Dastani Consulting has developed a customer value prediction model to identify and evaluate decisive sales potentials of customers for the company and to make them available for the management of sales activities.
Evaluate performance with Customer Value Prediction
In customer value prediction, the entire customer base is evaluated with regard to the expected future revenue of each individual customer. In addition, it is possible to specify the expected sales per customer over a specific period of time – be it 3, 6 or 36 months.
Target/actual comparison identifies shortfalls
A customer value prediction predicts the revenue that can be generated from the entire relationship with a customer. Before marketing uses the forecasts, a target/actual comparison is carried out: The expected values of a customer value forecast are compared with the actual values of the current calendar year. The resulting delta (actual/target) answers the question of whether the customer has already met his target sales in the current calendar year or whether there is a shortage. From this, a precise sales control can be derived.
By breaking down the sales potential according to assortment areas, it is possible to tap important cross-selling and up-selling potentials. In this way, you can also identify the area in which a customer has a shortage and thus increase sales by up to 35%. You will also be provided with information on which existing customers require product-specific marketing and sales measures.
Data basis and model development
The input and at the same time the basis of a customer value prediction are primarily the transactions stored in the ERP system. From this, a large number of variables are formed that represent the product-specific purchasing behavior of a customer. The Customer Value Prediction module developed by Dastani Consulting is able to carry out this prediction automatically in order to significantly increase the prediction quality, so that the expected values of as many customers as possible correspond to the actual sales.
All variables of the model are tested for quality and predictive power. Statistical methods evaluate which variables are relevant for future behavior in which combination and to what extent. The forecast model is optimized in such a way that the quality of the forecast is maximized.
Success: promising business relationships
Use our predictive analytics models to identify sales opportunities and focus on attractive and promising business relationships to increase your revenue. Use your resources efficiently and reduce your business risk to stay successful in the long run.