Matt Dixon

Matt Dixon is Chief Product & Research Officer of the Austin-based AI and machine learning venture, Tethr. In this capacity, he has responsibility for product strategy, product management, and product marketing. Prior to joining Tethr, Matt was a Senior Partner and Global Head of Sales Force Effectiveness Solutions at Korn Ferry Hay Group and, before that, held numerous global leadership roles in research, product development and management for CEB, now Gartner.

A seasoned business researcher, Matt has been involved in dozens of original quantitative and qualitative research studies on topics ranging from customer experience strategy to customer service and sales effectiveness. His first book, The Challenger Sale: Taking Control of the Customer Conversation (Pen...

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The Challenger Sale: Taking Control of the Customer Conversation

What's the secret to sales success? If you're like most business leaders, you'd say it's fundamentally about relationships--and you'd be wrong. The best salespeople don't just build relationships with customers. They challenge them.

The need to understand what top-performing reps are doing that their average performing colleagues are not, drove Matthew Dixon and his colleagues to investigate the skills, behaviors, knowledge, and attitudes that matter most for high performance. And what they discovered may be the biggest shock to conventional sales wisdom in decades.

Based on an exhaustive study of thousands of sales reps across multiple industries and geographies, The Challenger Sale argues that classic relationship building is a losing approach, especially when it comes to selling complex, large-scale business-to-business solutions. The authors' study found that every sales rep in the world falls into one of five distinct profiles, and while all of these types of reps can deliver average sales performance, only one-the Challenger- delivers consistently high performance.
Instead of bludgeoning customers with endless facts and features about their company and products, Challengers approach customers with unique insights about how they can save or make money. They tailor their sales message to the customer's specific needs and objectives. Rather than acquiescing to the customer's every demand or objection, they are assertive, pushing back when necessary and taking control of the sale.

The things that make Challengers unique are replicable and teachable to the average sales rep. Once you understand how to identify the Challengers in your organization, you can model their approach and embed it throughout your sales force. The authors explain how almost any average-performing rep, once equipped with the right tools, can successfully reframe customers' expectations and deliver a distinctive purchase experience that drives higher levels of customer loyalty and, ultimately, greater growth.

An acclaimed international bestseller, The Challenger Sale has been lauded as “the most important advance in selling for many years” (SPIN Selling author Neil Rackham) and “the beginning of a wave that will take over a lot of selling organizations in the next decade.” (Business Insider). The Challenger Sale has sold nearly a million copies worldwide, has been translated into 8 foreign languages and has appeared on the Amazon and Wall Street Journal bestseller lists on multiple occasions since its release.

The Effortless Experience: Conquering the New Battleground for Customer Loyalty

Everyone knows that the best way to create customer loyalty is with service so good, so over the top, that it surprises and delights. But what if everyone is wrong?

In their acclaimed international bestseller The Challenger Sale, Matthew Dixon, and his colleagues busted many longstanding myths about sales. In The Effortless Experience, Dixon and his team turn their research and analysis to a new, vital business subject—customer loyalty—and once again turn the conventional wisdom on its head, producing one of the most influential books ever to be published in the customer experience and customer service space.

The idea that companies must delight customers by exceeding service expectations is so entrenched that managers rarely even question it. They devote untold time, energy, and resources to trying to dazzle people and inspire their undying loyalty. Yet the careful research conducted by Dixon and his team over more than five years and tens of thousands of respondents proves that the “dazzle factor” is wildly overrated—it simply doesn’t predict repeat sales, share of wallet, or positive word-of-mouth. The reality:  Loyalty is driven by how well a company delivers on its basic promises and solves day-to-day problems, not on how spectacular its service experience might be. Most customers don’t want to be “wowed”; they want an effortless experience. And they are far more likely to punish you for bad service than to reward you for good service.

The Effortless Experience takes its audience on a fascinating journey deep inside the customer experience to reveal what really makes customers loyal—and disloyal. In this presentation, Dixon lays out the four key pillars of low-effort customer experience, along the way delivering robust data, shocking insights and profiles of companies that are already using the principles revealed by the research, with great results.
One of the most influential customer experience and customer service books ever written, The Effortless Experience has been described as "a business detective story in which cherished truths are systematically investigated and frequently debunked" (Dan Heath, co-author of Switch and Made to Stick).
The rewards are there for the taking, and the pathway to achieving them is now more clearly marked than ever.

