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While e-Commerce sites continue in their struggle to find ways to give customers a shopping experience that matters, models that predict the potential value of each customer have become essential. These models enable retailers to provide enhanced services for the best customers and save money on marketing campaigns. This type of business optimization technology is becoming increasingly important to companies under pressure to add value to customers while simultaneously cutting costs and maximizing resources. The e-CLV model is typical of the technology IBM business consultants are helping companies implement to achieve better service levels with decreasing IT costs.
Although models that predict a customer's value already exist, they don't take into account the new breed of online shoppers or cannot see the big picture that is available only by looking into individual historical data. This data includes the type of items bought in the past and at what frequency. Existing technology can only identify a customer's lifetime value once they have a notched up a significant purchase history with a specific online site.
The e-CLV technology developed by the Business Transformation Group allows retailers to estimate the potential lifetime value of relatively new customers. It works not only by "learning" from the spending patterns of a single customer, but also from the online activity of other more established customers. By monitoring the buying behavior during the initial visits of a new customer, the model can assign the customer to a group that has a specific "buying profile" and predict spending patterns based on the behavior of others in the same group.
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