Analytics project: Customer Segmentation and Profiling

SCOPE

      Bank’s large databases contain customer’s information and history, which is often used to increase bank’s profitability, since they need to use more and better ways for analyzing their customers. As part of data mining techniques, customer segmentation and classification are easily applicable and very practical methods in analytical Customer Relationship Management (CRM). Most activities are concentrated on customer’s grade and their credibility to determine customer validity to take a loan. The major point for financial organizations is profiling customers according to their profitability for bank. At the end, this is what makes banks successful in their business.

APPLICATION

      In other words, with customer segmentation and profiling methods, we are able to get the most of our client’s database. Simply, with customer segmentation, we are dividing customer’s database into logical for the business groups. On the other hand, customer profiling is related to segmentation but goes one step deeper by creating a portrait of a customer. Combining customer segmentation and profiling is extremely powerful tool for customer behavior modeling because provides our clients the opportunity to improve customer’s CRM process.

      Trough our projects, we have developed many customer behavior models to navigate business activities such as:

  • targeting actual and potential customers,
  • offering incentive programs for retaining customers
  • offering  propaganda plans for attracting profitable customers and many others;

TECHNOLOGY

      Оur  analytical customer relationship management projects include activities such as capture, storage, extraction, processing, interpretation and reporting customer’s data provided by our clients, so it can be analyzed according to our client’s needs. In each part of the process, we use the advancement of information technology and new systems for better interaction with the environment and ultimately to help clients to profit.

In order to identifying strategically significant customers, the analytical CRM system helps profile and segment existing customers. In customer profiling, we incorporate several aspects of customers into a sensible evaluation, for example:

  • customer details;
  • historical records and contact details;
  • customer attractiveness or customer satisfaction;
  • and any other available  aspects which can contribute for the analysis;

      Even that customer profiling is usually more orientated towards the operational function than the analytical function, it gives broader view of a customer and it is essential information to understand the true value of each customer and gain insights to realize customer behavior.

      Customer segmentation approaches are used to better understand customer’s preferences and to more efficiently allocate resources based on the available information. Thus, our clients benefit from better service differentiation by providing appropriate and suitable products and additionally, building up a competitive advantage. On the other hand, we guide them to their most valuable customers and navigate to allocate major capital, effort and time to generate more profit.

      For our data mining projects, we first gather the necessary data for performing. Then, based on customer behavior, for example usage of bank card, segmentation is done, where each segment is labeled and each segment’s customer has been known by that label. For customer profiling, classification methods are used so that their target variable are customer’s segment name.

      Throughout our working experience, in this increasingly competitive environment, we see segmentation and profiling as a key method employed by banks to better understand and to service their customers.

The Toolbox

Strategic Planning and Analysis:

Competitive and functional strategy.

Change Management:

CAP, Workout.

Process Improvement:

Six Sigma, DMAIC, DMADV.

Programme Management:

PRINCE II, BCPM, SSADM.

analytics case studies

Analytics project: Predictive Modelling and Forecasting

Analytics project: Predictive Modelling and Forecasting Summary

Analytics project: Customer Segmentation and Profiling

Analytics project: Customer Segmentation and Profiling Summary