In the previous post we presented a few methods of data analysis, which are used to identify customer needs and preferences and allow us to predict their behavior. Such knowledge results in building better marketing and sales offers which meet specific customer expectations.
In today’s article we present further examples of Data Mining methods that can be applied in daily business operations.
| Challenge | Solution – analysis type | Benefits |
|---|---|---|
| The Marketing Department has to determine which marketing strategy to apply to selected customers depending on their potential value. | Lifetime Value Analysis Lifetime Value (LTV) analysis is used for assessing the current value of future customer profits – it estimates the expected profit a customer will generate during the whole period of using the company’s services. |
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| The Sales Department has to determine the volume of sales in the next quarter. | Sales forecasting This solution applies methods of stochastic processes analysis to predict profit or sales volumes on the basis of data like profit and sales volume in the previous periods, changes in macroeconomic conditions, the results of competitors’ promotional campaigns or other random factors. |
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| The CRM Department has to determine when to intensify efforts in order to maintain the selected clients. | Survival Analysis The main purposes of Survival analysis are to estimate the time a customer will subscribe to a service or estimate the probability of customer’s defection in subsequent life cycles. This information allows the company to determine the predicted period of retaining the customer and introduce an appropriate loyalty policy. |
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| The Marketing Department aims to determine which set of features of a given product is preferred by customers and how this product shows out against the competition. | Conjoint Analysis Conjoint analysis allows to compare different variants of a given offer on the basis of their usability to customers. The result of Conjoint analysis is the selection of the best combination of features for the analysed offer. |
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