When you call some firm’s customer service number, do you really care whom you talk to? I mean, beyond basic competence in addressing your request or walking through how to solve a problem, do you really care? Would it matter if there were some way of matching you with a better agent? “Better” here is not about skill level, per se, but rather about someone who matches your personality type. That is, you and I may call with the exact same issue but have different agents recommend as best for each of us based on just how we behave on the phone.
This is the kind of service offered by a Chicago-based firm called Mattersight, which has been featured in recent articles in both Crain’s Chicago Business (Why you might not hate calling customer service next time, Feb 12) and InformationWeek (Big Data: Matching Personalities In The Call Center, Feb 17). Here is how Crain’s describes what they do:
Your call is automatically routed to a like-minded agent who’s been matched to you according to factors such as communication style and personality type. It sounds a little like science fiction, but it works. Clients such as pharmacist CVS Health and online insurers Progressive and Esurance (an Allstate subsidiary) say Mattersight’s software speeds up calls, boosts sales or raises customer satisfaction by 10 percent or more. …
Mattersight’s product, based on more than 10 million algorithms developed by an in-house team of behavioral scientists, is overseen by David Gustafson, Mattersight’s product chief and executive vice president. The algorithms are if-then statements that analyze callers according to speech patterns and cadence in order to gauge their personality type and mood and route them toward a simpatico customer-service rep.
People’s speech patterns constitute “an emotional syntax,” says Gustafson, 37, one that can quickly demonstrate whether a caller “is someone who values order and logic, or if they’re fun, spontaneous and creative.” The best customer service reps are adept at working with all personality groups but still do better with one type or another; Mattersight’s tech aims to play to that strong suit as often as possible.
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Whenever there are stories about Uber or TaskRabbit or any other “sharing economy” platform, the benefit of scheduling flexibility is inevitably mentioned. These firms may not offer their workers (more accurately, contractors) benefits or guarantees of employment, but they allow workers to craft a schedule that fits their own needs. Does granting such flexibility work in a more conventional setting?
Zappos, it seems, is out to answer that question with its call center workers (Zappos is bringing Uber-like surge pay to the workplace, Jan 28). Zappos’ incumbent system had call center agents signing up for their preferred shifts on paper once a quarter based on seniority. That obviously limits flexibility. Further, Zappos (not surprisingly) faces some predictable patterns in its call volume that are challenging to meet. For example, there is a spike on weekday mornings as people call from the East Coast — which is way early at Zappos’ Las Vegas call center. The solution? A bit of Uber-like surge pricing.
[CEO Tony] Hsieh was not available for an interview for this article, but as Goldstein recalls, he asked the Labs team, “‘How do you feel about looking at something like Uber for the call center?’ It was definitely not something we’d actively been thinking about,” Goldstein says.
That conversation sparked the development of what is now known as Open Market—referred to as “Om” internally—an online scheduling platform that allows workers to set discretionary hours and compensates them based on an Uber-esque surge-pricing payment model: hourly shifts with greater caller demand pay higher wages. The goal of Open Market was to create a “free-market system,” Goldstein says, and strike a balance between the rigidness of customer service center scheduling and what the company says is its dedication to giving employees time to pursue other opportunities at Zappos, like extra training. “We wanted the [customer service center employees] to work more flexible hours, eventually 100% flexible, and reward them based on how much or how little customers need them to work,” he says. …
Zappos limited the Open Market pilot to the 213 employees who work the customer service center’s phones. Everyone received at least 10% flexible time, so during a 40-hour week, employees would have four hours to play with. They could choose to not work during those hours or they could fulfill them whenever they liked by tacking them onto the start or end of a workday or by coming into the office on a scheduled day off.
Employees decided when to work with the help of Open Market’s real-time customer service center metrics algorithm and historical data that showed customer demand, as measured by the wait time of the longest-holding customer, and the accompanying compensation rates. The longer the hold time, the higher the customer demand, the more the employees working that shift would get paid.
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When was the last time you called a business number, got put on hold and heard dead silence? In all likelihood it was some time ago. So why play music when customers are forced to wait? It’s not like anyone really enjoys hearing pabulum played at the highest fidelity permitted your phone’s speaker so there is a real question here for why firms should go through the effort. Slate has an article that tries to get at this question (Your Call Is Important to Us, Sep 8). If you prefer to listen instead of read, here is an NPR interview with the article’s author.
The first thing to recognize is that playing something for callers placed on hold aimed to solve a practical problem: If all you here is nothing, how do you know that the call is still connected?
But in the spring of 1962, an application appeared in the U.S. Patent Office, humbly titled “Telephone Hold Program System.” “In the course of receiving telephone calls,” it began, a bit grandly, before settling into the problem at hand: What to do about that dead silence the caller endured while calls were transferred, their respective parties chased down? Operators were supposed to check in again on callers who had been waiting; but what if they got busy? “In any event,” the application went on, “listening to a completely unresponsive instrument is tedious and calls often are abandoned altogether or remade which leads to annoyance and a waste of time and money.”
