Data Science Use Case: Van Marcke
Updated: Jun 2
What is Data Science?
Data Science focuses on the collection, modelling and interpreting of company data. This helps organizations reach better conclusions and make better decisions as a result of this data.
Van Marcke, a market leader in the specialized distribution of home plumbing and central heating, offers a diverse product range and cover an even more diverse customer portfolio. The technicians and plumbers account for the largest part of the company sales and are currently split into various segments.
CANGURU supported Van Marcke in developing a prototype enabling more intuitive and unbiased customer segmentation. An ideal customer was also developed per segment.
The current segmentation does not really resonate within Van Marcke’s teams, resulting in its often inconsistent application. The simplification of the segments (a reduction of more than half) and a more specific customer profiling provide a solution.
A reduction in the number of customer segments means that the evolution from the existing segmentation can be more easily followed-up. As a result of this, the right marketing actions can be undertaken quickly, such as the identification of customers with poor payment history, “lazy” returners, etc. Furthermore, new customers can be more easily assigned to the correct segment.
To make the new segmentation usable and understandable at all levels of the organization, the prototype currently focuses on a limited sample of parameters for a short period of time. This can be scaled up in the future to a wider set of parameters, as well as a longer timeframe.
As always, the principle of “there’s no data science without data!” applies. CANGURU has therefore also advised Van Marcke to collect certain data in more detail so that, in the future, further analysis can be carried out over a longer period of time.
CANGURU is a young and innovative consulting company based in Mechelen. The data science team helps companies reach better conclusions and make better decisions as a result of “smart data”. We implement the right tools to gather and compile qualitative data. We subsequently bring this information into the light which should help the company take the correct decisions.
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