This month, I had the opportunity to write an article for 1to1 Magazine about the top issues that CRM professionals will come up against this year. I focused on five points:
- Short-term cost-cutting hurts long-term growth.
- New technologies making new skills necessary for call center employees.
- Corporate arrogance hampering growth.
- Unnecessarily difficult relationships with vendors and partners.
- Challenges in translating big data to usable information.
The good news is, all of these issues can be overcome. To see how your organization measures up, check out the full article, “5 Landmines for CRM Professionals to Avoid in 2012.”
Let me know if you’ve encountered any of these issues, or if you think I missed any!
What do you do when one of your best selling products, your cash cow, your go-to, has decreasing sales revenue and can no longer be counted on to save the sales figures? Worse, what if most of the ones being sold are quickly returned? The call center has the answers, and they lie within the call logging and coding data, and the metrics from social customer service. Companies can mine their ‘big data’ by using text analytics and uncover the root issue of this terrible trend.
The company Twitter feed and Facebook page supports the discovery that customers perceive the product to not be as fast as the competition, and lacks some additional functions they know are possible now. When the CRM records are analyzed the hypothesis is confirmed, as each return highlights the product speed as the main reason for the return.
While the problem may not be a quick fix, the answer was found significantly faster through text analytics than waiting until the Annual Report or The Street, reports the loss of earnings. The business intelligence through text analytics can lead to the creation of a new process for the product development group, a new product roll out, and before you know it that cash cow product is back on top in the market place. Continue reading “Text analytics adds the ‘why’ behind the numbers.” »
There’s something so interesting (and addictive) about social media. It makes even luddites feel tech-savvy; it’s hip and new, and, according to some customer experience experts, anyone who matters is doing it. And consumers’ social media activities extend well beyond updating their Facebook page or tweeting about their most recent customer service disaster. Customer service is going social – big time!! According to Zendesk, 62% of consumers have looked to social media channels for customer service issues.
But before you begin logging onto your company’s Facebook page a dozen times a day to see how many “likes” you have, and endlessly searching tweets containing your company’s name, step away from your keyboard. Social Media Monitoring is not the place to start your Social Customer Service efforts. Responding to the noise on social media platforms is like chasing smoke – frustrating, time-consuming and ultimately futile if your aim is to effectively improve the customer experience. If you take this approach you are incapable of controlling what people put out there in the social sphere about your organization.
Instead, think about taking the inside-out approach. Social Media Business Intelligence, is so much more sexier than Social Media Monitoring, as it is far more effective in driving long-term service improvements within an organization which ultimately reduces the number of complaints customer voice through all channels, social media included. The interactions organizations have with their customers are increasing in their complexity. Where in the past all issues were funneled through the call center, today customers are more likely to address an issue through self-serve. Failure in that arena leads customers to community chat (filled with an equal mix of knowledgeable gurus and misinformation) and finally the call center. Dial-to-disconnect speech analytics can help organizations gain insight into these complex interactions and more importantly, their failure points. Continue reading “Social media monitoring is like chasing smoke” »
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.
What Customer Relationship Metrics does in Business Intelligence engagements is use a completely hosted reporting and data aggregation tools to bring disparate and largely unrelated data sources together into a platform where analytics are then possible. Analytics provide business partners with a means to identify relationships and to prioritize metrics in terms of capture and analysis, in what manner existing data can be best leveraged, and in many cases conducts the analysis that reveals opportunities, bottle-necks and risks within the organization that when rectified, result in top-line growth and bottom-line savings by improving the customer experience.
The organization depicted below is falling below their Call Resolution goal for the year. An analysis of resolution performance (from a customer perspective) revealed that the second largest department (in terms of call volume) is performing 15% below goal. This department accounts for approximately 33% of all calls and therefore represents the largest opportunity for improving the organization’s call resolution performance. This department is also lagging on the KPIs first call resolution, repeat call resolution, service level, and average handle time. This additional insight reveals that this department is experiencing failure in delivering resolution not only on initial contact but on any further contacts customers deem necessary to attain resolution. The repeat call problem, combined with above average handle time makes the issue of non-resolution a very costly one.
An analysis of customer comments about non-resolution revealed the following:
- 22% of customers complained that agents did not seem to care about the customer’s problem or expressed no desire to help the customer.
- 11% of customers indicated dissatisfaction with the amount of time they had to wait to reach an agent.
- 40% of customers perceived that a specific line of company products were lemons (requiring multiple repairs for the same / a recurring problem due to product quality).
- 27% of customers reported dissatisfaction with the company’s resolution to lemons Continue reading “What is Business Intelligence?” »
Holistic medicine is a big picture view – the emotional, physical, psychological and environmental factors that contribute to a patient’s overall health. Without considering all of these factors, a doctor may only solve part of the affliction without completely healing the patient. In your call center, the agents lacking a holistic view of a customer’s history may only solve part of the customer’s problem but not rectify the entire issue.