The Challenger Customer: Selling to the Hidden Influencer Who Can Multiply Your Results

The bestselling authors of The Challenger Sale overturned decades of conventional wisdom with a bold new approach to sales. Now their latest research reveals something even more surprising: Being a Challenger seller isn’t enough. Your success or failure also depends on who you challenge.

Picture your ideal customer: friendly, eager to meet, ready to coach you through the sale and champion your products and services across the organization. It turns out that’s the last person you need.

Most marketing and sales teams go after low-hanging fruit: buyers who are eager and have clearly articulated needs. That’s simply human nature; it’s much easier to build a relationship with someone who always makes time for you, engages with your content, and listens attentively. But according to the latest research from Matthew Dixon and his coauthors—based on data from thousands of B2B marketers, sellers, and buyers around the world—the highest-performing teams focus their time on potential customers who are far more skeptical, far less interested in meeting, and ultimately agnostic as to who wins the deal. How could this be?

The authors of The Challenger Customer reveal that high-performing B2B teams grasp something that their average-performing peers don’t: Now that big, complex deals increasingly require consensus among a wide range of players across the organization, the limiting factor is rarely the salesperson’s inability to get an individual stakeholder to agree to a solution. More often it’s that the stakeholders inside the company can’t even agree with one another about what the problem is.

It turns out only a very specific type of customer stakeholder has the credibility, persuasive skill, and will to effectively challenge his or her colleagues to pursue anything more ambitious than the status quo. These customers get deals to the finish line far more often than friendlier stakeholders who seem so receptive at first. In other words, Challenger sellers do best when they target Challenger customers.

The Challenger Customer unveils a research-based approach that will help sellers and managers to distinguish the "Talkers" from the "Mobilizers" in any customer organization. It also provides a blueprint for finding them, engaging them with disruptive insight, and equipping them to effectively challenge their own organization.


  • The Challenger Sale: Taking Control of the Customer Conversation
  • The Effortless Experience: Conquering the New Battleground for Customer Loyalty
  • The Challenger Customer: Selling to the Hidden Influencer Who Can Multiply Your Results


  • Reinventing Customer Service
    Reinventing Customer Service
    Dec 27, 2018
    Matt Dixon, Harvard Business Review...
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    Reinventing Customer Service
    Dec 27, 2018

    Visit any big company, and few departments will be as instantly recognizable as customer service. The call center usually resembles a factory floor, with row after row of reps, headsets on, sticking to the script and rushing from call to call as they try to minimize “handle time.” Supervisors walk the floor to deal with escalated calls and, every now and then, take individual reps to a back room to review their performance. While some organizations have invested in improving reps’ lot, change has been slow to arrive in the practice of customer service. It’s no wonder that turnover rates for customer service workers are among the highest in the business world—27% annually, on average, according to Mercer. The reasons departing employees cite most often include a lack of challenging work, inadequate recognition, limited career paths, and too little flexibility. For customers, the experience is hardly better. They are forced to navigate computerized call trees and, should they get a live person, they’re often treated robotically and handed from one agent or department to another if their issue is outside a rep’s narrow repertoire.

    But walk into a T-Mobile contact center. The service department looks more like the sort of knowledge-work environment you’d expect to see in other parts of the company. Reps sit together in shared spaces called pods, collaborate openly, and are trained and encouraged to solve customer issues as they see fit. Most remarkably, these teams manage a specific pool of customer accounts, just as a small business would. Unshackled from legacy metrics like handle time, they instead think about the best way to solve each caller’s problem and, ultimately, how best to improve customer retention, share of wallet, and loyalty. Customers know how to reach their dedicated teams, and they never have to go through a call tree. Once connected, they find reps who actually know them and can reliably help.

