Archive for the ‘Call centers’ Category

Call center agents often sound robotic — and that may well be by design. Having agents follow a script helps keep service times predictable, supports delivering consistent service, and possibly reduces training costs. The same logic holds for other forms of electronic customer service interactions — be they chat sessions, emails, or Facebook posts.

But not every firm follows this model, relying instead on unscripted interactions to build relationships with customers. Among these is Dollar Shave Club, a subscription razor service with 2.2 million members (Why Dollar Shave Club invests in unscripted customer service, Los Angeles Times, Sep 26).

The company employs about three dozen member service agents who answer phones and emails, conduct online chats and reply to queries on social media — all while channeling the brand’s distinctly playful and irreverent tone.

The strategy isn’t easy. Training takes weeks. Finding the right personalities is challenging. It would be cheaper and less hassle to contract with a third-party customer service firm, which Dollar Shave Club does to complement its in-house team.

But online retailers, including pioneers Zappos and Bonobos, have found the investment in unscripted customer service worthwhile. The interactions, they say, feel more authentic and help humanize e-commerce brands that are, by their very nature, faceless.

So when does a scriptless approach pay off? (more…)

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Over the years, we have had a lot of posts on call centers. In some ways, call centers are a marvel of modern operations. They allow firms to serve a large volume of customers efficiently. But what’s it like to work in call center? As 20/20 reports, it not necessarily a walk in the park (Why Customer Service Representatives Might Be Deliberately Making Your Experience Worse, Mar 26).


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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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We have already written in the past about the use of data analytics to best route customers to agents based on demographics and other characteristics.  The NY Times has an interesting article on the use of data analytics to improve retention and employee-employer relationships (“Big Data, Trying to Build Better Workers“)

The article discusses the broader appeal of these ideas, but focuses on applications to call centers. Why call centers? In contact centers, customer service agents, that are hourly workers handle a steady stream of calls under challenging conditions, yet their communication skills and learning capabilities play a crucial role in determining both the employee’s tenure and performance. The article discusses a new startup, Evolv, which helps firms find better-matched employees by using predictive analytics.

Transcom, a global operator of customer-service call centers, conducted a pilot project in the second half of 2012, using Evolv’s data analysis technology. To look for a trait like honesty, candidates might be asked how comfortable they are working on a personal computer and whether they know simple keyboard shortcuts for a cut-and-paste task. If they answer yes, the applicants will later be asked to perform that task.


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