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The document discusses customer experience management. It defines customer experience management as generating insights about customer experiences and preferences based on existing network and IT data to prioritize actions that improve customer experience and business outcomes. It provides examples of how customer experience management helped telecom operators gain operational efficiencies, increase competitive differentiation, and optimize profits by automating proactive and predictive actions throughout the customer journey.
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- 1. Making your customersfeel special with Customer Experience Management powered by the Nokia Siemens Networks For internal use 1 © Nokia Siemens Networks 2012
- 2. What is CustomerExperience Management? CEM generates insight about customer experiences and preferences based on the existing data in the operator‟s network and IT systems, and uses it to prioritize and take action that result in a better customer experience and business outcome. 2 © Nokia Siemens Networks 2012
- 3. Smartphone subsidies threatenthe bottom line Excellent experience throughout the customer journey, a profitable alternative “As the company that powers the smartphones we love, we all should love AT&T, right? ….” Gregg Heard, VP-brand identity and design for AT&T, April 2012 • Subsidies have fueled the huge success of smartphone vendors. • 12.4% increase in Vodafone s acquisition and retention costs in 2011* led to an unhealthy 3.2% decline in EBITDA (Wireless Intelligence, Q4 2011) • “Operators are trying to fight back against the impact that Apple is having on their business” (Walter Piecyk, BTIG brokerage, Bloomberg News, 16 of April) 3 © Nokia Siemens Networks 2012
- 4. High value customersdrive quality demands in Brazil 45% willing to pay 46% of customers are heavy users of advanced more for excellent services. network quality. 31% willing to pay 24% of customers extra for personalized consider network & mobile services. service quality as the main reasons to choose an operator. -24 Net Promoter Score for mobile Internet quality among high value 47% of heavy users customers. likely to churn during the next 12 months. Nokia Siemens Networks Customer Acquisition and Retention study 2011 4 © Nokia Siemens Networks 2012
- 5. Responding to customerdemands and boosting profitability Operational Efficiency Competitive Differentiation Profit Optimization Higher efficiency by merging Real-time network and business Automated, proactive & business & network data, action on individual subscriber predictive action throughout the converted into insight in a level to improve loyalty and customer journey to improve holistic view revenue loyalty and profitability European operator gains €3 M Vipnet differentiates with 10% faster Asian operator gains $64 M per year revenue and saves €3.7 M per year problem resolution and 15% from revenue and efficiency through efficient problem resolution improvement in call escalation improvements 5 © Nokia Siemens Networks 2012
- 6. Customer Experience Management Best-practiceinsight & action CEM on Demand – insight & action content packs information aggregation Data collection & Service delivery CEM Engine Analytics engine Reporting Action engine engine Business process orchestration 6 © Nokia Siemens Networks 2012
- 7. Customer Experience Management Best-practiceinsight & action CEM on Demand – insight & action content packs information aggregation Data collection & Service delivery CEM Engine Analytics engine Reporting Action engine engine Generate and store „smart‟ insight from the network. Business process orchestration Enable real-time response & drill down to causes. Operational Efficiency 7 © Nokia Siemens Networks 2012
- 8. Customer Experience Management Best-practiceinsight & action CEM on Demand – insight & action content packs information aggregation Data collection & Service delivery CEM Engine Analytics engine Reporting Action engine engine Turn insight into personalized Business process orchestration real-time action and leveraging best-in-class network know-how. Differentiation Competitive 8 © Nokia Siemens Networks 2012
