As payments providers around the globe cope with increasing pressure on revenues and margins, customer service is increasingly becoming an important asset for driving top- and bottom-line performance, and improving the customer experience. While most banks, card companies, and other payments providers have implemented various degrees of customer service transformation by using advanced analytics, the discipline has yet to be fully leveraged in this regard. To realize the full potential of today’s analytical capabilities, financial institutions will need to possess, acquire, or develop the relevant capabilities and use them to customize and enhance a wide range of customer interactions. Show
Payments providers that adopt advanced analytics to develop broad integrated approaches are seeing significant improvement: customer satisfaction scores rose 5 to 10 percent and operating costs declined 15 to 20 percent when they used analytics to eliminate cross-channel leakage and migrate more customer interactions into self-serve channels. Analytics also enabled these firms to improve customer retention and revenues by 10 percent or more, by enhancing the customer journey and improving cross-selling. The future of customer serviceCustomer service is shifting dramatically, from phone and branch-centric models to an omnichannel interaction dynamic in which customers move seamlessly among service channels, including mobile, phone, chat, and online. A McKinsey survey in 2015 showed digital channels accounted for 30 percent of customer interactions. We expect this share will approach 50 percent by 2020. And of this, 26 percent will be exclusively digital with no branch interaction. Payments customers expect high-quality service across channels, similar to what they enjoy at other financial institutions and leading service providers, like Amazon and Zappos. To deliver this level of service, payments firms need to optimize customer and prospect telecommunications and deliver seamless omnichannel interactions. Building an omnichannel customer service modelTraditionally, financial institutions have tried to optimize customer service within channel silos, including call centers, online, and mobile. The key to delivering a high-quality omnichannel experience is adopting a broad customer journey approach that integrates customer interactions across digital and traditional channels. Several institutions have already embarked on such a model. A global life insurer, for example, recently developed a five-year plan to migrate nearly half of its customer journeys into self-serve channels. However, too often such changes are viewed as one-time efforts rather than as a large-scale transformation. Designing a comprehensive, ongoing program is key to sustaining omnichannel service improvements. Investing in the talent to transformA key part of transforming the customer experience is migrating basic transactions to self-service channels, and complex transactions to agent-assisted channels. While most organizations invest in ongoing agent training and capability building, transforming the customer experience demands a more substantial investment in talent. It requires investing in technology that enables customer service professionals to have more effective interactions with customers. For example:
To provide more personalized customer service, financial institutions must rethink how they interact with customers and prospects. Analytics can personalize customer experience by, for example, identifying the next-best action or product offering. (See “Using data to unlock the potential of an SME and mid-corporate franchise.”) Investments in technology are, of course, critical to transforming the customer experience. Two investment types in particular are key: developing the agility to rapidly build, pilot, and launch a broad transformation; and robotics or artificial intelligence (AI) to reduce manual workloads, improve cycle times, and minimize back-office errors. McKinsey research shows that 65 percent of back-office tasks at contact centers, and 30 to 50 percent of front-line calls, can now be automated. Six hallmarks of analytics successFinancial institutions that are successfully using advanced analytics to enhance the customer experience share six common hallmarks (Exhibit 1). Exhibit 1
We strive to provide individuals with disabilities equal access to our website. If you would like information about this content we will be happy to work with you. Please email us at: 1. Migrating customers to digital channelsGiven customers’ preference for omnichannel service, there are two important questions financial institutions must address: First, how do they create seamless transactions for digital natives, who prefer digital-only service? Second, in serving less digitally inclined customers, how can financial institutions use tools like journey analytics to prevent the use of multiple channels for the same query? The main challenge for customer service organizations is to identify the most appropriate transactions for migration and ensuring they are completed satisfactorily in digital channels whenever possible. Payments leaders in digital migration are achieving 20 to 30 percent reductions in call volume and successfully enhancing the customer experience. Some industry leaders are also developing a 360-degree, multitouch, multichannel view of customer interactions using journey analytics; but this requires robust integrated datasets that can capture customer interactions across channels. 2. Improving behavioral routing and IVR containmentFinancial institutions have been using interactive voice response (IVR) technology for several decades, but few have optimized these capabilities. Doing so requires more than investing in additional VR capabilities. Financial institutions can apply advanced analytics or AI-based technologies to improve behavioral routing and IVR containment:
3. Strengthen identity validation and personalize product offeringsThe layering of analytics on video and audio channels can improve identity validation and personalize the product offering. Examples include:
4. Optimize the workforce management modelMost financial institutions have established internal analytics centers staffed with experts working to capture workforce optimization opportunities. Yet, most workforce management practices are rooted in backward-looking general demand–supply matching, assuming some average service level for a day. However, customer research reveals that assumptions of averages fall short. There are three important challenges for each financial institution:
