Analytics as a tool for service quality
Customer experience and retention are inherently tied to service quality. However, with the rapid growth of devices and applications, and the pressure on network capacity, maintaining consistent service delivery poses significant challenges.
It's important to define key performance indicators that reflect a superior customer experience to support planning and service delivery, and provide measurable outcomes to evaluate performance.
Analytics plays an important role in service quality and capacity planning:
- An effective analytics platform can monitor the performance of the network, predict service failures and reduce the risk of unexpected downtime
- Trends analysis can forecast bandwidth growth by location thereby triggering investments where additional capacity is needed
- Big data technology can help optimize data routing and bandwidth, especially during temporary spikes in demand such as major sporting events
Strong focus on customer value
Imagine if big data analytics could be used to gain real-time insight into subscriber usage patterns, preferences and interests. These insights can help capitalize on opportunities and partner more effectively with new OTT providers. The reality is, however, that few CSPs have a consistent approach to data analytics or access to analytics skill sets across key disciplines.
Rather than simply increasing the average level of customer experience, it's possible to focus on specific customer lifetime value to provide the best return on investment. Analytics should be aiming for:
- More personalized, innovative and efficient services and offers leading to greater customer satisfaction, less churn and an increase in the average revenue per user
- A rich and detailed single view of the customer for advanced segmentation, incentive and campaign targeting and price plan optimization, improved operational efficiency, lower operating cost and improved customer service with faster response times
Success of the program can be measured through improvements in operational, bottom-line and superior customer experience.
An approach that covers all bases
An effective approach to customer experience and analytics is company-wide and cross-functional. It requires an holistic vision that bridges business functions such as marketing and products, and technical functions such as IT and network operations. It must also embrace different organizational boundaries, responsibilities and processes with well-defined roles to support clear business outcomes.
New initiatives are assessed using a business impact analysis that features capital and operating expenses, and quantifies savings and direct revenue gains. The benefits and impacts can be defined across the organization from the operations and network department, to marketing and customer service teams.
Industry benchmarks are critical for the main KPIs to help quantify cost reductions, revenue and margin improvements, operational efficiencies and customer experience.
Every technology investment requires a business impact analysis to inform decision-making and to demonstrate how customer experience management solutions can impact the bottom line.
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