Individual score values with high purchase probability

Kind of data

Customer profiles according to turnover, number of employees and previous industry affinity


Matching database entries with customer profiles

Development of a scoring algorithm for databyte® GmbH


databyte® GmbH provides its clients extensive business information, e.g. for the acquisition of new customers. In total, more than 5 million tradesmen with more than 100 million additional information are available. The decisive quality criterion is the accuracy of matching of the target group potential, which must be identified for the customer acquisition.


In order to further increase the accuracy of the matching, a scoring algorithm has to be developed that identifies new customer potential on the basis of existing customer lists with the highest possible probability of closure.


Initially, existing customer lists were segmented by industry. For the resulting industry segments, eoda has developed customer profiles based on a variety of different information such as sales, number of employees and previous industry affinity. In order to draw conclusions for the acquisition of new customers, eoda then examined the database entries for matches with the customer profiles.

The greater the match between a company in the database and the developed customer profiles, the higher the rating. In this way, the potential new customers for clients can be identified. In the course of the development, the performance of the algorithm was validated using various customer lists. It was shown that the algorithm for different customer profiles delivers reliable and even better results than before.


The result is an overview of all companies with customer-specific score values that best fit the customer profile of the client and have a high purchase probability. This increases the efficiency of new customer acquisition and simultaneously reduces costs due to lower wastage.

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