    The T-Mobile model is paying huge dividends for the company: In the three years since launch, T-Mobile’s overall cost to serve is down 13%, its Net Promoter Score (a measure of customer loyalty) is up by more than half, and its customer churn rate has dipped to an all-time low. Employees are happier too; attrition and absenteeism have plummeted.

    The Change Imperative
    Over the past decade, T-Mobile’s leadership team recognized that although the company’s investments in self-service had paid off well, they’d also created a challenge. The basic transactional calls that once dominated call queues—balance inquiries, address changes, new-service activation, and the like—had all but disappeared as customers turned to self-service options for addressing those matters. Now the queue was dominated by the complex and varied issues that customers couldn’t solve on their own—a shift that started to put real stress on the company’s reps. In response, the leadership team went to the drawing board and, in 2015, set to work reinventing the service organization from the ground up.

    The effort was led by Callie Field, the executive vice president of customer care. She and her colleagues wanted to improve reps’ ability to handle thorny problems and, in the process, further differentiate the company in a crowded marketplace. Field, who started at T-Mobile in 2004 as a mall-kiosk sales rep and rapidly rose through the ranks, faced an enormously challenging task. “But,” she explains, “my team and I had a good sense—just from our own experience as customers and employees—of the kind of service that makes you feel good about a company. We knew we had to create that. And we focused on identifying and eliminating the things that drive customers crazy. In the end, we had a simple goal: customer happiness. We figured happy customers would stay longer, spend more with us, and recommend us to others.”

    As Field’s team devised the new model, members identified four questions to ask in assessing the transformation over time: (1) Are our customers happier? (2) Are they staying with us longer? (3) Are we deepening our relationship with them? (4) Are we making their service experience low-effort? Because the model’s success hinged on T-Mobile’s ability to engage and mobilize its frontline employees, the same questions would be used to gauge their experience.

    Given its goals, Field’s team reasoned that a version of the account management model common in B2B settings—in which a dedicated sales and service team manages a pool of customers—could work well in B2C customer service. The question was how to implement such a model at scale across thousands of reps at dozens of locations serving 40 million customers around the clock. At the time, it appeared that such a system had been deployed only in B2B settings where call volumes are low and issues are resolved in hours or days. It had rarely, if ever, been attempted in a high-volume B2C support center like T-Mobile’s, which handles millions of calls each month and works to resolve issues in minutes or even seconds.

    To tackle this, T-Mobile devised the Team of Experts model, or TEX. This involves cross-functional groups of 47 people who serve a named set of customer accounts in a specific market. The team members are colocated, but they may be hundreds of miles away from their clients. For instance, a team in Chattanooga is responsible for 120,000 customers in Detroit, and a team in Charleston serves a similar number of customers in Philadelphia.

    In addition to the reps themselves, each team has a leader, four dedicated coaches, eight technology specialists who can handle more-complex hardware and software issues, a customer resolution expert (who spots trends and helps develop solutions to persistent issues), and a resource manager responsible for workforce scheduling and management.

    If call volume is unusually heavy, if a team is shorthanded, or if T-Mobile’s centers are closed, backup comes from dedicated outsourced teams that likewise follow the TEX model (or are in the process of adopting it; T-Mobile expects full adoption by early 2019). All teams operate during business hours aligned to the time zones of the communities they support, and customers can reach an account rep directly through a variety of channels—T-Mobile’s messaging app, the customer portal on T-Mobile’s website, and the phone. And although customers may not connect with the same rep each time, they will always be served by someone from their dedicated team.

    That person, moreover, will almost assuredly solve the problem. Each rep is a generalist who can handle everything from billing, sales, and line activation to standard technical-support inquiries. Transfers are rare; the only time a rep will hand off a customer is when an outside vendor needs to address a product issue or, on occasion, when an unusually complex problem requires the help of the team’s tech specialists. Even then, the rep will stay on the call to learn how to resolve similar matters in the future.

    To ensure that all team members work well together, T-Mobile built collaboration into the model. Teams hold stand-up meetings three times a week to share best practices, lessons learned, and ideas for handling recurring customer concerns. Members also collaborate in real time using an instant-messaging platform. This allows them to alert colleagues to emerging issues in the communities they serve (for instance, weather events and service outages) and to solicit advice during the course of a customer conversation. To encourage these exchanges, the pods include a central table and whiteboard for huddles and coaching sessions.

