Deriving Call Data Record Insights through Self Service BI Reporting

Deriving Call Data Record Insights through Self Service BI Reporting

The Need for Business Intelligence BI assists corporate managers and decision makers to make relevant, accurate, timely and smart decision in an organization and thus lead to increase in productivity and profitability of an organization. BI combines business processes with IT systems to support decision-making in an organization. In order to succeed in the market, telecommunications companies are not competing solely on price. They have to expand their services based on their knowledge of customers needs gained through the use of call detail records (CDR) and customer demographics. The telecommunications market is now highly competitive. Companies in the telecommunications industry are facing conditions that are unlike those that exist in any other sector. Consolidation is happening at a record pace, allowing businesses to instantly expand their product lines and enter new markets. And convergence strategies are emerging quickly, as carriers strive to serve as all-in-one providers, offering everything from voice and Internet, to video, data, and multi-media services. Customers are able to switch providers easily, because there are many of them available. In order to understand their customers and create a better environment for managing customer relationships, many telecommunications companies use call detail analysis to achieve competitive advantage. By understanding customers characteristics and behavior, it is possible to successfully tailor services that meet customers needs. These shifting business models have made the need for business intelligence extremely critical for telecommunications companies perhaps more so than in any other industry today. 2

Telecommunications Industry Overview and Major Trends In the U.S., the telecommunications sector drives more than $1 trillion in annual revenue. Worldwide, the industry accounts for about $3.5 trillion. There are nearly 7 billion mobile subscriptions worldwide. This is equivalent to 95.5% of the world population. Traditional telecommunications service providers must leverage the Internet and the new types of services it can provide. Major telecommunications vendors are focusing on bundled service packages which combine wireless accounts, very high speed Internet access, entertainment such as video on demand and Internet TV, in addition to VoIP or landlines. MOBILE SUBSCRIPTIONS WORLDWIDE = 7 BILLION 95.5% World Population TELECOMMUNICATIONS SECTOR ANNUAL REVENUE $3.5 Also, traditional telecommunications service providers need to create innovative new valueadded services that are accessed online. For example, consumers might respond well to online services that monitor home security or adjust home energy usage, or services that monitor the movements and needs of elderly family members at home. $ Trillions U.S. $1 Global The competitive landscape continues to shift dramatically due to mergers and acquisitions. Government regulations are bringing big changes to business strategies as they continue to evolve quickly. Overall, the telecommunications industry is in a state of continuous technological and economic flux, driven by intense competition and new technologies. TELECOMMUNICATIONS SERVICE PACKAGES High Speed Internet Wireless Accounts VoIP & Landlines Internet TV 3

The 8 Core Areas of Improvement through BI for Telecommunications CUSTOMER PROFITABILITY It is imperative they acquire new, profitable customers as well as increase the profitability of existing ones. CUSTOMER SEGMENTATION Segmentation is used to segregate customers who exhibit common characteristics in different segments. CROSS SELLING This can be a major source of selling for a telecom company. For effective crossselling, existing data can be leveraged using business intelligence solutions to quickly zero in on new products that may be required by existing customers. BUDGETING Data warehousing facilitates analysis of budgeted versus actual expenditure for various cost heads like promotion campaigns, product development, infrastructure maintenance, investments, commissions, etc. CUSTOMER ATTRITION Acquiring new customers is much more costly than retaining existing ones. Customer attrition analysis is an essential step in customer retention. ANALYZE CUSTOMER USAGE Telecom operators need to analyze customer usage pattern in various dimensions. This is important in order to understand why customers have behaved in a particular way at a particular time. For example, customers may have different calling habits depending on tariff plan, available service, time of the day, and so on. These analyses also enable the discovery of hidden behavior, which has not been noticed in the past. CAMPAIGN ANALYSIS Campaign analysis is used to analyse the effectiveness of a marketing or promotion campaign. The effects of a particular campaign on sales of the promoted product can be tracked using business intelligence solutions. FORECASTING To plan their networks, telecom service providers perform forecasting that helps operators to make key investment decisions. 4

Typical Results within a Year of Implementation Constant access to reports from anywhere, at any time, through browser based or mobile applications. Automated import of measurement data from a wide variety of sources allows for automatic creation of up-to-the-minute reports. The time required to turn around a request for detailed call records shrinks by up to 80%. Reduce the average time to load a day s worth of data from 2 hours to under 10 minutes. Decision making process moves from an observation to a prediction model. After implementing BI for a telecom client, a key insight was discovered that critical business and marketing decisions were being based on daily revenues that were approximately 15-20% less than the actual amount. Perform real-time analysis on vast amounts of CDR data generated and analyze historical data of CDR in order to identify customer value and make strategic decisions to retain, attract new customers and ensure their satisfaction towards increasing profitability. Supports rapid implementation of warehousing solutions with meaningful data. Facilitates a structured approach to subsequent customization and extension of the data warehouse. Enables business users to more effectively control and reduce time taken to scope their requirements. Provides a solid basis for statutory reporting and relationship management supporting decision making and executive information applications. Minimizes development costs. Reduces the risk of failure by facilitating an incremental approach to delivering an integrated data warehouse solution. Fosters collaboration between business and IT to turn business requirements into actionable solutions. Comprehensive collecting content from multiple client engagements and turning it into a suite of related Subject Areas - with a proven methodology and models that require minimal customization. Delivers competitive advantage by enabling clean data consolidation across multiple systems. 5