- 9. Customer Experience Management Best-practiceinsight & action CEM on Demand – insight & action content packs information aggregation Data collection & Service delivery CEM Engine Analytics engine Reporting Action engine engine Business process orchestration Respond proactively and automatically in an instant to changing customer needs. Optimization Profit 9 © Nokia Siemens Networks 2012
- 10. Case study 1– Understanding customer satisfaction Intelligence - drivers Customer Experience Index European Operator • Rapid data growth. Perception gap (MBB service) Insight: • Keen to retain brand strength with increasing There is a challenges and competition. ? disconnect between # customers network KPIs and • Clear focus on efficient customer experience satisfaction survey delivery. results. CMO – “I need to Poor Performance rating Good understand the drivers of Network view Customer view customer satisfaction” 10 © Nokia Siemens Networks 2012
- 11. Case study 1– Understanding customer satisfaction Intelligence - drivers Customer Experience Index European Operator • Rapid data growth. Perception gap (MBB service) Insight: • Keen to retain brand strength with increasing There is a Accurately tuned CEI challenges and competition. ? reflects ongoing disconnect between customer KPIs and network perception # customers • Clear focus on efficient in real time, for all customer experience satisfaction survey customers and delivery. results. devices. CMO – “I need to Poor Performance rating Good understand the drivers of Network view Customer view customer satisfaction” 11 © Nokia Siemens Networks 2012
- 12. Case study 1– Understanding customer satisfaction Intelligence - drivers Customer Experience Index European Operator • Rapid data growth. Perception gap (MBB service) Insight: Insight: • Keen to retain brand strength with increasing Therethe atuned CEI With is AccuratelyCustomer challenges and competition. ? reflects ongoing disconnect between Experience Index, customer KPIscan see network perception # customers • Clear focus on efficient the operator and in real time, for all satisfaction survey customer experience the actual experience customers and delivery. results. per customer and devices. drill down to the factors affecting it. CMO – “I need to Poor Performance rating Good understand the drivers of Network view Customer view customer satisfaction” 12 © Nokia Siemens Networks 2012
- 13. Case study 2– Vipnet: Differentiating with 10% faster Customer Care problem resolution Automation Vipnet • Market leader in Croatia and pioneer in introducing mobile broadband data and video calling. • Ability of customer care personnel to resolve calls quickly was compromised by limited visibility across the network and systems. CMO – “We need to improve the problem resolution time to differentiate” CTO – “We need to reduce the number of escalations to technical support”. 13 © Nokia Siemens Networks 2012
- 14. Case study 2– Vipnet: Differentiating with 10% faster Customer Care problem resolution Automation Vipnet • Market leader in Croatia and pioneer in introducing mobile broadband data and video calling. • Ability of customer care personnel to resolve calls quickly was compromised by limited visibility across the network and systems. CMO – “We need to improve the problem resolution time Insight: to differentiate” • When customer calls about problems with mobile CTO – “We need to reduce broadband, the solution the number of escalations to identifies the cause: barred data technical support”. traffic when roaming and incorrect handset settings. 14 © Nokia Siemens Networks 2012
- 15. Case study 2– Vipnet: Differentiating with 10% faster Customer Care problem resolution Automation Vipnet • Market leader in Croatia and pioneer in introducing mobile broadband data and video calling. • Ability of customer care personnel to resolve calls quickly was compromised by limited visibility across the network and systems. CMO – “We need to improve the problem resolution time Insight: Action: to differentiate” • When customer calls about • With two clicks the call problems with mobile center agent solves the CTO – “We need to reduce broadband, the solution problems during the first the number of escalations to identifies the cause: barred data call. technical support”. traffic when roaming and incorrect handset settings. 15 © Nokia Siemens Networks 2012
