How U.S. Telecoms Can More
             Effectively Convert Data to
             Foresight
              Cognizant Research Center | September 2011




©2011, Cognizant
Driving Forces

      •     CSPs (Communication Services Providers) operate in an increasingly tough environment
              •    Declining average revenue per user (ARPU) in the wireless voice area, countervailing the
                   increase in data ARPU
              •    Increasing competition from non-traditional players—mobile virtual network operators
                   (MVNOs) and over-the-top (OTT) providers such as Skype, Yahoo and Google
              •    Growing technology complexity
              •    Mounting mobile broadband customer base
              •    Increasing customer demands for ubiquitous and customized services
              •    Pressure to reduce Cap-Ex and Op-Ex




1   | ©2011, Cognizant
Driving Forces
    •    CSPs must regularly contend with:

                   •     Fleeting customer loyalties, made easier by the implementation of mobile number
                         portability
                   •     Billing abnormalities
                   •     Revenue leakage
                   •     Call failure




2   | ©2011, Cognizant
Customer-Centricity Imperative


              •    According to a Bain & Company study, a 5% increase in customer retention can improve
                   profitability by 75% for any company

              •    CSPs have put greater emphasis on improving customer experience in a bid to retain
                   customers amid challenging business conditions

                     o   As a result, they have prioritized on tools that help deliver improved customer
                         service




3   | ©2011, Cognizant
The Need for Analytics

      •     Improve customer service

              •    CSPs posses rich and abundant customer data

              •    Leveraging this data using advanced analytics will enable them understand their
                   customers, predict their future requirements and make effective decisions



      •     Network management

              •    Providing customers around-the-clock connectivity requires efficient network capabilities

              •    Network analytics allow CSPs to continuously monitor network performance, identify
                   bottlenecks, address capacity concerns and utilize network infrastructure intelligently




4   | ©2011, Cognizant
Analytics for Improved Customer Relationship Management


    •       CSPs have enjoyed limited success with their CRM initiatives


              •     Analytics provide CSPs a 360-degree view of customers and allows different groups in an
                    organization to leverage this information


              •     Further, they aid in:
                      o      Identifying prospective customers
                      o      Predicting customer needs
                      o      Designing targeted marketing campaigns
                      o      Providing customized services




5       | ©2011, Cognizant
•     To manage its growing operations, India’s Bharti Airtel deployed CRM
                    analytics allowing sales teams to generate accurate leads from its customer
                    database, improving the conversion of prospective customers into paying
                    customers.



6   | ©2011, Cognizant
Analytics for Improved Customer Relationship Management

    •       Customer lifetime value (CLV)
                      •      Reveals how much a new customer is worth
                      •      Determines which customer segments provide better opportunities




    •       Customer profitability analytics
                      •      Allow CSPs to determine their most profitable customers
                      •      Reveals why some customers are not profitable and helps identify ways to convert
                             them into profitable ones




7       | ©2011, Cognizant
Analytics for Improved Customer Relationship Management

    •    Targeted marketing campaigns

                   •     Customer segmentation analysis allows CSPs to design marketing campaigns tailor-
                         made to address the needs of each segment
                   •     For example, high-value customers can be identified and offered special tariffs and
                         services that incent them to stay longer without compromising profitability
                   •     Predictive analytics can be used to understand the purchase behavior of customer
                         segments, resulting in better ROI for campaigns

    •    Campaign analysis
                   •     Helps in studying the efficacy of marketing campaigns and design efficient future
                         campaigns
                   •     Real-time campaign analysis allows marketers to measure each and every aspect of a
                         marketing campaign and take immediate corrective actions, resulting in efficient
                         utilization of budget and resources.

    •    In 2011, U.S. Cellular deployed campaign analytics resulting in a more than 200%
         increase in campaign roll-outs per week, improved customer targeting, reduced time
         to measure and analyze campaign results, etc.

8   | ©2011, Cognizant
Analytics for Improved Customer Relationship Management

      •     Cross-Selling and Up-Selling

                     •   Affinity analytics or market-basket analytics enable CSPs to understand products (or
                         services) that are often bought together
                     •   CSPs can offer bundled services (up-selling) or new services (cross-sell), leading to
                         improved customer spending (increased ARPUs) and reduced campaign costs



      •     Churn management
                     •   Churn management solutions, including social network analysis, allow organizations to
                         identify customers who are most likely to churn based on their behavior
                     •   By analyzing data of lost customers, CSPs can understand factors that influenced the
                         movement and take steps to prevent further churn

      •     In 2005, Nextel (now Sprint Nextel Corp.) used analytics to successfully reduce
            churn by 30% to 1.4%, the lowest in the industry.