Common Areas of Influence for BI Data USAGE & TRAFFIC BEHAVIOR QUESTIONS THAT BI CAN HELP ANSWER Customer behavior analysis by customer segment, by product and by service. Behavior call pattern analysis, call pattern and traffic analysis, call location analysis. Which product has the highest demand with retailers in specific geographic locations? Performance of retailers by location or in a particular period or both. Call usage behavior analysis. Traffic behavior analysis by customer/service. What is the usage (behavior) of our customers? Which customers generate the most important % of the total traffic? And what products they are using? What are the traffic patterns of customer X? Usage and trends during peak and off-peak. Which products/services/features are used by customer X? By segment Y? What is the usage behavior of customer X? Segment Y? P&S usage analysis by customer/product/segment. What is his call pattern? What is the usage trend/pattern and revenue pattern during a customer life cycle? Why did he change his behavior? What is his usage preference? What is the usage behavior by product/customer/ month (including historical analysis and historical comparison)? What VAS application are the customers actually using through the Internet? Which customers are using service X from state to outside? Which promotion has been the most popular and can be used in near future? Which location has minimum number of mobile connections? Comparative analysis of the performance of sales executives based on factors such as gender, age group, region. Which area witnesses maximum call traffic? What day of week witnesses maximum call traffic? On which day of the year was the maximum number of SMS sent? REVENUE & MARKETING QUESTIONS THAT BI CAN HELP ANSWER What is the average revenue by customer ARPU? ARPU for VAS? ARPU for 3rd party VAS? Average margin AMPU? Who generates the most important revenue in my customer base? By P/S? By segment? By Channel? By category (music, fun, info, data) and platform (WAP, SMS, Web)? Who are my top 10 customers (individuals and organizations)? Who are my top 10 customers in segment Gold? Platinum? Silver? Bronze? What is the revenue growth by customer? Segment? Revenue breakdown by subscription, contract, billed amount, P/S and individual. Customer purchasing behavior impact on the revenue? Revenue variance this month vs last month? Revenue variance analysis. Revenue trends. Impact of major events on the revenue and trends? Revenue breakdown by cell, BSC and MSC. Impact of campaigns on the target revenue? Impact of price reduction on the revenue? Cannibalization. Analyzing daily refill by agent? Which customers generate 80% of my revenues? What is the revenue of customer X? What is the revenue generated by cluster Y? What is the revenue generated by segment Z? Who are my top X customers from a contribution perspective and/or revenue perspective and/or usage perspective? Revenue breakdown by contract type/maintenance amount/rent amount/billed amount. CHURN PREDICTION, PROFILING, AND HISTORY MADE EASY Customer demographic patterns. Customer spend/call/contact pattern. Customer roaming pattern/network usage pattern. Network specific customer span pattern. Network specific long-term vs short-term customer spend pattern comparison. Correlation patterns with demographic/behavioral/ other customer data. Churn history profiling and patterns and interpredictor correlation. Network specific churn index. Build customer specific indexing. Network specific churn predictor index. Customer specific/predictor indexing. Customer churn profile predictions. 6

Business Advantages of Analysis for Telecommunications Placing intelligence about the company in the hands of executives enables senior management to run the company better, while intelligence available at the fingertips of mid-level management and frontline knowledge workers enables far more accurate decision making and supports a more productive and effective workplace. PROFIT IMPROVEMENT Gained from increasing the velocity, rationing and targeting of marketing programs and incentives to customer segments with proven contribution potential. PROFIT Gained from transaction/service costing, pricing/costing rules, actual charges and discounts, historical activity and price performance etc. improve revenue and profits by acquiring and retaining high-value customers; reduce costs through more effective and responsive management; automate compliance with regulatory reporting requirements; and improve customer loyalty through improved quality and superior service delivery COMPETITIVE ADVANTAGE Gained from better understanding the customer s total telecommunications wallet and identifying and reacting to usage defection across the service and content value-net. CUSTOMER INTELLIGENCE Gained from understanding subscriber value across lifecycles and product lines. Improved response to customer needs using proactive and reactive programs focused on building and retaining a valuable subscriber base. OPERATIONAL EFFICIENCIES AND RISK MITIGATION Gained from improvements in process assurance and the minimization of operational risks (e.g., credit management). 7

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