- 16. Case study 2– Vipnet: Differentiating with 10% faster Customer Care problem resolution Automation Vipnet Outcome: • Market leader in Croatia and pioneer • Problems are spotted earlier and resolved in introducing mobile broadband data 10% faster. and video calling. • Percentage of calls solved without • Ability of customer care personnel to escalation has improved by 15%, reducing resolve calls quickly was costs and boosting efficiency. compromised by limited visibility across the network and systems. CMO – “We need to improve the problem resolution time Insight: Action: to differentiate” • When customer calls about • With two clicks the call problems with mobile center agent solves the CTO – “We need to reduce broadband, the solution problems during the first the number of escalations to identifies the cause: barred data call. technical support”. traffic when roaming and incorrect handset settings. 16 © Nokia Siemens Networks 2012
- 17. Case study 3– Gaining $64 M per year from revenue and efficiency improvements Intelligence, Device Manager CMO: “How can I CTO: “How can I be Large Asian Operator improve satisfaction proactive and ensure and loyalty?” best quality in mobile • Rapid mobile broadband growth. broadband?” • Rising churn and declining monthly ARPU even though network KPIs were improving. Churn % Monthly ARPU $ 17 © Nokia Siemens Networks 2012
- 18. Case study 3– Gaining $64 M per year from revenue and efficiency improvements Intelligence, Device Manager CMO: “How can I CTO: “How can I be Large Asian Operator improve satisfaction proactive and ensure and loyalty?” best quality in mobile • Rapid mobile broadband growth. broadband?” • Rising churn and declining monthly ARPU even though network KPIs were improving. Insight: • Wrong device settings preventing browsing. • Specific devices having a negative impact on service performance. • Heavy 2G who had 3G capable phones. 18 © Nokia Siemens Networks 2012
- 19. Case study 3– Gaining $64 M per year from revenue and efficiency improvements Intelligence, Device Manager CMO: “How can I CTO: “How can I be Large Asian Operator improve satisfaction proactive and ensure and loyalty?” best quality in mobile • Rapid mobile broadband growth. broadband?” • Rising churn and declining monthly ARPU even though network KPIs were improving. Insight: Action: • Wrong device settings preventing • Proactive and automated browsing. provisioning. Correction of • Specific devices having a negative device settings. impact on service performance. • Optimization of terminal • Heavy 2G who had 3G capable market mix. phones. • 3G up-sells to heavy users. 19 © Nokia Siemens Networks 2012
- 20. Case study 3– Gaining $64 M per year from revenue and efficiency improvements Intelligence, Device Manager Outcome: Large Asian Operator $64 M per year • Rapid mobile broadband growth. from device • Rising churn and declining monthly provisioning and ARPU even though network KPIs correct device were improving. settings. Insight: Action: • Wrong device settings preventing • Proactive and automated browsing. provisioning. Correction of • Specific devices having a negative device settings. impact on service performance. • Optimization of terminal • Heavy 2G who had 3G capable market mix. phones. • 3G up-sells to heavy users. 20 © Nokia Siemens Networks 2012
- 21. Case study 4- Improved revenue and reduced busy Customer mgmt: hour demand Cost & billing/Service & device portfolio Medium-sized Western European operator • Rapid data growth. • CAPEX demand driven by narrow peak hour. Developed Market • Revenues not growing in Quality “Others” proportion to usage. sensitive 23 % COO - “Help me reduce 44 % busy hour demand, but increase my revenues 25 % as well” 8% Price elastic Price sensitive 21 © Nokia Siemens Networks 2012