    Teamwork and Creative Solutions
    To encourage collaboration and innovation, the TEX model uses a balanced scorecard that weights both individual and team performance. This is a dramatic departure from typical schemes for evaluating customer service agents, which measure only individual performance, encouraging reps to hoard knowledge and look out for themselves. With the emphasis on team effectiveness, tenured reps have more incentive to share their best practices. As one of T-Mobile’s senior account experts explains, “In the old model, it was sink or swim on your own. Now we all spend time helping the less-tenured team members and the new folks coming out of training, to make sure they’re successful. At the end of the day, we succeed or fail as a team.”

    TEX teams are expected to manage their own profit and loss statements. Field says, “Our team leads used to look at things like handle time and schedule adherence. Now they look at their P&L—are they keeping and growing customer business? Are they reducing calls per account and cost to serve? They’re like mini-CEOs running their own businesses.” Team leaders now engage in quarterly business reviews with senior managers, much as a business unit general manager reviews financial and operating performance with the CEO. As a result, coaching conversations with reps often focus on the business impact of individual decisions and how a decision for a given customer will affect that customer’s loyalty and the team’s financial performance. Such coaching enhances reps’ skill sets; one team leader said, “I have no doubt that any of my team members could leave tomorrow and open their own business—and be really successful at it.”

    With group performance top of mind, account teams are encouraged to come up with innovative solutions to persistent service issues. A team serving Salt Lake City, for instance, noticed unusually high churn among younger customers. A deeper dive into the data revealed that a primary cause was the defection of young Mormons about to head out on their two-year missions, during which time they are prohibited from having a phone. The team determined that although phones are not allowed, missionaries can have tablets. So when customers called to deactivate, reps offered them a tablet for the duration of their mission—a solution that helped the customers retain their phone numbers and accounts for their return. This clever solution generated one of the highest improvements in profitability for that particular customer base—and had a meaningful impact on team members’ bonuses.

    Similarly, when the company rolled out its T-Mobile ONE Military plan, which provides members of the armed forces with a 50% discount on family lines, TEX members serving communities with heavy military populations thought proactively about managing the effects of the discounted plan on their business objectives. The question was how to balance the obvious customer savings benefit with the potential revenue loss impacting their business goals. The solution: helping customers understand that the savings could be put toward an additional phone line that would keep family members connected. One team migrated 30% of its military customers to the new plan and increased average new-line sales from four per rep per hour to seven—while simultaneously increasing the Net Promoter Score among those customers by five points.

    Making It Local
    No matter how far TEX teams are from the communities they support, members are intimately familiar with the places their customers live. Teams decorate their workspaces to reflect the markets they serve. The Chattanooga-based team serving Detroit, for example, has decked out its work area with “Motor City” signage and memorabilia. And the Salem, Oregon, pod that serves San Francisco built a Golden Gate Bridge out of Legos. Says a senior rep in Idaho whose team serves San Diego, “We’re constantly talking about what’s happening there. I’ve never been to San Diego, but I know what’s going on in the local news, where the best place is for fish tacos, and what the surf report looks like for the next few days.”

    This local connection helps the TEX team members manage community-level situations. For instance, the San Diego team was recently deluged with calls about a widespread outage caused by a local brush fire. “In the old world,” one rep said, “I wouldn’t have had any idea that this was happening—or that it was happening to more than one customer—so I’d have said, ‘I’m really sorry about the inconvenience. Let me submit a ticket to engineering.’” But the new model enabled the rep to deliver a tailored response: “Yes, we’re aware that a brush fire outside the city is affecting your service, and we’re working on the issue. I’ve been in touch with the engineers on the ground, and they’re working to restore service as we speak. They’re telling me it should be up and running within 24 hours.”