Think about how information in your company is heavily siloed by department which dictates that your call center agents have access to some of the customer’s history and information but not a holistic view of their entire interaction/relationship with the company. As we discussed last week, when Big Data is put to work in the right way it greatly benefits your customers and your brand. But when marketing, sales, online and other departments generate, collect and evaluate customer data but do not share it with the call center, the power of Big Data is undermined.
Your customers already think you are the master of Big Data, right? How often do you hear, ‘why can’t you see that on your screen? ’ Customers get frustrated and call center agents fail when the customer intelligence data available is incomplete or not readily accessible to them during a call. It’s also easier to misdiagnose a customer problem, miss an up-sell or cross-sell opportunity, or even lose a customer if the agents are limited to a single view of that customer. Think about the times you’ve called about a product or service issue and how much better your customer experience would have been had they offered to upgrade your service because they could see your contract was about to expire. Or gave you a discount on a related product because they had access to your spending patterns. Or could see that you spend most of your time shopping online through their web site and then tweeting about your purchases, so you were informed about their Twitter service handle to use the next time. Continue reading “Holistic medicine for your call center; look at the whole customer experience.” »
Everyone is abuzz over the ‘new’ Big Data trend and while most companies are floundering to analyze the data they already have, not to mention the data they have yet to capture, some big brands are setting the bar of customer analytics excellence pretty high.
So what are these brands doing right? Have they identified the proper analytics people to exploit their data in a useful way instead of falling prey to the skills-gap issues that plague other companies? Is it the data itself – what they are analyzing, when and how much? Or are they just internally and departmentally sound and settled thus allowing them to look at the big picture of Big Data?
When companies can look at their data and deduce the relationships between the data sets, it’s the customers that are reaping the immense benefits. To take a big data for marketing example, I’ve been a card holder at a particular clothing store since 2004. Because I’m spending money with their credit card they are easily able to track my purchase frequency, what departments I shop in, and can predict what I am likely to buy in the future. What this means for me is tailor-made marketing including rewards and discounts I’ll actually use. It’s not just the credit card data; they are looking at my social media habits too. I ‘like’ their page on Facebook and by pairing my profile information with my city, and crossing that with my credit card billing information and spending, they sent me an email that my local mall was having a sale on sweaters and gave me a discount if I want to take advantage of the sale. Result – they are getting more of my business than before. Continue reading “Big Data done right can benefit brands and customers.” »
A friend of mine works for a prominent university where one of his primary responsibilities is actively engaging with the alumni and athletic boosters, both directly and through social media channels, to garner large donations. Recently his department compiled a tribute video for one of their most prominent alumnae (and donor) using recorded messages from some of their past outstanding football players. It was a great idea in theory but tracking down this old player data proved to be rather difficult.
The life in academia is very much like our corporate lives. We have TONS of data about past and present customers (students) but it’s not easily accessible, not well organized and definitely not easily analyzed. My friend’s task sounded easy – track down football players that played for the university between 1974 and 2010, contact them, and get them to agree to appear in the tribute video that would air during this year’s homecoming celebration. What seemed like a straightforward request, turned into nothing short of a Big Data nightmare. You must be thinking, ‘I can get past customer addresses – what’s the big deal?’
The big deal is that my friend’s problem goes far beyond getting addresses. What kind of analytics are they using to determine who are the most valuable alumni (customers)? The university likely picks the person(s) who have given large amounts in the past (bought more) but who in their population is not connected, is not giving, has not been engaged with the university. There are invaluable relationships among the data that will increase donations (purchases) but you cannot just “eyeball” the answer. Continue reading “Mo’ big data, mo’ big problems.” »
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. Continue reading “Tips to prevent creating your own contact center analytics shelfware.” »
The other day, I got the $64,000 question (more like a million than dollars nowadays) from a client — why was their best-selling product not selling so well anymore? For years it had been their cash cow because of its ease-of-use, long lifespan and consistent price point. My client was scratching his head because, in his mind, nothing had changed. The call center was still taking the same volume of calls and they hadn’t had any recent agent turnover, so on the surface there was no reason as to why sales had fallen off a cliff.
The answer is always with your customer and often takes some outside eyes to take a different approach. So we dug deeper into the customer experience data to find out what was happening during the agent calls that was contributing to the decline in sales. Turns out that their tenured agents were consistently attempting to up-sell customers (and being a little pushy) on the accompanying products that the customers felt they didn’t need. This was causing many of their customers to sour and end the call, purchasing the product elsewhere. The analysis identified our client’s issue and with a quick re-scripting for their agents they got a steady increase in sales over the months following this small tweak. Continue reading “Does your customer experience data answer the $64,000 question?” »
In addition to reading this blog, you should also check out 
the video series Speech Analytics Best Practices. Our Chief Spokesman, Jim Rembach, discusses the importance of identifying the key personnel required for a successful Business Intelligence implementation and the traits or attributes of these personnel:
1. Analytic / math skills,
2. Project management skills,
3. Persuasive story-telling ability (art), and
4. Business acumen. Continue reading “Learn How to Become a Speech Analytics Analyst in 30-Days or Less” »
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