Customer Value Optimization
Help service providers understand their customers to serve them better, thus Analytics is a step ahead of business intelligence (BI).
In most businesses, decision makers are often faced with the task of selecting the best possible strategy from a large set of feasible options. A crucial work of the decision making process is the selection of an optimal strategy. From a data-mining perspective, the problem of strategy selection is to identify the best strategy that has the potential to outperform the baseline performance with consistent returns in the future. Given the fundamental problem definition, the approach involves discovering useful patterns or relationship in the data using models, and applying that information to identify whether a selected strategy is an optimal one.
Optimization involves the use of analytical techniques to better manage operations, resources, information and infrastructure . Data mining techniques are used to identify the solutions in the search space that are optimal and/or acceptable. These potential solutions are made available to the decision makers who can opt for the best action or alternative. It is also important to ensure that the solutions generated are comprehensible and satisfy the imposed constraints, as they are potentially utilized by an end-user for supporting decisions to be made.
Most data mining tasks fundamentally involve optimization concepts based on numerical analysis of data. The goal of most data mining tasks naturally lends itself to optimization of a predefined cost that is supposed to be minimized. Aside from complexity issues of the problem, the massive dimensionality of real world data mining problems is another difficulty arising in optimization-based data mining research.
- Improved customer satisfaction by personalized incentives and targeted marketing
- Addressing CRM challenges such as up-sell and cross-sell
- Optimal allocation of funds for maximum returns
- Optimal Inventory Management subject to demand
- Resource allocation and Scheduling