- 22. Case study 4- Improved revenue and reduced busy Customer mgmt: hour demand Cost & billing/Service & device portfolio Medium-sized Western European operator • Rapid data growth. • CAPEX demand driven by narrow peak hour. Developed Market Smartphone Daily Volume Profile • Revenues not growing in Quality “Others” proportion to usage. sensitive 23 % Usage (MB) COO - “Help me reduce 44 % Quality busy hour demand, but sensitive increase my revenues 25 % as well” 8% Price sensitive Price Price elastic elastic Price sensitive 00:00 02:00 04:00 06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 22 © Nokia Siemens Networks 2012
- 23. Case study 4- Improved revenue and reduced busy Customer mgmt: hour demand Cost & billing/Service & device portfolio Insight: Segmentation Medium-sized Western European operator • Rapid data growth. • CAPEX demand driven by narrow peak hour. • Revenues not growing in proportion to usage. COO - “Help me reduce busy hour demand, but increase my revenues as well” 23 © Nokia Siemens Networks 2012
- 24. Case study 4- Improved revenue and reduced busy Customer mgmt: hour demand Cost & billing/Service & device portfolio Insight: Segmentation Medium-sized Western European operator Action: proposal of new • Rapid data growth. app to stimulate device or more usage. • CAPEX demand driven by narrow peak hour. Outcome: A further 3% • Revenues not growing in achieved revenue increase proportion to usage. segment. from this COO - “Help me reduce Action: offer differentiated busy hourQoS for a price premium. demand, but increase my revenues as well” Outcome: improved loyalty. 24 © Nokia Siemens Networks 2012
- 25. Case study 4- Improved revenue and reduced busy Customer mgmt: hour demand Cost & billing/Service & device portfolio Insight: Segmentation Medium-sized Western European operator Action: proposal of new Action: targeted • Rapid data growth. app to stimulate device or discounts to grow usage. more usage. • CAPEX demand driven by narrow peak hour. Outcome: 8% additional Outcome: A further 3% • Revenues not growing in achieved revenues. revenue increase proportion to usage. segment. from this COO - “Help me reduce Action: offer differentiated Action: enforce policy busy hourQoS for a price premium. demand, but controls. increase my revenues as well” Outcome: improved Outcome: Busy hour loyalty. usage reduced by ~15%. 25 © Nokia Siemens Networks 2012
- 26. Facts & Figures 26 © Nokia Siemens Networks 2012
- 27. Thank you! For internal use 27 © Nokia Siemens Networks 2012
Editor's Notes
- #3 Então, o que é de fato necessário para que se possa prover uma experiência excelente ao usuário durante todo o seu relacionamento com um operador?Historicamente observamos uma certa desconexão entre os clientes e seus operadores. A impressão que fica é que os clientes de fato só são lembrados ao final de cada contrato, quando são chamados a renovar seu contrato e retirar um novo celular subsidiado. Nada contra as pessoas ganharem celulares, mas esse negócio é de fato sustentável para o operador? Veremos mais adiante o que está acontecendo no mundo a este respeito.Nósacreditamosquepara de fatoproverumeexperienciaexcelenteaousuário final, osoperadoresdevemnãosomentecuidar dos seusclientesao final do contrato, massimobservaremdetalhes o queestaacontecendo com a experienciadesteclientedurantetodo o ciclo. Dessamaneiraao final do contrato, o clientenaovaiquerernempensarem se aventurar com outrooperador. Porestarsatisfeito, oumelhor, encantado com o serviçoquerecebe, eledarápreferência a manterseurelacionamento com o seuoperadoratual.Podeparecerficção, masgeraressetipo de relacionamento é possível, através de umabemimplementadaestratégia de CEM.CEM provêinformações (insights) acercadaexperiência e das preferências dos clientesindividuaisousegmentosse baseandoem dados jáexistentesnasredes, sistemas de TI dos operadores, etc, comovemosnascamadasacima. Tais dados sãoutilizadosparapriorizaraçõesemnível individual ou de segmentoafim de garantir a melhorexperiência do usuário e o melhorresultado de negóciopara o operador. Trata-se de um win-win, ambos osladosganhamnessaequação.Tais ações, não obstante serem disparadas para casos individuais, são executadas também em todas as camadas que observamos acima. Um exemplo é um usuário que tenha um problema de qualidade de rede pode disparar uma ação de otimização de rede, envolvendo além da rede propriamente dita, os sistemas de gerenciamento de rede e TI do operador. Proximo slide...
