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      Forbes.com

      Big Data for Customer Loyalty? Don't Forget the Humans

      Big Data for Customer Loyalty? Don't Forget the Humans

      Algorithms can suggest remedies, but only humans can fix or improve the underlying processes and policies that make up the customer’s experience.

      글 Chris Brahm, Aaron Cheris and Lori Sherer

      • 읽기 소요시간

      Article

      Big Data for Customer Loyalty? Don't Forget the Humans
      en

      This article originally appeared on Forbes.com.

      Big Data analytics tantalize with the promise of nearly automated customer experience programs. Just tune the latest analytics software to your customer interactions and to social media sites, the pitch goes, and you can track and analyze how customers behave, as well as what they think about their experience with your company’s product or service.

      In reality, it’s not that simple. The human dialogue between customers and employees still matters during many of the episodes that customers experience with a company. Sure, algorithms can instantly suggest remedies after a poor interaction or reinforce the company’s brand after a great one. For example, one of us recently flew business class on Virgin America for the first time in almost a year. The plane was delayed on the tarmac for a half hour. As soon as the flight landed, we received an email from Virgin apologizing for the delay and offering a $50 voucher toward our next Virgin flight.

      But only humans can fix or improve the underlying processes and policies that make up the customer’s experience, whether digital or physical. Only humans can tease out the nuances of, and empathetically respond to, a customer’s concerns.

      Advanced practitioners of the Net Promoter System, for instance, loop real-time customer experience data and fresh customer feedback to employee teams who can translate the feedback into action by identifying and launching process improvements that have a positive and material effect on customers’ experiences with the company. Teams close the loop by calling back customers who had a bad experience in order to help deal with their concerns. They also speak with some customers who had a good experience to learn more about what made them feel so positive. Talking directly to customers allows the team to understand what real individuals want, rather than speculating or thinking in terms of the average customer. Big Data does not replace this ability to dig into the underlying causes of what individuals perceive, but it can amplify the value by applying the lessons across a broad base of customers.

      Human dialogue with customers is central to other endeavors as well, including new product design, prototype testing or sales of complex solutions. And digital technologies can allow employees to have much higher-quality and often lower-cost interactions with customers in those areas. At many web and mobile software companies, for instance, engineers interact with a small panel of customers via online tools such as those offered by usertesting.com. Seeing and hearing how customers interact with a product in real time shows engineers what they need to do better or differently.

      Big Data then can reinforce and extend some of the fundamental principles around earning customer advocacy:

      • Get the basics of the experience right. Wine.com, a leading online wine retailer, has invested in recommendation algorithms and a convenient digital experience for selection and shipping, but it also encourages customers to chat with wine sommeliers. These experts help customers learn and explore a broader selection, which has increased customers’ loyalty and lifetime value to the firm.
      • More data without action moves a company backward. The data will only be useful if you tie it into customer feedback loops that lead directly to improvements in the relevant experience. Think of software applications that ask millions of users to report crashes yet never close the loop with those customers or fix the application. The software companies are swimming in experience data but do not use the data to make the relevant improvements.
      • Data itself does not create a customer-centered culture. Many companies have intensely instrumented their experience without truly incorporating the customer’s perspective. The enterprise software industry has an average Net Promoter Score of negative 3 from its customers and even lower scores among end users. The ethos of providing a great end-user experience has not permeated that industry despite the reams of data it collects.

      Leading companies are using Big Data analytics to scale up their abilities to serve, tailor and enhance the experience for their customers. They still rely on humans for creativity, making trade-offs and engaging with customers where it matters—that is, all the areas where human judgment and empathy come into play.

      Chris Brahm is a partner with Bain & Company’s Digital and Advanced Analytics practices. Aaron Cheris is a partner with the Customer Strategy & Marketing practice, and he leads the firm’s Retail practice in the Americas. Lori Sherer is a leader in the firm’s Advance Analytics and Digital practices.

      저자
      • Headshot of Chris Brahm
        Chris Brahm
        Alumni, San Francisco
      • Headshot of Aaron Cheris
        Aaron Cheris
        파트너, San Francisco
      • Headshot of Lori Sherer
        Lori Sherer
        어드바이저 파트너, San Francisco
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      고객 전략 및 마케팅
      Avoiding the Pitfalls of Personalized Marketing and Sales

      A number of deliberate processes can raise the odds of creating an effective segment-of-one approach.

      자세히 보기
      어드밴스드 애널리틱스
      What Big Data Means for Customer Loyalty

      Only humans can fix broken policies or processes, but analytical tools can amplify their reach.

      자세히 보기
      어드밴스드 애널리틱스
      Three Promises and Perils of Big Data

      Advanced customer analytics can be a powerful business tool, but companies need to avoid common pitfalls before investing.

      자세히 보기
      어드밴스드 애널리틱스
      AI Is Transforming Productivity, but Sales Remains a New Frontier

      Potential applications of generative and agentic AI could free up more selling time and boost conversion rates.

      자세히 보기
      어드밴스드 애널리틱스
      Agentic AI Commerce Hinges on Consumer Trust

      Security, privacy, and institutional trust are the battlegrounds for AI-led payments.

      자세히 보기
      First published in 8월 2016
      태그
      • 고객 전략 및 마케팅
      • 어드밴스드 애널리틱스
      • Digital

      프로젝트 사례

      어드밴스드 애널리틱스 A New Demand Forecasting Approach Signals a Bottom-Line Boost

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