Today the key to more customers and to a significant increase of sales is “recommend” instead of “selling”!

On-line shopping pioneers such as Amazon.com did it and proved it: depending on the category of products between 10 to 20 per cent increased sales in the Web-shop by means of purposeful, automated article recommendations in the “Long Tail” of the total assortment. In the meantime German enterprises also recognized this enormous potential. E.g. Quelle.de increased the portion of cross-selling-articles in the market place demand even more than ten times after the introduction of its recommendation-engine-solution in the beginning of 2006.

The METRO group makes one step further and examines the real-time-recommendation-solution for the offline purchase world in its future-store. Through so-called personal shopping assistants (PSA) and displays installed in shopping carts, the corresponding articles are chosen and scanned by the customers themselves. At the same time similar articles are offered to the customers.

How do IT-supported recommendation engines get the knowledge about group purchases and demand chains, about preferences, favors and usage habits?