- #5 A NSN realiza anualmente uma pesquisa que avalia os drivers de aquisição e retenção de clientes para operadores de telecomunicações em mercados chave ao redor do mundo. Os resultados que obtemos a nível mundial corroboram a idéia de que CEM é a saída para operadores estabelecerem uma diferenciação sustentável.A mesma premissa também se aplica aos resultados obtidos no Brasil, especialmente se observamos o segmento de “usuários de alto-valor”, que são em geral formadores de opinião que utilizam serviços avançados mais que a média dos usuários e obviamente também gastam mais que a média.Se observarmososresultadosobtidospara o Brasil, chegamos a númerosbastanteinteressantes: - Primeiro, 24% dessesusuárioselencaramqualidade de rede e serviçocomo a razão primordial pelaqualelesMostinterestingly perhaps - they are also more likely to spend extra for special service like excellent network quality (53%) or special mobile services (36%). But the downside is that they are also less loyal than the average with a likeliness to churn within the next 12 months being as high as 33%. For this group, mobile Internet quality ranks as the most important reason to stay with an operator. This group are also 11% more dissatisfied with it than the average users. So, when thinking about where to invest – this group of heavy users are the high value customers who can certainly have a big impact on your business performance, especially when investments are done in quality.(Average spending for telecom services per month: 70 USD)
- #6 Response to customer demands – the path to regain profitabilitySo how can operators respond to these customer demands in a way that is also profitable for them?The answer depends on how far along they are in implementing Customer Experience Management solutions – what is their maturity phase. This varies a lot operator by operator across the world.Operational EfficiencyThe first phase includes operators who build up network and business insight across their organization, targeting one holistic view to the customer.Building holistic insight is a common starting point, in many cases driven by operational efficiency. This starts first by focusing on gaining end-to-end visibility to network, services and subscriber behavior, and then bringing together all the business and network data.NSN enabled one European operator in this phase to gain €3M in revenue and €3.7M savings by using Customer Experience Management for efficient and streamlined problem detection and resolution.Competitive DifferentiationOnce the operator has built this holistic view to network and business insight, the next step is to link the insight to business and operational processes in order ensure that the right network and business actions are taking place across the whole organization, and throughout the customer journey. Actions follow at an individual subscriber level, and in real time when needed. As a result, the operator can differentiate in the market with higher customer satisfaction levels for target segments and improve revenue from those customers.The actions are still reactive, and manual or semi-automated.A good example here is Vipnet who differentiates from competitors with 10% faster problem resolution and 15% improvement in call escalation with the help of our Customer Experience Management that speeds up request and complaint resolution time in customer care.Profit OptimizationThe third phase in this maturity path is still slightly visionary. It is the target towards which operators are moving. In this phase, problems are solved automatically before the customer even realizes them. The network adjusts automatically based on predicted customer behavior.In this phase, end-to-end automated business and operational processes enable automated, proactive and predictive actions along the customer journey. When actions happen behind the scenes and are personalized, real-time, proactive and even predictive, CEM has a profound and direct impact on efficiency, revenue, and profitability.Several operators have already implemented CEM use cases which are already in this category. An Asian operator is a good example which proactively solves problems for their subscriber base. By provisioning and correcting device settings proactively and automatically, the operator gains 64M dollars per year due to revenue and efficiency improvements.
- #7 Best-practice insight & actionThe heart of our CEM offering lies on the customer management layer. A CEM engine handles real-time reporting, analytics and actions, ensuring a seamless and automated flow.The CEM portal, or CEM on Demand, provides best-in-class insight & action content packs, incorporating the knowledge and experience gathered from 100s of customer cases.Real-time data is gathered from multiple sources, including the network, service and device performance, customer behavior and related revenue, the experience and service usage. Insight is used to prioritize and take concrete action across operator´s business processes and departments, from points of sale and care centers to field technical operations.The result is better customer experience and business outcome.We can link the different phases of the maturity path to this high level architecture. The first phase would be linked more to the reporting and analytics engines, while the second phase focuses on the actions and the third on the automated and real time loop which allows the operator to be proactive and efficient.Each of the bubbles (mapped to maturity phases) emphasizes our USP for that phase.
- #8 Best-practice insight & actionThe heart of our CEM offering lies on the customer management layer. A CEM engine handles real-time reporting, analytics and actions, ensuring a seamless and automated flow.The CEM portal, or CEM on Demand, provides best-in-class insight & action content packs, incorporating the knowledge and experience gathered from 100s of customer cases.Real-time data is gathered from multiple sources, including the network, service and device performance, customer behavior and related revenue, the experience and service usage. Insight is used to prioritize and take concrete action across operator´s business processes and departments, from points of sale and care centers to field technical operations.The result is better customer experience and business outcome.We can link the different phases of the maturity path to this high level architecture. The first phase would be linked more to the reporting and analytics engines, while the second phase focuses on the actions and the third on the automated and real time loop which allows the operator to be proactive and efficient.Each of the bubbles (mapped to maturity phases) emphasizes our USP for that phase.