5. Automate to improve employee efficiency and engagementThus far, automation has not been systematically applied in the customer service environment. In customer care, AI can be used to automate services by supporting customers with virtual agents, and contact center agents through real-time interaction tools (e.g., automated knowledge management systems) and back-end automation (e.g., robotic process automation). Virtual agents can solve customer requests by using natural language processing technology, and get smarter over time through machine learning. For example, programs like IPSoft’s Amelia can play the role of any customer service agent by rapidly absorbing call logs, recognizing emotional context, and interacting with customers, thereby saving costs and lifting both revenue and customer experience. With large tech players moving into the digital assistant arena, we expect things to evolve quickly in this area. 6. Optimize frontline performance through analytics in recruitingRecruiting processes for customer service organizations are seldom informed by what makes agents successful. Leading firms take an approach called people analytics methodology, which reverse engineers the process, starting with the best customer service agents and identifying common traits that makes them successful. They then apply these insights at the top of the recruiting funnel in selecting candidates. By applying people analytics in this way, financial institutions can improve talent management in customer experience as well as in the wider organization. Case example I: Improving digital channel experience and digital adoptionRecently, a North American bank used journey analytics to accelerate digital adoption across its customer base. Using analytics and design thinking to address digital adoption levers across customer journeys (rapid digitization, containment, signature moments, customer targeting), the bank achieved a gain of more than 20 percentage points in digital engagement. The initiative included the following elements:
Case example II: Enhanced contact managementA credit card company was struggling to migrate customers to its self-serve channels despite having invested in natural-language speech IVR. Consequently, it devised a three-pronged approach to accelerate migration, which focused on resolving (and containing) a higher percentage of calls within their IVR, and delivered a differentiated experience along the customer journey:
Through these efforts, the credit card provider identified 200 to 500 bps in potential improvement in the containment rate (Exhibit 2). The VR enhancements and post-VR agent initiatives also led to a 5 to 10 percent reduction in costs or incremental annualized savings. Exhibit 2
We strive to provide individuals with disabilities equal access to our website. If you would like information about this content we will be happy to work with you. Please email us at: Case example III: Demand forecastingThe call center head of a large UK-based bank turned to analytics to optimize agent utilization by automating demand forecasting, as part of a larger analytics-driven transformation at the institution. The approach incorporated the following elements:
The bank achieved a 20 to 40 percent error reduction in forecasting for a subset of population and are rolling it out across all FTEs. Starting the journey on analytics to customer serviceWhen introducing advanced analytics, a critical first step is clearly understanding the organization’s current position in terms of one of three horizons (Exhibit 3): Exhibit 3
We strive to provide individuals with disabilities equal access to our website. If you would like information about this content we will be happy to work with you. Please email us at: Those on Horizon 1 generally have low levels of awareness regarding recent developments in advanced analytics for customer service. These organizations need to begin their transformation by building a business case, educating their leadership, and obtaining organizational buy-in. Once these initiatives are underway, quick, tangible wins should be pursued to reinforce the organization’s commitment to a full transformation. Additionally, another challenge faced by these organizations is lack of in-house knowledge on relevant frameworks and solutions, to diagnose and prioritize initiatives. Enterprises at Horizon 2 have a better understanding of recent advances in the field, and have started to experiment with or adopt them. However, they have done so largely on an ad hoc, unstructured basis. Unfortunately, informal approaches are likely to leave significant value on the table. The key challenge for Horizon 2 organizations is to identify the most efficient path for delivering the desired results. This might be accomplished, for instance, by shaping their perspectives through a sharing of external best practices, and then setting challenging timelines. Horizon 3 firms are well ahead of the curve, applying next-generation analytics solutions to transform the customer service model. At this stage, the key challenge is finding ways to advance to even higher levels, and to continue to invest in next-generation solutions. The use of new analytical tools and capabilities are transforming customer service in financial services. The following questions can help firms shape their strategy discussions:
How does verbal communication help customer service?Your communication skills determine your chances of a sale — from your opening pitch to your closing statements. Developing your questioning, vocal and conversational skills will help you build on a strong first impression by gaining trust and establishing credibility.
Is the foundation of effective customer service?There are five fundamental factors to great customer service that will help you make a positive impact on the experience of your customers. These factors are Reliability, Assurance, Tangibles, Empathy, and Responsiveness (RATER).
Why is nonverbal communication important in customer service?It plays a vital role especially in the workplace and particularly when the job involves dealing with external customers. When a customer service agent is interacting with a customer these nonverbal communication signals can tell the customer whether they are actually being listened to with the aim of understanding.
Which of the following is an assertive and appropriate way to deal with customers or coworkers when you disagree quizlet?Which of the following is an assertive and appropriate way to deal with customers or coworkers when you disagree? Agree to disagree and negotiate a solution that both parties can live with.
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