Marketing problems can be analysed from various angles as there is no comprehensive solution to all the interlinked and complex questions that the business will pose for the analysts.
Strategic decision making is a very sophisticated job and requires complete focus on the validity and applicability of the "go to market" plan that the data driven approach will suggest.
Let us review some new business questions today:
"which customers are going to stay put with us", "how long will they stick to my business","how much profit can i make from such long standing customers"
Buying behaviour of an average customer is getting impacted by multiple factors, called drivers, like product quality, value of the deal, branding of the product, promotion efforts, competitive space in the market etc. Many times the companies launch price offs, combo deals etc to retain their customers. Especially in a B2B space, customer relationship management is very crucial. Loss of a single big fish may prove very costly and even result in convolution of the brand in the market.
Hence, Marketers want to predict the longevity of the customer as well as their value in terms of profit. Here Customer lifetime value analysis can play a prominent role in suggesting the targeting strategy to the sales and marketing teams.
Retention predictions are usually done using survival analysis whereas profit predictions can be done using various methods like regression, cart or random forests.
In the next post i will discuss these topics in detail. So stay tuned....
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