AI-based target group identification

How about regional retailers seeing a map and being shown via mouseover how many potential buyers live in which region and with which advertising medium or even media mix you can reach them most effectively? And best of all, the target group or persona does not have to be defined in advance by the retailer or headquarters but is based on hard facts and an AI-based analysis. This means it corresponds to the actual buyer base and not the assumed target group - which, as we all know, is not always identical. Wishful thinking? No, because our team of mathematicians and UI designers have developed just that with Germany's leading marketing data provider, which holds a wide range of microgeographic and regional market data and how to use it.

Empirical data such as buyer analytics and non-buyers and other statistical data such as socio-demographic structures form the basis for comprehensive analysis - AI is the key technology here. Sifting through data sets, recognizing patterns, predicting outcomes, and guiding each customer individually on their customer journey is the goal. The result: models and methods that throw up a score that allows end-users to intuitively geotarget effectively - whether by zip code or household - and without significant wastage.

"What we appreciate most about the cooperation with our partner socoto, apart from the reliability, is the profound understanding in dealing with data. Through the interplay of analytical qualifications and geomarketing expertise, socoto creates solutions with which sales territories can be processed in a target group-specific manner. In doing so, socoto maps complex relationships to target groups and territories in such a way that they are user-friendly to operate and easy to implement," says Karl-Heinz Mühlbauer, managing director of panadress marketing intelligence GmbH.

In this way, socoto has eliminated a problem faced by many marketers - the communication gap between assumed target groups and actual buyers.

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