracking can help to optimize store design or the positioning of categories and brands. Granular location data about consumers’ movements hence further allows for minimizing potential offline transaction costs based on the distances to stores.
</p>
</abstract>

Location data has become more and more accessible. Smartphone applications such as location-based services collect location data on a large scale. Up to now, most approaches have relied on past data, but new developments in machine learning and artificial intelligence will soon enable more dynamic real-time use of location data. Companies that embrace these technologies will be able to create competitive advantages. 
Location data offers great potential to improve a variety of marketing decisions such as targeted pricing and advertising, store locations and in-store layout. Location based advertising is currently the most common application. It allows targeting all customers within a certain distance of a store. Besides advertising, location data can be used for dynamic pricing decisions. Customers close to competitor’s locations can be charged a lower price for particular products via discounts in order to reduce switching costs. Indoor tracking can help to optimize store design or the positioning of categories and brands. Granular location data about consumers’ movements hence further allows for minimizing potential offline transaction costs based on the distances to stores.

Tell Me Where You Are and I’ll Tell You What You Want: Using Location Data to Improve Marketing Decisions

Professor of Electronic Commerce and Digital Markets, Ludwig-Maximilians-University of Munich,

Assistant Professor, Gabelli School of Business, Fordham University, New York,

Professor of Business Information Systems at the Baden-Wuerttemberg Cooperative State University, Ravensburg,

NIM Marketing Intelligence Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Location data has become more and more accessible. Smartphone applications such as location-based services collect location data on a large scale. Up to now,...

Tell Me Where You Are and I’ll Tell You What You Want: Using Location Data to Improve Marketing Decisions

Published Online: Oct 28, 2016

Page range: 30 - 37

DOI: https://doi.org/10.1515/gfkmir-2016-0013

Keywords
Location Data, Location Intelligence, Decision Support Systems, Mobile Targeting, Mobile Analytics

© 2016

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Tell Me Where You Are and I’ll Tell You What You Want: Using Location Data to Improve Marketing Decisions

Published Online: Oct 28, 2016

Page range: 30 - 37

DOI: https://doi.org/10.1515/gfkmir-2016-0013

KeywordsLocation Data, Location Intelligence, Decision Support Systems, Mobile Targeting, Mobile Analytics

© 2016

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
Location Data, Location Intelligence, Decision Support Systems, Mobile Targeting, Mobile Analytics