    One leader on a team serving Seattle customers said that local knowledge and connections have enabled his group to deliver the kind of service you’d expect from a mom-and-pop store. “If a customer orders a new device and wants to pick it up in the store, we need to make that as easy as possible. Because I know all the store managers in my area, I can call the local manager and ask that he have the phone ready to go. It makes a big impression when the store manager meets a customer as she walks in and says, ‘Hey there—Nick from your Team of Experts called me to say you were coming by. Here’s your new phone; you’re all set.’”

    The Payoff
    The new model’s business results speak for themselves. In the first quarter of 2018, the company recorded the lowest cost to serve in its history (a 13% decline since 2016). Liberated from legacy metrics like handle time, reps now take a little longer on each call to make sure they’ve not only solved the customer’s immediate issue but also anticipated and addressed in advance issues the customer might call back about. The result: a 21% reduction in calls per account, which more than offsets the longer length of calls.

    And because customers are now receiving better service, reps no longer have to issue credits for previous missteps. Such “apology credits” are down 37% across the board. The results are also seen in record levels of customer retention (an all-time low in customer churn in Q1 2018) and increased customer loyalty. Reflecting customers’ satisfaction, T-Mobile has been ranked the number one wireless company for customer service by Nielsen for the past 24 months and has received—twice in a row—the highest score ever awarded by JD Power in its rankings of wireless-provider customer-service quality.

    The company has also seen positive effects among employees, including record highs in rep engagement and record lows in turnover (from 42% annually before the rollout to 22% today). Absenteeism—typically a trouble spot for most contact centers—has plummeted too: Because TEX teams can manage their own schedules and tailor shifts to members’ needs, absenteeism has dropped 24%. The four outsourcing partners who have adopted the TEX model have seen an even steeper decline in turnover: Historical frontline turnover levels in partners’ call centers had been more than 100% annually; today, average turnover is at 14%—below that of T-Mobile’s in-house customer-care centers.

    Getting Started
    T-Mobile executed this transformation with its existing talent—there was no wholesale revamping of the hiring profile and no mass exodus of frontline staffers who couldn’t cut it. Instead, the company found that most reps were up to the task and wanted to do well. What they needed was freedom from the old model that had been holding them back, coupled with the training to succeed in the new world. As Field sees it, “If all you ask people to do is bring down their handle time, they can do that. But if you empower them to do more—to think like a small-business owner who is focused on the customer’s happiness and the strategic management of their P&L—they can do that too. And they’ll do it really well if you give them the tools and get out of their way.”

    That said, a wholesale transformation from factory floor to knowledge-work environment hasn’t been without challenges. One lesson T-Mobile learned early on is that colocation is essential. Field explains, “We originally thought we could pull this off by setting up virtual teams and leveraging collaboration tools, but it turned out to be easier said than done. We didn’t get the level of collaboration we needed, and the teams failed to gel when they were spread all over the country. So we decided that the teams needed to sit together, which meant investing in a new physical layout for our contact centers.”

    Although the cost of redesigning the contact center floor wasn’t extraordinary (“We knocked down some cube walls,” Field said, “and bought everybody better headsets so they could roam”), the company’s investment in talent was significant. In addition to modestly increasing pay for reps in recognition of their expanded responsibilities, T-Mobile doubled down on training to help reps transition from a narrow focus on specialized lines of business—such as billing, collections, and tech support—into generalist roles. For new hires, the cost of more training (10 weeks instead of eight) was offset by reductions in ramp-up time. The company also gave managers more time to deliver coaching, which meant increasing the ratio of managers to reps. In the first year of the new model, T-Mobile promoted more than 2,100 employees to management positions, providing commensurate raises and management training. Although those investments were expensive, Field notes that the resulting reductions in cost to serve and the improvements in customer retention and wallet share have delivered an ROI that far surpassed original projections.

    However, while most reps embraced the training and gamely transitioned to the team-based model, not all did. As the incentive structure shifted from emphasizing individual performance to rewarding team performance, some reps who had shined as individual workers ended up being frustrated when their rankings dipped as a result of softer team performance. Some balked at the perceived unfairness of the new system, and a few left.

