However, even if data on product sales is available – be it via the utilisation of existing POS data or an external purchase of such data – only a few companies have an answer to the question of which external factors influence sales success, and which are the most effective levers for maximising success. Answers to these questions can be found – often unnoticed by offline retailers – on the internet.
Services such as Google Maps, Facebook or Flickr provide large amounts of geo-specific data with high informational value. Using this, the stationary trade can put itself in the shoes of the end consumer in order to identify the most relevant information for its industry. Consumers, for example, can find out online about opening hours (Google), user ratings (Google, TripAdvisor, Foursquare), shop-specific offers (Yelp), directions (Google Maps) or relevant events (Facebook). This behaviour generates geo-specific data that can be used individually for each outlet and scaled for the entire market. It is therefore possible to obtain detailed data about the area around an individual outlet – for example about the density of shops, relevant places such as concert halls or schools, or proximity to the underground or suburban railway stops – solely via the data from geo-services such as Google Places or Open Street Map. The integration of this data together with the company's own figures represents a decisive and thus far missing link in order to make detailed assessments of the relevant consumer target group, the respective sales potential and the optimal marketing measures for each outlet.