Analytics for U.S. Telecoms

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Telecommunications service providers in the US can leverage advanced analytics to improve customer retention and average revenue per user, and offer more relevant products and services.

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Analytics for U.S. Telecoms

  1. 1. How U.S. Telecoms Can More Effectively Convert Data to Foresight Cognizant Research Center | September 2011©2011, Cognizant
  2. 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-Ex1 | ©2011, Cognizant
  3. 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 failure2 | ©2011, Cognizant
  4. 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 service3 | ©2011, Cognizant
  5. 5. 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 intelligently4 | ©2011, Cognizant
  6. 6. 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 services5 | ©2011, Cognizant
  7. 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. 8. 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 ones7 | ©2011, Cognizant
  9. 9. 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
  10. 10. 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
  11. 11. 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 disliked10 | ©2011, Cognizant
  12. 12. 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 service11 | ©2011, Cognizant
  13. 13. 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 profitability12 | ©2011, Cognizant
  14. 14. 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 settlements13 | ©2011, Cognizant
  15. 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 resolved14 | ©2011, Cognizant
  16. 16. 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 analytics15 | ©2011, Cognizant
  17. 17. 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
  18. 18. 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 service17 | ©2011, Cognizant
  19. 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/telecommunications18 | ©2011, Cognizant

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