- #9 Best-practice insight & actionThe heart of our CEM offering lies on the customer management layer. A CEM engine handles real-time reporting, analytics and actions, ensuring a seamless and automated flow.The CEM portal, or CEM on Demand, provides best-in-class insight & action content packs, incorporating the knowledge and experience gathered from 100s of customer cases.Real-time data is gathered from multiple sources, including the network, service and device performance, customer behavior and related revenue, the experience and service usage. Insight is used to prioritize and take concrete action across operator´s business processes and departments, from points of sale and care centers to field technical operations.The result is better customer experience and business outcome.We can link the different phases of the maturity path to this high level architecture. The first phase would be linked more to the reporting and analytics engines, while the second phase focuses on the actions and the third on the automated and real time loop which allows the operator to be proactive and efficient.Each of the bubbles (mapped to maturity phases) emphasizes our USP for that phase.
- #10 Best-practice insight & actionThe heart of our CEM offering lies on the customer management layer. A CEM engine handles real-time reporting, analytics and actions, ensuring a seamless and automated flow.The CEM portal, or CEM on Demand, provides best-in-class insight & action content packs, incorporating the knowledge and experience gathered from 100s of customer cases.Real-time data is gathered from multiple sources, including the network, service and device performance, customer behavior and related revenue, the experience and service usage. Insight is used to prioritize and take concrete action across operator´s business processes and departments, from points of sale and care centers to field technical operations.The result is better customer experience and business outcome.We can link the different phases of the maturity path to this high level architecture. The first phase would be linked more to the reporting and analytics engines, while the second phase focuses on the actions and the third on the automated and real time loop which allows the operator to be proactive and efficient.Each of the bubbles (mapped to maturity phases) emphasizes our USP for that phase.
- #14 This third customer example is from one a little further along the maturity path, in the Competitive Differentiation phase.A Croatian mobile operator, Vipnet, had a growing number of service platforms to serve its expanding mobile subscriber base. This made service monitoring more difficult, compromising the ability of customer care to resolve complaints quickly. The operator lacked the ability to have full visibility of their customers across network and systems, which lead to high costs in customer care handling.Vipnet has been looking for a solution that helps resolve most customer problems on the first call, minimizing the need to escalate issues to more experienced and costly technical support teams and to improve end-user service quality while operational expenditure under control.Nokia Siemens Networks deployed its Customer Care Automation that features an easy graphical user interface (GUI) that demands no previous technical knowledge from Vipnet’s customer care agents. The software takes data in real time, including customer profile and traffic data, from multiple sources across multivendor networks and automatically detects any inconsistencies or problematic configurations. It displays results to customer care agents in simple terms and provides one-click resolutions, helping staff resolve customer issues instantly. This reduces the number of calls which need to be forwarded to teams of technical experts, reducing the overall time spent in complaint handling and improving customer experience. As a result, Vipnet can now spot problems earlier and get them resolved 10% faster. The proportion of calls solved without escalation has improved by 15%, reducing customer care costs and boosting efficiency. Greater insight into the causes of problems helps further to improve product development.
- #15 This third customer example is from one a little further along the maturity path, in the Competitive Differentiation phase.A Croatian mobile operator, Vipnet, had a growing number of service platforms to serve its expanding mobile subscriber base. This made service monitoring more difficult, compromising the ability of customer care to resolve complaints quickly. The operator lacked the ability to have full visibility of their customers across network and systems, which lead to high costs in customer care handling.Vipnet has been looking for a solution that helps resolve most customer problems on the first call, minimizing the need to escalate issues to more experienced and costly technical support teams and to improve end-user service quality while operational expenditure under control.Nokia Siemens Networks deployed its Customer Care Automation that features an easy graphical user interface (GUI) that demands no previous technical knowledge from Vipnet’s customer care agents. The software takes data in real time, including customer profile and traffic data, from multiple sources across multivendor networks and automatically detects any inconsistencies or problematic configurations. It displays results to customer care agents in simple terms and provides one-click resolutions, helping staff resolve customer issues instantly. This reduces the number of calls which need to be forwarded to teams of technical experts, reducing the overall time spent in complaint handling and improving customer experience. As a result, Vipnet can now spot problems earlier and get them resolved 10% faster. The proportion of calls solved without escalation has improved by 15%, reducing customer care costs and boosting efficiency. Greater insight into the causes of problems helps further to improve product development.