9   | ©2011, Cognizant
Analytics for Improved Customer Relationship Management

     •    Social network analysis

             •        Social network analytics helps in identifying proximities and relationships between
                      people, groups, organizations and related systems
             •        It reveals the strength of relationships, information flow within groups and identify the
                      influencers in the group
             •        By appeasing group influencers, CSPs can prevent mass churn and attract new customers
                      including those from competitors, and spread news about new offerings



     •     Social media analytics
             •        Tracking of social media (using tools such as text analytics) allows CSPs to comprehend
                      customer sentiment and gain a deeper understanding of their products and services
             •        For example, analyzing the chatter created on social media about a new advertising
                      campaign, CSPs will know what customers liked or disliked




10   | ©2011, Cognizant
Analytics for Efficient Network Management

     •    Capacity planning

                    •     The growth of broadband and smart devices is driving the demand for more bandwidth

                    •     CSPs must ensure that they do not overbuild capacity in anticipation or under-build

                    •     Real-time network analytics allow CSPs to understand current network usage and identify

                          regions where it is expected to grow vis-à-vis others


     •    Network monitoring

                    •     Network monitoring tools track network behavior and identify stress points before they impact the
                          network and connectivity.
                    •     By conducting root cause analysis of past network breakdowns future disturbances can be averted,
                          resulting in improved quality of service




11   | ©2011, Cognizant
Analytics for Revenue Assurance

     •    Fraud management

                    •     Companies lose nearly $72 billion to $80 billion (about 4.5% of revenues) annually to
                          global fraud
                    •     Fraud analytics tools aid to proactively identify customers exhibiting fraudulent behavior


     •    Customer risk management
                    •     Some customers may not be able to pay their bills resulting in debt; an increase in the
                          number of such customers is putting pressure on the top line
                    •     Analytics help to proactively identify risky accounts and design less expensive tariffs to
                          reduce the burden on such customers without affecting profitability




12   | ©2011, Cognizant
Analytics for Revenue Assurance

     •       Revenue leakage

                       •      CSPs globally lose about $100 billion annually in revenue leakage primarily due to inter-
                              carrier settlements
                       •      The increase in billing complexity puts pressure on the existing legacy systems when
                              analyzing huge volumes of call detail records (CDRs)
                       •      Advanced analytics can process billions of CDRs quickly and efficiently, identify and plug
                              revenue leakage sources, resulting in accurate billing and inter-carrier settlements




13       | ©2011, Cognizant
Roadblocks

     •    Legacy systems and inefficient database management

                    •     CSPs typically have data residing in many independent legacy systems, often resulting in
                          data inconsistency
                    •     It is therefore important that data structures across the organization be standardized and
                          data issues resolved




14   | ©2011, Cognizant
Analytics for Competitive Advantage

     •       Role of the top management

                       •      Drive analytics adoption by defining specific goals such as improve profitability, reduce
                              errors, etc.
                       •      Focus on creating a strong organizational culture and lay emphasis on data-driven
                              decision-making
                       •      Create a collaborative environment by closely aligning business units with the team that
                              handles analytics




15       | ©2011, Cognizant
Embracing Analytics as a Service


     •    Partner with experts to:
                    •     Overcome challenges in handling huge amount of data

                    •     Deploy on-demand telecom analytics applications (via cloud computing) that can save

                          critical Cap-Ex and gain Op-Ex flexibility

                    •     Experience the benefits that are more extensive than traditional BPO.