So the thought was that using music could improve customer service and operation efficiency. People would be more willing to hang on the line and thus would not need to call back later. Does that actually work? (more…)
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Check out this video of Steve Jobs talking about the origins of the iPad.
The text that appears as Jobs talks is how a computer program developed by a firm called Beyond Verbal is interpreting Jobs’ emotion. That is, the program is judging whether Jobs is feeling fatigue or nostalgia based not on what is saying but how he is saying it.
Kinda nifty, but does it have commercial applications? The claim is yes and it is in call centers.
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American Express runs its call centers differently. No scripts. No high pressure on handle times. Instead, they put a focus on relating to customers and evaluate agents on how the customers they interact with answer the question “Would you recommend this company to a friend?” Fortune has an interview with Jim Bush, American Express’ EVP of world service, who has overseen this change (How can American Express help you?, Apr 19). (Dedicated readers of this blog with long memories might recall that we posted on this about a year and a half ago.)
He makes some interesting points on their philosophy in running customer service — starting with the fact that they view call centers as serving customers, not processing transactions.
The perception of service is that it’s all about problems. Problems are actually a very small percentage of why customers interact with American Express. What we’ve learned is that the power of that interaction gives us an opportunity to expand the perception of the brand in a very positive way.
There’s a tendency to see service as a sunk cost — the customer is reaching out to you. So people say, “It’s a cost. Let’s look to eliminate it.” And over time we can eliminate friction points, which eliminates the need for some customers to interact with us. But the reality is, it’s a very powerful opportunity to build a relationship.
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So which country is a bigger market for off-shored technology services, India of the Philippines? According to Market Watch, the latter is the answer (Philippines lifted by outsourcing boom, Jun 15).
The Philippines’ fast-growing business-process outsourcing industry has turned the Asian nation into a major center for off-shored information tech services. The country recently passed India as the world’s top outsourcing destination, according to a report by the services arm of International Business Machines IBM +1.09% — which has a major presence in the country. …
“Ten years ago, we had maybe about 25,000 people in the industry,” said Jose Mari Mercado, business development director at Convergys in the Philippines, who said that number reached about half a million last year.
“The interest in the Philippines has really grown tremendously in the last five years,” he added.
While business outsourcing is typically associated with call centers, the industry actually covers a range of IT services, including customer relations, human resources, accounting and even more specific functions, such as mortgage processing.
In 2010, the Philippines’ IT and business process outsourcing grew 26% to $8.9 billion, according to the Business Processing Association of the Philippines. Workers and professionals employed by the industry grew by 24%, the industry association said.
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We have had a couple of recent posts about firms trying to get more out of their call centers through psychometric data. The idea is that by classifying both customers and agents along psychometric dimensions, the firm can route callers of a particular characteristic to the type of agent that is most likely to lead to a good outcome (where “good” is presumably defined based on what the firm wants). I have to admit that I am not overly familiar with what psychometric measures they are using and am not sure how well they can measure these with infrequent customer contact. At some level, this starts to sound like whether a libra should date a taurus.
With that background, I found a recent Sloan Management Review article really fascinating (Matchmaking With Math: How Analytics Beats Intuition to Win Customers, Winter 2011). It is an interview with Cameron Hurst, a VP at Assurant Solutions. Assurant Solutions sells credit insurance. You pay them every month and then if you are, say, laid off they help cover your credit card bills. What customers pay ranges from $10 to $80 per month and it is not hard to see that some people may have second thoughts about paying that. What seemed like a good idea six months ago might not seem worth $20 now. Hence, their call center plays a key role in keeping customers. When customers get cold feet, it is up to call center agents to “re-sell” them on the product and retain the business. And that is where “affinity routing” comes in. They brought in some business analytics experts who already worked in the firm but doing actuarial work and such and asked them to look at the call center.
The first thing that was interesting about their approach was that rather than thinking about the average speed of answering phone calls, or the average “handle time,” or service level metrics, or individual customer experiences or using QA tools to find out what we did right and what we did wrong — all the things we usually consider when looking at customer and representative interaction — they started thinking of it purely from the perspective of, “We’ve got success and we’ve got failure.”
Success and failure are very easy things to establish in our business. You either retained a customer calling in to cancel or you didn’t. If you retained them, you did it by either a cross-sell, up-sell or down-sell.
So this is what they started asking: What was true when we retained a customer? What was true when we lost a customer? What was false when we retained a customer? And what was false when we lost a customer? For example, we learned that certain CSRs generally performed better with customers in higher premium categories while others did not. These are a few of the discoveries we made, but there were more. Putting these many independent variables together into scoring models gave us the basis for our affinity-based routing.
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