What are Recommendation Engines?

Recommendation Engines are used in numerous on-line Shops, call centers and terminals to automatically offer the customers individualized products and to measure the success of the offer acceptance (e.g. via A/B-Tests). On the basis of previously bought articles the engines compute so-called „group purchases” as well as (with temporal purchase) „demand chains” and use them to suggest personalized product offers („customers, who bought product A, also bought product B, C and D!”).

Here however only the two dimensions „customer” and „product” are considered („to offer the right product to the right customer!”). Three other crucial dimensions like „the communication channel”, „the offer time” and „the price” are not included in modern marketable recommendation machines or included rudimentarily.

What is a Customer Interaction Server?

A customer interaction server is a consequent further evolution of a recommendation engine. It embraces all five dimensions (customers, product, communication channel, time and price) holistically and considers them for optimal, automated product offer.

A customer interaction server offers

• the right (suitable) product, service,…,
• to the right (affine) customer, user, visitor, potential buyer,…,
• at the right (convenient) time (customers should be also attentive!),
• through the right (suitable) communication channel,
• for the right (optimal) price,

to raise the probability of transaction (purchase, bargain, premium rate service,…) and to increase the sales volume and turnover / profit. The customer interaction server uses here not only the history of previous purchases and interaction data, but also uses for its calculations a multitude of internal and external sources of information, in order to successfully accomplish its sophisticated offer optimization.

You can find further information in Publications.