Customer Scoring: Increase sales effectiveness with artificial intelligence
01.
Background
A manufacturer wants to optimize the effectiveness of his distribution (distributor and own sales force) in the B2B (HoReCa) business and improve the acquisition of customers
02.
Research questions (extract)
Which characteristics influence the probability of becoming a customer?
Which attributes influence the potential customer value?
Where are the potential customers geographically located?
03.
Approach
Customer Scoring
Comparison of user-generated and web-based information with internal customer sales data
Data size: 651.940 data rows
Analytical forecast: Who is a potential customer for my segment? Who is potentially a good / valuable customer for me?
04.
Result
Intuitive map with locations of potential customers and their customer value
Explanation of the influencing factors and their significance on the probability of becoming a customer or good customer
Self-learning tool for a continuous increase of sales effectiveness
