Intelligent recommendations combine product information and the best sales experts' knowledge.
The heart of excentos Guided Selling technology are the knowledge model and Matching Engine:
The Matching Engine compares the user profile, the accumulation of the user's input, buying history or other available data with the product profiles. This way excentos calculates a Fit Score that represents the buying probability.
Every recommendation is calculated for the individual user profil and thus a personalized recommendation.
How are recommendations generated?
In the same way as a human sales expert would: with sales and product knowledgeexcentos creates a knowledge model based on the know-how of product and sales experts. The Matching Engine applies the knowledge model:
- The Product Guide creates a user profile that includes all buying needs and user data
- The knowledge model translates the user profile into product specific needs.
For this process the knowledge model refers to product and sales knowledge such as: which processor does the nootbook need to run a specific software
- a ranking is created and defines which products fulfills the customers needs the best
- the ranking is optimized according to purchase probability
The knowledge model includes all relevant information about the products, their attributes, specific sales strategies and typical buying requests.
The knowledge model, the translation of buying desires into product attributes, sets general correlations between buying desire to product attribute and is not limited to one product. Therefore, new products can be introduced into the system through the datafeed and do not require any change of the Product Guides configuration.
The Matching Engine always analyzes all attributes of a product and compares them to the customer's buying desires. The result list with the recommendations is displayed the order that has been established in the ranking.