    A final word of caution from T-Mobile’s leaders: Before heading down this path, companies should consider their cultural readiness. One team leader explains, “We never believed in scripting our people and were always very focused on hiring people who really wanted to deliver great service. So we had the basics, from a cultural and talent standpoint, already in place. That’s probably not the case for many other companies.” Even for T-Mobile, the leader acknowledged, it took some time for reps to feel comfortable with the level of ownership they were offered: “In the beginning, we told them to make decisions on their own and do what they felt made sense for the customer, but we still had a lot of folks who would put the customer on hold and ask their supervisor for permission anyway.”

    The Bigger Story
    T-Mobile has established itself as the “Un-carrier”—a company not afraid to challenge standard industry practices that it sees as flawed and unfair to customers. It was the first to stop locking customers into two-year service contracts and the first to stop charging usurious fees for exceeding data limits. As CEO John Legere said in testimony before Congress in June 2018, “We set out to fix a stupid, broken, arrogant industry.” The TEX model of customer care is in keeping with that mission.

    But T-Mobile’s service transformation is part of a larger story of reinvention that’s been playing out in other corporate functions—at many companies—over the past few decades. HR leaders, for instance, once faced an existential threat from the automation of transactional processes such as payroll and benefits. Progressive HR executives transformed themselves and their departments into strategic partners to the board and the CEO by handing off transactional work to human resource management systems and outsourcing business processes, while simultaneously developing new capabilities such as strategic workforce planning, leadership development, employee engagement, and succession management.

    Customer service organizations that emphasize knowledge work haven’t abandoned their core function: handling and addressing customer issues. But companies that adopt models like T-Mobile’s TEX will be more competitive in an environment characterized by increasingly complex customer issues and high expectations. At the same time, they’ll discover new ways to deliver value to employees, customers, and business partners, deepening their relationships across the board.

  • Use AI to fix call center quality assurance, not just automate it
    Use AI to fix call center quality assurance, not just automate it
    Jun 14, 2018
    Matt Dixon...
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    Use AI to fix call center quality assurance, not just automate it
    Jun 14, 2018

    The problem with traditional call center QA

    Few processes are more broken in today’s customer service department than quality assurance, or QA for short. QA is the process whereby companies “audit” calls for how well a representative adheres to company-defined scripting and language during a customer interaction. Did the rep say the customer’s name three times? Did the rep thank the customer for her loyalty? Did the rep read the required disclosure statements after executing the transaction? Did the rep display empathy, friendliness and professionalism?

    The problems with call center quality assurance—as currently practiced by companies—are many. From the perspective of company leadership, QA’s biggest shortcoming is that it is a manual, people-driven process. And people are inherently inefficient and expensive. What this means in practice is that companies will end up listening to and auditing only a small percentage of customer calls—typically 1% of recorded calls will ever be audited by a company’s QA team. As a result, QA becomes a source of frustration for reps who feel that they aren’t being treated fairly and that the company is assessing their performance on too small a sample to be valid. So, it should come as no surprise that for every call center QA process in a large company, there is also an appeals process for reps to dispute spurious results and scoring that is perceived to be unfair.

    AI-enabled speech analytics as a solution

    For this reason, companies have latched onto new AI-based technologies (namely, machine learning-powered speech analytics) as an opportunity to automate QA—to stop having QA managers listen to a small percentage of calls and instead teach a machine to listen to all calls, without the cost and inherent bias of people. Understandably, service leaders’ eyes widen at the idea of automatically scoring all service interactions without any human involvement.

    As an AI AND MACHINE LEARNING PLATFORM company, Tethr is often asked to help companies automate their call center QA process. But, as attractive as it seems to use AI-based “listening” approaches to automate a manual process, our advice is that companies think twice before doing this. In our view, digital technologies are better deployed to fix call center QA, not just automate it. People are the problem in QA…but it’s less because of how QA is administered and more about how QA is designed.

    The far bigger issue with call center QA isn’t that it’s inefficient and expensive (which it is), but that it’s built off of assumptions, hunches and gut instincts. Companies ask QA to listen for things they think are important (e.g., saying the company’s name at the beginning of a call for brand association or saying the customer’s name multiple times to make the customer feel the interaction is personalized). But these assumptions, regardless of how well-intentioned, have rarely been tested with data. This is why most companies constantly update their QA scorecards—without a compass to show them where to go, they resort to guessing.