- #16 This third customer example is from one a little further along the maturity path, in the Competitive Differentiation phase.A Croatian mobile operator, Vipnet, had a growing number of service platforms to serve its expanding mobile subscriber base. This made service monitoring more difficult, compromising the ability of customer care to resolve complaints quickly. The operator lacked the ability to have full visibility of their customers across network and systems, which lead to high costs in customer care handling.Vipnet has been looking for a solution that helps resolve most customer problems on the first call, minimizing the need to escalate issues to more experienced and costly technical support teams and to improve end-user service quality while operational expenditure under control.Nokia Siemens Networks deployed its Customer Care Automation that features an easy graphical user interface (GUI) that demands no previous technical knowledge from Vipnet’s customer care agents. The software takes data in real time, including customer profile and traffic data, from multiple sources across multivendor networks and automatically detects any inconsistencies or problematic configurations. It displays results to customer care agents in simple terms and provides one-click resolutions, helping staff resolve customer issues instantly. This reduces the number of calls which need to be forwarded to teams of technical experts, reducing the overall time spent in complaint handling and improving customer experience. As a result, Vipnet can now spot problems earlier and get them resolved 10% faster. The proportion of calls solved without escalation has improved by 15%, reducing customer care costs and boosting efficiency. Greater insight into the causes of problems helps further to improve product development.
- #17 This third customer example is from one a little further along the maturity path, in the Competitive Differentiation phase.A Croatian mobile operator, Vipnet, had a growing number of service platforms to serve its expanding mobile subscriber base. This made service monitoring more difficult, compromising the ability of customer care to resolve complaints quickly. The operator lacked the ability to have full visibility of their customers across network and systems, which lead to high costs in customer care handling.Vipnet has been looking for a solution that helps resolve most customer problems on the first call, minimizing the need to escalate issues to more experienced and costly technical support teams and to improve end-user service quality while operational expenditure under control.Nokia Siemens Networks deployed its Customer Care Automation that features an easy graphical user interface (GUI) that demands no previous technical knowledge from Vipnet’s customer care agents. The software takes data in real time, including customer profile and traffic data, from multiple sources across multivendor networks and automatically detects any inconsistencies or problematic configurations. It displays results to customer care agents in simple terms and provides one-click resolutions, helping staff resolve customer issues instantly. This reduces the number of calls which need to be forwarded to teams of technical experts, reducing the overall time spent in complaint handling and improving customer experience. As a result, Vipnet can now spot problems earlier and get them resolved 10% faster. The proportion of calls solved without escalation has improved by 15%, reducing customer care costs and boosting efficiency. Greater insight into the causes of problems helps further to improve product development.
- #18 Moving on to look at a case from the most mature CEM maturity phase. This one is from an emerging Asian market. The operator was faced with falling monthly ARPU and customer churn was on the rise, even though the network KPIs were showing improvement. The operator decided to take proactive actions to improve their customers’ experience, by automating the following use cases:They identify subscribers unable to browse due to wrong device settings. Proactively and automatically they provision and correct device settings. Only this use case translates into an impressive 68 M$ gain per year from revenue and efficiency improvement. This use case, already operational, fits to the profit optimization phase.In addition to this use case they also focus on the following (which fit more to the competitive differentiation phase, as they are not fully automated at the moment):2. They identify devices with negative impact on service performance, and proactively optimize the terminal market mix.3. They identify heavy users in 2G with 3G capable phones. With this insight, the operator’s marketing department is able to take action and offer a 3G up-sell to those customers who are using over 200MB per day with 2G, with impressive business results. They increased their data ARPU 350% - threefold. How is that for actionable insight!
