Evaluate customer behavior not only in terms of sales volume, but also in terms of value, risk, and relationship quality.
Customer analytics aims to understand customer growth, product preferences, order patterns, payment behavior, service costs, and future potential, in addition to reporting past sales. For wholesale customers, high turnover doesn't always translate to high profitability or low risk.
Minerva analyzes CRM activities, offers, orders, shipments, invoices, collections, returns, and service records from a customer perspective. This allows for the evaluation of customer relationships along with their commercial and operational impacts.
Key areas of customer analytics
Sales, growth, gross margin, and contribution rate.
Product, category, and channel purchasing behavior.
Order frequency, average order, and repeat purchases.
Conversion from quotation to order and reasons for loss.
Payment period, overdue and credit risk indicators
Return, complaint, service and logistics costs
Customer lifetime value and relationship potential.
Risk of getting lost and early warning signals
Turn analytics into the next right action.
Analytical results can be correlated with sales visits, product recommendations, credit reviews, contract renewals, or collection actions. AI-powered recommendations should be explainable and used with the evaluation of sales or finance managers who are familiar with the customer relationship.
Evaluate the customer not only by what they buy, but also by the sustainable value they provide to the company and the overall service burden they create.