    New technologies today allow companies to combine the best of human intelligence with the best of artificial intelligence to deepen a company’s knowledge of what actually drives customer outcomes. Put differently, the promise of AI isn’t just about automation, it’s about understanding.

    Armed with machine learning and data science techniques, leading companies are seizing upon this opportunity to finally overhaul call center QA so that it delivers what it was originally intended for: higher quality customer interactions.

    Putting AI to use – real-world examples

    One large telecommunications provider, for example, had long used their call center QA team to assess whether their reps demonstrated appropriate acknowledgement when customers expressed frustration—i.e, “I’m sorry you’re having this problem” and “I know how frustrating this must be for you.” Using AI to understand how unstructured voice data impacted known outcomes (like CSAT, NPS and Customer Effort Score), they came to learn that this sort of acknowledgment—which the company had always assumed drove positive customer outcomes—actually made customers more frustrated, not less. The frustration level, in fact, was on par with what customers experience when they’re transferred to another department. Now, the company teaches its reps to resist the urge to acknowledge and apologize and instead get on to solving the problem at hand.

    A provider of home services that we work with used AI to figure out what objection-handling techniques lead to higher sales conversion rates. The company had long assumed that when customers balk about the price of their services, the best approach was to explain to the customer that the company offered some of the lowest rates in the business and, if push came to shove, to offer a small discount. But, when the company used machine learning to study this technique across thousands of sales calls, they found that this technique wasn’t remotely correlated with higher sales conversion. Instead, reiterating the company’s money-back guarantee ended up being much more highly correlated with conversion (and much cheaper to offer than a discount).

    This company also used AI to understand—at a very specific level—how their reps should demonstrate “advocacy” in customer interactions. While advocacy had been on the call center QA “checklist” for many years, they never really knew how best to demonstrate advocacy in different customer situations. A large-scale analysis using machine learning demonstrated that in sales interactions, reps are best served by using language that demonstrates control, confidence and authority (e.g., “Here’s what I recommend” or “This is the option I would pick”). In fact, the data analysis suggested that such approaches backfire in issue-resolution situations. In those sorts of calls, reps are far better off proposing an option but hinting that there are other options if the first one doesn’t pan out (e.g., “I’ve got some ideas for how to fix this…let’s try this first”).

    Finally, we worked with one large insurer to apply AI to their voice data in order to identify–among more than 250 categories of rep behaviors and interaction dynamics–which ones actually drive one of the key outcome metrics the company is focused on, Customer Effort Score. In the end, we identified 14 statistically significant drivers (ten behaviors that eroded CES and four that improved it). Most impactful among the behaviors that eroded CES was when reps used language that indicated they were “powerless to help” a customer to resolve a specific issue. The company is now focused on training and coaching their reps on how to avoid these phrases and instead use language that demonstrates advocacy and empowerment. And, importantly, their call center QA team now knows what critical behaviors and techniques to be listening for in calls.

    Fix first, then automate

    It is true that advances in AI, machine learning and natural language processing finally afford companies with the opportunity to automate call center QA, which represents a step-function change in efficiency for companies. But, the greater opportunity is to dramatically improve the effectiveness of QA by finally identifying the language techniques that actually drive quality. Armed with this insight, companies will then be well-positioned to automate their processes and finally capture the scale benefits of scientific and data-driven quality assurance.

    Our strong advice to service leaders is this—“fix first, then automate,” not the other way around.

  • The Omnichannel Experience (Part 2): What Matters to Customers...and What Doesn't
    The Omnichannel Experience (Part 2): What Matters to Customers...and What Doesn't
    Dec 08, 2016
    Matt Dixon...
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    The Omnichannel Experience (Part 2): What Matters to Customers...and What Doesn't
    Dec 08, 2016

    In my last post, we discussed the promise of omnichannel –integrating data streams and queues across all channels to ensure a seamless service experience and unified view of the customer. Omnichannel seems to hold a lot of promise, but it clearly comes at a (steep) cost. At the end of that first piece, I left you with the question, “is it worth the time and money to do it?”

