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Client Base Analysis

As is well known, only clients produce profit therefore, most companies consider customer relationship management (CRM) an important element of their corporate strategies. Companies introduce and actively use CRM systems, however, most such programs have poor analytical capabilities, being designed for resolving such problems as data collection and automation of routine operations. The result is a catch-22 situation, when a company has much interesting and valuable information about clients but cannot convert this knowledge into a competitive advantage.

In order to make use of the information accumulated in the CRM system, it is not enough to receive reports — the company has to find patterns in large volumes of data and take them into account when dealing with clients. The objective of this work is to individualize the work with every customer, taking into account their interests, preferences and capabilities. Loginom is a powerful tool for comprehensive analysis of the client base:

  • Client ranging. Ranging the clients by importance, profitability, loyalty and prospects improves the company’s operating efficiency because it allows the company to concentrate attention on the most valuable consumers. Loginom automatically selects and shows the best and the worst clients in any slices, calculates each client’s input in the overall result and computes efficiency indicators.
  • Client segmentation. One of the classical ways to optimize servicing of clients is by clustering them (segmentation) i.e. separating them into sufficiently uniform groups, finding out the characteristic properties of each segment and making proposals which take into account the identified regularities. Loginom contains algorithms that allow high-quality clustering to be performed and take into account the influence of diverse factors.
  • Preferences analysis. Creating more attractive customer proposals requires understanding the reasons that customers choose one product or another. Loginom offers mechanisms for rule discovery and pattern search. Using these, not only can companies find these regularities, but also interpret and explain them.
  • Forecasting. Prediction modeling allows forecasting of demand and evaluation of how it is affected by various factors. Loginom contains a complete set of algorithms used for developing prediction models.
  • Advertising action planning. Analyzing the useful effect of advertising actions is a complicated task because it is difficult to distinguish a single factor, while their mutual influence is anything but simple. Loginom contains tools for developing complex nonlinear models. Their use allows the effect of marketing actions to be evaluated and "What if" modeling of the situation to be performed.

Loginom also contains many other mechanisms for analyzing the client base, including consolidation, reporting, data enhancement and cleansing. These tools can work with both internal and external information including market trends, competitive environment, demographic parameters and location information.