Techniques used in spotting, digging-out, and analyzing business data, to support better business decision-making in the call center or contact center.
Have you ever stopped to determine how many different types of customers you need to serve? The importance of having this type of customer insight became even more clear to me when I read an article written by the editor for Harpers Wine & Spirit, Richard Siddle.
In the article, he summarized a recent study by […]
Most VoC programs utilize only quantitative measures. This is not particularly surprising. Researchers and analysts tend to take a great many statistics classes and, as such, specialize in the manipulation of numbers. But quantitative voice of the customer data is not enough to be successful with customer experience management.
It is rare to find a customer […]
Proving that your quality program contributes a positive ROI often times feels like searching for the Holy Grail with your contact center investments.
On the surface, the question “can you prove that your quality program produces a positive ROI?” sounds simple. If not simple, at least do-able. But, the answer […]
All of the brand promises developed by marketing professionals can be fulfilled, broken, or discovered in the contact center. More and more marketing professionals are taking keen interest in the operation and insights that can be captured in contact centers. Moments of truth, magic moments, […]
Preventing marketing attacks from ambushing the customer experience
The concept of guiding patronage behavior can be traced all the way back to ancient Greece and in the print media back to the 1600s. I’m sure you’ve felt the impact of an effective marketing campaign and can personally attest to the success of such efforts on shaping […]
“Is the Marketing Department your call center survey support group?” is one of the self- assessment items in the 25 Mistakes to Avoid with Post-call IVR Surveys. This eBook consists of items designed to highlight attributes that are barriers to a successful customer experience measurement program. Take advantage of our knowledge and experience accumulated over the past 20 years since inventing post-call IVR surveying for call centers.
Why is this a problem?
By now most would agree that the management of a contact center is complex and challenging. How many other areas in your company require such a broad range of cooperation, knowledge, and expertise? Being the focal point of an organization draws attention that, at times, is not the kind that serves your service-focused mission. […]
When you think of a typical salesperson what comes to mind? Do you immediately conjure up visions of multi-colored flags, ‘zero-money down’ signs, and some sleaze-bag car salesman telling you to buy the over-priced lemon of your dreams? The term, salesperson, quickly makes us imagine this derogatory image, something that we do not want to be associated with as our career label.
Let me challenge your normal reaction to the word ‘salesperson’ with one of my favorite quotes from Robert Louis Stevenson, “Everyone lives by selling something.” Think about that for a moment. When you’re at the hair salon and he or she is discussing the option for highlights or the hair care products, this hairdresser is selling, right? If you are a marketer you’re hoping to ‘sell’ your audience with your subject line and convince them to open your email and look at your message. And even as a parent, you are ‘selling’ your six-year old on those healthy green beans (or at least trying to). But I bet if you asked that hairdresser, marketer or parent if they worked in sales their answers would be a resounding “No”. In fact, only one in nine people in the US are designated as being in sales, but most everyone is. […]
Hurricane Sandy ravaged the Northeast and changed the immediate futures of many. Focus will no doubt shift from extravagant extras to just rebuilding the necessities. For many local businesses looking to rebuild as well and turning to their loyal customers and the commitments made prior to this unthinkable disaster, you have to wonder when is the right time to ask your customers to be customers again.
For one local-area sports team, a letter was sent to its season ticket holders affected by the storm offering their support and reminding them their first payment was now due. If you are a season ticket holder it should come as no surprise that this money is due; you committed to these tickets nearly six months ago if not longer. As a team and a business in its own right, at a certain point disaster or not, there are still employee salaries and bills to pay. But if your home is gone or you just lost a family member in the storm and you get a letter like this, would you think the team is pretty insensitive to your situation? Or would you feel they were within their right to collect the money you promised to pay? […]
Unless you’ve been actively hiding from all forms of media for the past year, you’ve heard about business intelligence. A Google search of the term yields 108 million results. So what is Business Intelligence? Business Intelligence is the practice of using Big Data to gain insight and drive change within an organization. A pretty broad definition, right? How do we do Business Intelligence at Customer Relationship Metrics?
Much of the work we do with/for our business partners is based in call centers. Call centers have been dubbed “the center of your universe” for very good reasons. Terabytes of data on the customer experience are collected each year, from customer email addresses to compliments, product quality issues, questions, wish list items, consumer behavior, online presence and preferences, etc. There’s not a better place in an organization to be if your slice of heaven is data, data and more data! But much of the data collected in call centers is “raw”, unstructured, in a hard-to-use format, and/or disconnected from other key data points. […]
Mining and analyzing customer comments to understand sentiment is no longer a wish. It’s a must. Based on years of experience, I suspect many of you are like the business partners I work with: you understand the value of the activity, would love to be able to get your hands on the insight, but don’t have the resources to do the work.
