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КСИ Сезон 2017

Analytical Support for Customer Care
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Analytical Support
for Customer Care

In the markets with high penetration of communications services and introduction of 3G networks, telecommunications operators face new challenges and increased competition. In such environments, the premium quality of service and tailored approach to customer care become the most effective and reliable means to acquire new customers and retain existing ones, increase the operator’s profit margins and consolidate its market position. Today, professional and accurate analysis of customer data, usage preferences, market situation, and service promotion strategies becomes the most efficient way to survive. At the same time, dealing with large volumes of customer data, operators need high-performance and full-featured business intelligence tools.

CBOSS offers analytical support for customer care – a state-of-the-art and effective CBOSSdm solution featuring sophisticated Data Mining methods.

CBOSSdm is purpose-built to:

  • Achieve customer segmentation to improve customer care quality
  • Find groups of customers with similar behavior to create loyalty campaigns
  • Build consumer baskets to boost sales.

System Operation

Key Features

CBOSSdm offers the following functionality:

  • Segmentation
    Using flexible models based on the Data Mining algorithms, CBOSSdm can achieve customer segmentation to identify:
    • value segments (e.g. high-, medium- and low-value)
    • profitability groups within value segments
    • customer groups with similar usage profiles (e.g. ‘preference for WAP/GPRS services’, ‘MMS users’, etc).

    Among other clusters, customer segmentation identifies a group of high-value customers making up just 2-3% of the customer base but generating up to 20% of the operator’s revenue.
    It is also possible to build and analyze marketing segments to facilitate marketing and advertising campaigns in alignment with the company’s strategies.
  • Churn forecasting
    Data Mining algorithms are used to analyze usage and create a list of customers with high propensity to churn. Behavior of such customers is very similar to the behavior of those who have recently left the operator. The system also generates a list of loyal customers. Such churn forecasting is a vital tool for effective marketing campaigns.
    To minimize errors and their consequences, the forecasting model can be validated on a test sample. The system generates a list of customers excluded from analysis and calculates such characteristics as churn forecasting accuracy, level of error (how many customers who left were considered loyal and how many loyal users were considered likely to churn), and accuracy of the prediction model as compared to random guessing.
    The solution identifies customers likely to churn with an 80% accuracy. Timely marketing campaigns aimed at retaining these customers can save over 30% of the revenue they generate.
  • Consumer baskets
    CBOSSdm can analyze which services are purchased together (consumer baskets) and:
    • Analyze contents of consumer baskets
    • Evaluate the size and solvency of the basket user group
    • Evaluate potential demand for communications services.

    Comparison of customers with similar baskets, differing by one service group only, allows telcos to identify target groups for promotion of the service.
    By analyzing history of service usage and deactivation, operators can identify the target group to promote services used episodically, but at much less level than by other customers with the same consumer basket.

In addition to the above metioned features, CBOSSdm offers the following supplementary functions:

  • User-defined datasets
    To build prediction models, the system enables to select data specific for a certain marketing objective and build a target dataset. In addition to standard service profile attributes, calculated parameters derived from the initial characteristics can be included (e.g. share of WAP/GPRS charges).
  • Service groupings
    Before the analysis, CBOSSdm enables to group services by type and/or by nature (e.g. voice, data, infotainment, etc). Each group may be characterized by total charges for each service, usage volume, and the number of usage events during the analyzed time period.
  • Customer lists
    CBOSSdm can generate and analyze customer lists. Lists can be imported from text files, generated from source datasets or by user-defined SQL queries. The system can also analyze and manipulate the existing lists. Moreover, in CBOSSdm the results of analysis and modeling can be registered as customer lists and used for further processing.
    Customer lists can be exported into external applications and systems integrated with CBOSSdm.


  • Stronger customer loyalty
    Identifying customers with a high propensity to churn, CBOSSdm allows the operator to develop and implement proactive customer retention campaigns. Based on the obtained analysis results, the operator can create unique offerings for each customer segment improving the service and customer care quality. Individual retention campaigns become available for high-value users. For other segments, telcos can offer tailored campaigns based on usage profiles and generated revenue. These steps result in stronger customer loyalty, increased time with the company, acquisition of new customers, stronger market position, and generation of new revenue streams.
  • Reduced costs of service promotion and deployment
    Identifying the needs of all target groups, the operator can create very attractive service offerings. With CBOSSdm, the telco’s marketing campaigns are accurately planned, tailored to match the needs of the target segment and, consequently, exceptionally cost-effective.
  • Efficient use of accumulated data
    CBOSSdm uses continuously accumulating customer data for new product launches, loyalty campaigns, and sales boosting. Customer characteristics are updated on a monthly basis.
  • Scalability and integration
    CBOSSdm is easily scalable to accommodate customer base growth. Also, to make full use of the existing functionality, CBOSSdm can seamlessly integrate with other CBOSS products, including:
    • CBOSSbcc Billing & Customer Care
    • CBOSSmcm Marketing Campaign Management.
  • Scientific approach to data analysis
    Mathematical methods used make customer data analysis objective and strategy-driven. In several-hundred thousand (and even multi-million) subscriber bases, every dollar misspent on each subscriber will lead to significant losses, which can be prevented with CBOSSdm.
  • User-friendly and ergonomic interface
    CBOSSdm is designed for business users and requires only basic mathematical skills. Sophisticated mathematical methods and algorithms of data processing are concealed from the user. At the same time, CBOSSdm is very intuitive and provides rich visualization capabilities.

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