16   | ©2011, Cognizant
Analytics for Efficient Network Management

     •    To experience the full potential of analytics, CSPs need to do the following:

                    •     Develop enterprise-wide data architecture
                    •     Identify key areas for deploying analytics
                    •     Design a comprehensive strategy for adoption and implementation of analytics, including
                          information technology
                    •     Develop a fact-based decision-making culture focusing on achieving specific goals
                    •     Formulate strategies to capitalize on unique data, instead of copying the competition
                    •     Continuously renovate and renew analytics implementation
                    •     Enter into relationships with the right partners capable of providing analytics as a service




17   | ©2011, Cognizant
Thank You
            Vinaya Kumar Mylavarapu, Cognizant Research Center

            Jayendra Ramesan, Director and Practice Leader, Cognizant Enterprise Analytics
            Practice

            Read the complete white paper:
            How U.S. Telcos Can More Effectively Convert Data to Foresight

            For more information, please visit:
            http://www.cognizant.com/telecommunications




18   | ©2011, Cognizant

Analytics for U.S. Telecoms

  • 1.
    How U.S. TelecomsCan More Effectively Convert Data to Foresight Cognizant Research Center | September 2011 ©2011, Cognizant
  • 2.
    Driving Forces • CSPs (Communication Services Providers) operate in an increasingly tough environment • Declining average revenue per user (ARPU) in the wireless voice area, countervailing the increase in data ARPU • Increasing competition from non-traditional players—mobile virtual network operators (MVNOs) and over-the-top (OTT) providers such as Skype, Yahoo and Google • Growing technology complexity • Mounting mobile broadband customer base • Increasing customer demands for ubiquitous and customized services • Pressure to reduce Cap-Ex and Op-Ex 1 | ©2011, Cognizant
  • 3.
    Driving Forces • CSPs must regularly contend with: • Fleeting customer loyalties, made easier by the implementation of mobile number portability • Billing abnormalities • Revenue leakage • Call failure 2 | ©2011, Cognizant
  • 4.
    Customer-Centricity Imperative • According to a Bain & Company study, a 5% increase in customer retention can improve profitability by 75% for any company • CSPs have put greater emphasis on improving customer experience in a bid to retain customers amid challenging business conditions o As a result, they have prioritized on tools that help deliver improved customer service 3 | ©2011, Cognizant
  • 5.
    The Need forAnalytics • Improve customer service • CSPs posses rich and abundant customer data • Leveraging this data using advanced analytics will enable them understand their customers, predict their future requirements and make effective decisions • Network management • Providing customers around-the-clock connectivity requires efficient network capabilities • Network analytics allow CSPs to continuously monitor network performance, identify bottlenecks, address capacity concerns and utilize network infrastructure intelligently 4 | ©2011, Cognizant
  • 6.
    Analytics for ImprovedCustomer Relationship Management • CSPs have enjoyed limited success with their CRM initiatives • Analytics provide CSPs a 360-degree view of customers and allows different groups in an organization to leverage this information • Further, they aid in: o Identifying prospective customers o Predicting customer needs o Designing targeted marketing campaigns o Providing customized services 5 | ©2011, Cognizant
  • 7.
    To manage its growing operations, India’s Bharti Airtel deployed CRM analytics allowing sales teams to generate accurate leads from its customer database, improving the conversion of prospective customers into paying customers. 6 | ©2011, Cognizant
  • 8.
    Analytics for ImprovedCustomer Relationship Management • Customer lifetime value (CLV) • Reveals how much a new customer is worth • Determines which customer segments provide better opportunities • Customer profitability analytics • Allow CSPs to determine their most profitable customers • Reveals why some customers are not profitable and helps identify ways to convert them into profitable ones 7 | ©2011, Cognizant
  • 9.
    Analytics for ImprovedCustomer Relationship Management • Targeted marketing campaigns • Customer segmentation analysis allows CSPs to design marketing campaigns tailor- made to address the needs of each segment • For example, high-value customers can be identified and offered special tariffs and services that incent them to stay longer without compromising profitability • Predictive analytics can be used to understand the purchase behavior of customer segments, resulting in better ROI for campaigns • Campaign analysis • Helps in studying the efficacy of marketing campaigns and design efficient future campaigns • Real-time campaign analysis allows marketers to measure each and every aspect of a marketing campaign and take immediate corrective actions, resulting in efficient utilization of budget and resources. • In 2011, U.S. Cellular deployed campaign analytics resulting in a more than 200% increase in campaign roll-outs per week, improved customer targeting, reduced time to measure and analyze campaign results, etc. 8 | ©2011, Cognizant
  • 10.