But there is good news. Using basic business intelligence approaches, it is possible to get a quick start on sentiment and text analysis to better understand what your customers think and say about your business. This information can then be leveraged to better serve customers and ultimately, improve the bottom line.
The rate at which customers provide commentary in customer experience surveys in itself can be very telling. Below are examples of insights that can be gained simply by examining the relationship between key real-time survey metrics and the propensity of customers to provide verbal feedback.
For the business partner depicted in the chart below, customer comments and real time alert rates were highly correlated. The more likely a customer was to comment, the more likely alert rates were to increase, and vice versa. This suggests that dissatisfied customers who required a follow up call from a manager were more likely to leave negative comments than positive ones.
While this may seem troublesome at first blush, understanding customer complaints is often an untapped gold mine. Reading and mining these comments could offer significant intelligence and gains for this business partner which can then be woven back into continuous improvement initiatives. […]
I recently had to call the post office’s customer service number regarding a change of address form that got screwed up. Monday I waited on hold for 15 minutes and finally hung up. Tuesday, the same deal. I finally physically went down to my local post office on Wednesday to deal with the mess in person. And there I waited in line for 20 minutes before finally getting it sorted out. There was one (!!!) person working at the post office window to deal with the many, many disgruntled people there. It sure makes it easy to see why they lose money each and every day they operate.
While I understand the reality of our economy, it’s too simple to say ‘cut headcount’. Most financial people making the decision to cut headcount are not very skilled or intelligent. They are not capable of looking at the entire picture. They are simply making quick cost savings in the short run, without considering their long-term savings and growth potential. Who ultimately pays the price for cuts in personnel? First the customers pay, then the company. Your once loyal product advocates get cast aside in the name of smaller overhead and a more manageable bottom line. So what’s the solution? How can you reevaluate your business AND the needs of your customers to come to a more appropriate cost savings solution than just slashing headcount? […]
Recently, I walked into my classroom for the upcoming term and braced myself for the exasperating questions that seemingly every class insists on asking: “Will you be sending out lecture notes after class?”, “will this be on the test?”, and “why do I have to take this [any variation of math] class?” The answers to which are “Ha ha, ha ha, ha ha,” “maybe” and “because you may want to choose to work in the fast food industry, because I’m guessing you’d prefer your Thunderbird T-top to rest on tires and not blocks, because maybe someday you’d like to have tires on your car but not on your house.” But, this time around I was pleasantly surprised. A student’s question about the merit of using paper and pencil (and whiteboard) to do math in a world of ever-accelerating computational speed led to a discussion of the priorities businesses place on subject-matter expertise versus technological skill.
The unfortunate reality is that many well-intentioned businesses spend millions of dollars each year on good, even great, tools designed to make their businesses more efficient and provide greater visibility into the inner-workings of the business. They spend time and money making a business case for the purchase, calculating the product’s ROI, payback period, etc. Unfortunately what is often lacking is the subject-matter expertise required to make good on the ROI projections. […]
Targeting customers with the right message at the right time and getting that message into the hands of a decision maker is one of best ways to gain new customers and to upsell current customers on new products and services. Unfortunately for many companies, they fail miserably (unintentionally for sure) in their marketing efforts […]
Nearly a year ago, I wrote a blog entitled Self-serve: Cheap can be very expensive about the high customer experience cost of the self-serve model. Imagine my delight to see a recently published study conducted by TSIA and Coveo supporting Customer Relationship Metrics’ conclusion. Among the study’s findings was the fact that while voice and face-to-face contact are the most expensive ways to support customers, they also result in the greatest customer satisfaction.
I realize this study is not going to make anyone shut down their email, web chat and self-serve programs, so instead this three-part blog series is designed to help you make these types of interactions better for your customers and provide you with greater customer insights into the customer experience results for the various channels handled in your call center.
The success of any Business Intelligence project is contingent upon people, not technology. Analysts and end users must work in concert to ask a concise question, identify the data available to answer that question and, validate interpretation of analytic outputs in context of the business environment. From there, the subject-matter experts (statisticians, data analysts, data miners, etc.) must be allowed the freedom to draw upon their breadth of knowledge and experience to select the best methodology for the job.
I cannot tell you how many times a business unit manager has come up to me and with all of the confidence of a just-learned-to-stand toddler and declared “I need a model!” “Really?” I respond. What type of model? Logistic? Linear? What kind of data do you have for me to work with?, and a plethora of other rather technical questions. My point is that predictive models have been used quite successfully in marketing for many years. In a business environment where “half of the organizations surveyed do not take advantage of analytics to help them target, service, or interact with customers” according to Accenture’s Customer Analytics survey, predictive models have gained the esteem and notoriety akin to Steve Jobs.