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.

1. How U.S. Telecoms Can 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
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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
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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
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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 intelligently
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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 services
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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.
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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 ones
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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.
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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.
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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 disliked
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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 service
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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 profitability
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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 settlements
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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
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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 analytics
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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.
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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 service
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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
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