Clustering service - customer clustering based on buying behavior into behavioral groups for your targeted marketing

In order to send out campaigns in a more target-oriented manner, it is recommended to get to know your customers better first, requiring a qualitative grouping of your customers. For example, your top customers may react differently to advertising measures than your new customers or customers who are in danger of leaving.

Our RFMR Scoring provides the solution to this problem. RFMR stands for recency, frequency and monetary ratio and differentiates your customer base according to exactly these criteria: When did the customer‘s last purchase take place, how often does he make purchases and what revenue is being generated by him? Thanks to our calculation algorithms, these customer values are always adapted to your needs and up to date.

Translations: Kaufverhalten = Buying behaviour, Analyse = Analysis, Einzelscores = Individual scores, Gesamtscore = Total score

Translations: Dynamische Kundencluster = Dynamic customer clusters, Kundenscores = Customer Scores, Einzelzuordnung = Individual assignment, Gesamtzuordnung = Total allocation

RFMR scores provide a solid data basis for clustering your customers and determining the segments mentioned above. Value ranges of qualitative segments sometimes differ significantly depending on data structure, thus they should not be determined statically but calculated dynamically. We provide a solution for that issue as well: Our dynamic clustering algorithm adapts your customer’s behavior and thus always creates optimal customer segments.

In addition to RFMR values, other customer characteristics can also be taken into account by our algorithm – such as touch point activities, length of stay or demographic data. There is plenty of information of the customer that can be relevant for the calculation of customer value or the assignment to a customer cluster.

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