    Analytics for ImprovedCustomer Relationship Management • Cross-Selling and Up-Selling • Affinity analytics or market-basket analytics enable CSPs to understand products (or services) that are often bought together • CSPs can offer bundled services (up-selling) or new services (cross-sell), leading to improved customer spending (increased ARPUs) and reduced campaign costs • Churn management • Churn management solutions, including social network analysis, allow organizations to identify customers who are most likely to churn based on their behavior • By analyzing data of lost customers, CSPs can understand factors that influenced the movement and take steps to prevent further churn • In 2005, Nextel (now Sprint Nextel Corp.) used analytics to successfully reduce churn by 30% to 1.4%, the lowest in the industry. 9 | ©2011, Cognizant
  • 11.
    Analytics for ImprovedCustomer Relationship Management • Social network analysis • Social network analytics helps in identifying proximities and relationships between people, groups, organizations and related systems • It reveals the strength of relationships, information flow within groups and identify the influencers in the group • By appeasing group influencers, CSPs can prevent mass churn and attract new customers including those from competitors, and spread news about new offerings • Social media analytics • Tracking of social media (using tools such as text analytics) allows CSPs to comprehend customer sentiment and gain a deeper understanding of their products and services • For example, analyzing the chatter created on social media about a new advertising campaign, CSPs will know what customers liked or disliked 10 | ©2011, Cognizant
  • 12.
    Analytics for EfficientNetwork Management • Capacity planning • The growth of broadband and smart devices is driving the demand for more bandwidth • CSPs must ensure that they do not overbuild capacity in anticipation or under-build • Real-time network analytics allow CSPs to understand current network usage and identify regions where it is expected to grow vis-à-vis others • Network monitoring • Network monitoring tools track network behavior and identify stress points before they impact the network and connectivity. • By conducting root cause analysis of past network breakdowns future disturbances can be averted, resulting in improved quality of service 11 | ©2011, Cognizant
  • 13.
    Analytics for RevenueAssurance • Fraud management • Companies lose nearly $72 billion to $80 billion (about 4.5% of revenues) annually to global fraud • Fraud analytics tools aid to proactively identify customers exhibiting fraudulent behavior • Customer risk management • Some customers may not be able to pay their bills resulting in debt; an increase in the number of such customers is putting pressure on the top line • Analytics help to proactively identify risky accounts and design less expensive tariffs to reduce the burden on such customers without affecting profitability 12 | ©2011, Cognizant
  • 14.
    Analytics for RevenueAssurance • Revenue leakage • CSPs globally lose about $100 billion annually in revenue leakage primarily due to inter- carrier settlements • The increase in billing complexity puts pressure on the existing legacy systems when analyzing huge volumes of call detail records (CDRs) • Advanced analytics can process billions of CDRs quickly and efficiently, identify and plug revenue leakage sources, resulting in accurate billing and inter-carrier settlements 13 | ©2011, Cognizant
  • 15.
    Roadblocks • Legacy systems and inefficient database management • CSPs typically have data residing in many independent legacy systems, often resulting in data inconsistency • It is therefore important that data structures across the organization be standardized and data issues resolved 14 | ©2011, Cognizant
  • 16.
    Analytics for CompetitiveAdvantage • Role of the top management • Drive analytics adoption by defining specific goals such as improve profitability, reduce errors, etc. • Focus on creating a strong organizational culture and lay emphasis on data-driven decision-making • Create a collaborative environment by closely aligning business units with the team that handles analytics 15 | ©2011, Cognizant
  • 17.
    Embracing Analytics asa Service • Partner with experts to: • Overcome challenges in handling huge amount of data • Deploy on-demand telecom analytics applications (via cloud computing) that can save critical Cap-Ex and gain Op-Ex flexibility • Experience the benefits that are more extensive than traditional BPO. 16 | ©2011, Cognizant
  • 18.
    Analytics for EfficientNetwork Management • To experience the full potential of analytics, CSPs need to do the following: • Develop enterprise-wide data architecture • Identify key areas for deploying analytics • Design a comprehensive strategy for adoption and implementation of analytics, including information technology • Develop a fact-based decision-making culture focusing on achieving specific goals • Formulate strategies to capitalize on unique data, instead of copying the competition • Continuously renovate and renew analytics implementation • Enter into relationships with the right partners capable of providing analytics as a service 17 | ©2011, Cognizant
  • 19.
    Thank You Vinaya Kumar Mylavarapu, Cognizant Research Center Jayendra Ramesan, Director and Practice Leader, Cognizant Enterprise Analytics Practice Read the complete white paper: How U.S. Telcos Can More Effectively Convert Data to Foresight For more information, please visit: http://www.cognizant.com/telecommunications 18 | ©2011, Cognizant