    So, here I want to share some results of CEB’s recent research on the omnichannel benefits customers care about – and those they’re less likely to reward you for.

    Most of our members tell us that their budgets are tight and they're not in the position to spend the millions (in some cases, tens of millions) necessary to implement a comprehensive omnichannel solution. Instead, what they really want to know is which specific elements of omnichannel will deliver the highest returns for their business. Put differently, what will generate the most customer value while also helping to reduce operating expenses? To figure this out, we scoured all of the major omnichannel vendors’ websites to create a list of the claimed features and benefits that their solutions deliver. We boiled this list down to 30 categories – everything from channel integration (the ability to deliver a seamless experience to customers as they switch from one channel to the next) to customer knowledge and recognition (the ability to deliver a 360-degree view of the customer).

    We then surveyed more than 2,000 customers to understand which of these attributes deliver the lowest-effort experience. It's important to note that we didn't just ask customers their preference on features and benefits. Instead, we tested the impact these benefits had on actual experiences customers had with companies. In the end, we were able to discern what, if any, impact they had on the customer's experience. What we found was pretty surprising and not at all what most companies would expect.

    Probably the biggest surprise was that the benefit most often touted by vendors – the ability to seamlessly migrate a customer from one channel to another (e.g., from a chat session online, to the phone) – doesn't actually deliver that much impact on effort reduction. In fact, it reduced customer effort by only 5.3%. To be fair, it does help, but at what cost? After all, this level of functionality is one of the most technically complicated (and therefore expensive) omnichannel benefits to deliver.

    Another benefit that delivered only nominal returns was “customer knowledge and recognition” – the ability for a company to integrate customer data and channels to instantly recognize who they're talking to and deliver to an agent a 360-degree view of the customer. Again, it delivers some benefit – 5.4% according to our research – but certainly not the value expected from a multi-million dollar omnichannel solution.

    It turns out, the two things that customers do care about are "service transparency" and "service proactivity." Meaning, customers want the companies they deal with to inform them of the steps taken and the timeframe expected to resolve their issue (transparency) and to alert them of updates/issues related to their request (proactivity). These two benefits/features help to reduce customer effort by 58.1% and 15.3% respectively.

    What can explain this discrepancy--the fact that channel integration and customer knowledge don't seem to matter much, but transparency and proactivity matter a lot? In our view, it all boils down to something we call "customer uncertainty." When customers leave a service interaction uncertain as to what will happen next and whether or not their issue is actually being resolved, they worry. That worry leads to additional customer effort in the form of another call/email/tweet/etc. to the company just to double-check everything. It’s an additional cost for the company and extra effort for the customer.

    To reduce customer uncertainty, leading companies do three specific things:

    1. Instill confidence by providing customers with information on next steps;
    2. Demonstrate progress by making the resolution process – and timing – more transparent, and;
    3. Increase access to information customers need when they need it.

    A good example is Delta Electricity, who provides customers with positive identification of the technician that will be servicing their home and then sends text message updates with the estimated time of arrival – helping to set customer expectations up front and reduce uncertainty along the way.

    To be clear, an omnichannel solution certainly can help companies provide greater levels of transparency to customers and deliver higher levels of proactive service. But, technology isn't the only way to deliver these benefits. Companies can also train and coach frontline staff, or update existing web content to accomplish the same thing.

    The reality is that most customer service reps have enough knowledge about the issues they're handling that they could deliver greater transparency into the resolution process, but handle-time restrictions often preclude them from doing so (even when it's clear that doing so would help reduce customer uncertainty).

    The same is true when it comes to proactive service. The average company can leverage their existing technology, tools and frontline staff to deliver more proactive service than they do currently. It’s about thinking one step ahead of the customer and helping them avoid frustrating, high-effort experiences down the road.

    In an era of “more” (more information, more channels, more options, etc.), a little extra transparency and proactivity will take you a long way in driving more customer loyalty. And, the best part is that it doesn’t have to cost you an arm and a leg to do it.



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