Decision analytics for monitoring and managing customer experience
Business Proposition
| - Demonstrates how a CSP can maximize the benefits of customer experience investments to achieve goals involving revenue, costs, and customer retention
- Demonstrates how departments responsible for decision making and operational monitoring can be aligned in a principled way through KPIs that represent key decision assumptions
- Allows a CSP to manage complexity by visualizing the interactions between tangible and intangible factors such as revenues, brand, investments, and decision outcomes by simulating existing business parameters and metrics
- Demonstrates a systematic approach to agile strategic and operational management, where the need to reconsider a decision is triggered by changes in operational KPIs
- Applies the CEM Control Center concept to use cases that are high on CSP’s agenda, like
- Shepherding successful products for enterprise customers from concept to cash; and
- Optimizing consumer mobile broadband product and service offerings
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TM Forum Standards in Use
for Development
| eTOM– detailing data collection and analytics related processes
TAM – detailing the role of enterprise management and product domain analytics
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Team Member Contributions
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Service Provider Champion
Service Provider Champion
Data Collection and Storage
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Mobile Broadband Customer Experience
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Business Process Definitions
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Decision Engineering
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Operational Analytics | | Demonstration Scenarios
| Scenario 1: Ideating successful products for mid-markets from concept to cash
A CSP wishes to launch a new product line. It considers the impact of various decisions (price, investment in sales training, etc.) on its goals (customer experience, brand, different margin measures at different points in time). The CSP implements a set of decisions, and monitors the product launch based on key decision assumptions, so that it knows when to reconsider pricing, marketing targets, and other decisions. To learn more, click here.
Scenario 2: Mobile Broadband Product Analytics
Service providers offer thousands of different products and services based upon mobile broadband platforms. However, for a CSP to select the features that provide the greatest value to itself and to its customers is a complex problem, involving choices around QoS, bandwidth, price, and other factors. This scenario shows how service providers can use a deep understanding of customers’ usage behavior, service experience, price tolerance, and other data to support maximize profitability.
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![[Open Quote]](/sdata/content/icons/quote_open.png) We see mobile broadband as a main service in Vodafone's portfolio. Advanced modeling and measurement of customer experience with mobile broadband services lays the basis to improve our product offerings in this area with the clear goal of optimizing customer value, reducing churn and improving customer loyalty.![[Close Quote]](/sdata/content/icons/quote_closed.png) | | – Karl Wilhelm Siebert, Director, Regional Networks & Operations Branch West, Vodafone |
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