- #19 Moving on to look at a case from the most mature CEM maturity phase. This one is from an emerging Asian market. The operator was faced with falling monthly ARPU and customer churn was on the rise, even though the network KPIs were showing improvement. The operator decided to take proactive actions to improve their customers’ experience, by automating the following use cases:They identify subscribers unable to browse due to wrong device settings. Proactively and automatically they provision and correct device settings. Only this use case translates into an impressive 68 M$ gain per year from revenue and efficiency improvement. This use case, already operational, fits to the profit optimization phase.In addition to this use case they also focus on the following (which fit more to the competitive differentiation phase, as they are not fully automated at the moment):2. They identify devices with negative impact on service performance, and proactively optimize the terminal market mix.3. They identify heavy users in 2G with 3G capable phones. With this insight, the operator’s marketing department is able to take action and offer a 3G up-sell to those customers who are using over 200MB per day with 2G, with impressive business results. They increased their data ARPU 350% - threefold. How is that for actionable insight!
- #20 Moving on to look at a case from the most mature CEM maturity phase. This one is from an emerging Asian market. The operator was faced with falling monthly ARPU and customer churn was on the rise, even though the network KPIs were showing improvement. The operator decided to take proactive actions to improve their customers’ experience, by automating the following use cases:They identify subscribers unable to browse due to wrong device settings. Proactively and automatically they provision and correct device settings. Only this use case translates into an impressive 68 M$ gain per year from revenue and efficiency improvement. This use case, already operational, fits to the profit optimization phase.In addition to this use case they also focus on the following (which fit more to the competitive differentiation phase, as they are not fully automated at the moment):2. They identify devices with negative impact on service performance, and proactively optimize the terminal market mix.3. They identify heavy users in 2G with 3G capable phones. With this insight, the operator’s marketing department is able to take action and offer a 3G up-sell to those customers who are using over 200MB per day with 2G, with impressive business results. They increased their data ARPU 350% - threefold. How is that for actionable insight!
- #21 Moving on to look at a case from the most mature CEM maturity phase. This one is from an emerging Asian market. The operator was faced with falling monthly ARPU and customer churn was on the rise, even though the network KPIs were showing improvement. The operator decided to take proactive actions to improve their customers’ experience, by automating the following use cases:They identify subscribers unable to browse due to wrong device settings. Proactively and automatically they provision and correct device settings. Only this use case translates into an impressive 68 M$ gain per year from revenue and efficiency improvement. This use case, already operational, fits to the profit optimization phase.In addition to this use case they also focus on the following (which fit more to the competitive differentiation phase, as they are not fully automated at the moment):2. They identify devices with negative impact on service performance, and proactively optimize the terminal market mix.3. They identify heavy users in 2G with 3G capable phones. With this insight, the operator’s marketing department is able to take action and offer a 3G up-sell to those customers who are using over 200MB per day with 2G, with impressive business results. They increased their data ARPU 350% - threefold. How is that for actionable insight!
- #27 Nokia Siemens Networks is one of the world’s leading CEM vendors with a wide offering that brings together pre-integrated software and related professional services across thenetwork, IT and the entire customer lifecycle. No one else provides deeper insight into the factors affecting customer experience and the targeted actions neededto improve it.Here are some numbers supporting our #1 position on the CEM market:Half of the world’s connected population runs on NSN CEM software (SDM: 2.9 billionsubscribers)800+ NetActinstallations / or 400+ customers, on average 2 installations per customer. In practise small customers with 1 installation and big ones with several NetActs. 148 Traffica customers50+ off-the shelf OSS integrations for different vendors and technologies150 SDM customers60+ Performance Manager customers; T-Mobile US handles 70+ billioncounterseveryday#1 vendor for subscriber data management and OSS/BSS. 250+ end user service optimization projects1200+ network management solutions installed at operators1,1 million network elements managed by Managed Services 700 millionsubscribersunderManaged Services