Target Group Prediction offers you a highly effective predictive analytics tool. The software is based on a proven algorithm aligned to the analysis of big data. By identifying acquisition potentials, the algorithm indicates which customers show a high affinity for your products.
Predictive Analytics
Target Group Prediction
- Targeted budget allocation
- Determines customer values
- Raises profit contributions
- Enhances sales efficiency
- Reveals potentials
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Predictive Analytics at Würth
Using Customer Value Prediction, Würth allocates each of its 500,000 active customers in Germany to the most appropriate sales segment. The 3,000-strong sales force knows the turnover potential per product segment, so that each salesperson can make targeted customer offers. Consequently, Würth is able to increase its profit contribution per customer. Random call-centre surveys have indicated a prediction success rate of 85 to 90 percent.
Predictive Analytics at Würth
Using Customer Value Prediction, Würth allocates each of its 500,000 active customers in Germany to the most appropriate sales segment. The 3,000-strong sales force knows the turnover potential per product segment, so that each salesperson can make targeted customer offers. Consequently, Würth is able to increase its profit contribution per customer. Random call-centre surveys have indicated a prediction success rate of 85 to 90 percent.
Customer Value Prediction boosts sales efficiency and turnover
In Germany, around 3,000 permanent sales employees of Adolf Würth GmbH & Co. KG sell more than 100,000 different products to over 500,000 trade customers. Regional sales are not only divided into sectors, but also into vertical segments – ranging across mini-businesses, tradesmen, potential customers right up to major companies. Deploying salesmen in all these segments is “the most expensive form of selling” according to Jens Neumann, manager of sales controlling at Würth.
Success rate of 85 to 90 percent
Over the past two years, Würth has been using customer value as the parameter to allocate all its customers to the right segment. For the Customer Value Prediction, Würth uses an algorithm from Dastani Consulting. The predictive application evaluates Würth’s internal database as well as external data. Each customer is clearly allocated to a particular segment and the software delivers an exact prediction of the expected turnover.
Raising turnover through Potential Analysis
This not only allocates the right salesman for a particular customer, i.e. the most competent salesman for that business and its required product assortment, but also accurately determines that customer’s potential. For example, roofing contractors with 10 to 15 employees are an interesting group. Based on customer histories and credit rating data, it is possible to determine the businesses in this or any other size cluster that show the highest expected sales prediction. “We re-allocate high-potential trade businesses according to their sales potential in order to fully exploit all available possibilities. That won’t always please the incumbent salesman, who doesn’t want to lose ‘his’ customer”, says Jens Neumann. But it pays off if one can convince the salespeople that attractive incentives based on data-driven allocation systems are more effective than a salesman’s ‘gut feeling’. Jens Neumann: “We have tested the results through a call centre. The success rate is 85 to 90 percent – a top rate.” A telephone interview takes between 10 and 15 minutes and costs Würth up to 4 euros. Applying a prediction to determine a customer value has proved to be a much more economical alternative.
Turnover potential per product segment
The prediction application not only allows sales managements to inform their salespeople how much turnover is possible with a particular customer, but also what it would be made up of. “Looking at the customer history, we determine for example that a tradesman has previously been buying insulating foam for 5,000 euros per year”, explains Jens Neumann. “Then we examine comparable customers. What have they bought? The conclusion could be that the salesman can also sell roofing panels for 5,000 euros and screws for 10,000 euros, making a potential total of 20,000 euros.” Breaking down the overall prediction into individual product range segments boosts the profit contribution. Together with Dastani Consulting, Würth has succeeded in enriching the existing data, thus significantly enhancing sales efficiency and creating a positive effect on the overall financial performance.
Turnover potential per product segment
The prediction application not only allows sales managements to inform their salespeople how much turnover is possible with a particular customer, but also what it would be made up of. “Looking at the customer history, we determine for example that a tradesman has previously been buying insulating foam for 5,000 euros per year”, explains Jens Neumann. “Then we examine comparable customers. What have they bought? The conclusion could be that the salesman can also sell roofing panels for 5,000 euros and screws for 10,000 euros, making a potential total of 20,000 euros.” Breaking down the overall prediction into individual product range segments boosts the profit contribution. Together with Dastani Consulting, Würth has succeeded in enriching the existing data, thus significantly enhancing sales efficiency and creating a positive effect on the overall financial performance.
Adolf Würth GmbH & Co. KG is a specialist in the area of assembly and fastening materials with over 100,000 products. In Germany, more than 500,000 trade, construction and industrial customers regularly purchase Würth products. Around 3,000 permanent salespeople provide country-wide personal service, supported by over 400 regional sales offices. Adolf Würth GmbH & Co. KG is market leader in Germany and employs around 6,300 people. Turnover amounted to 1.49 billion euros in the 2014 financial year (including company-internal turnover), of which about 13 percent resulted from e-business.
