by Rebecca Anderson on July 13th, 2015
It seems like organizations have been collecting and analyzing vast amounts of complex customer data for ages – there’s a reason we call it ‘Big Data.’ But thanks to the Internet of Things (IoT) and mobile/digital advances, the amount of customer data has been increasing exponentially. According to a fresh Kinsey Global Institute report, the potential economic impact of IoT could be more than $11 trillion annually by 2025. However organizations have not been able to make the data usable until recently because most of them still don’t have the proper tools to take action based on the data they have.
According to Aberdeen’s new study “Big Data in CEM: The Path to Productive Employees & Happy Customers” only four percent of companies are extremely satisfied with their ability to use customer data within Customer Experience Management (CEM) activities. Four percent. That’s a Big Data disappointment. The Aberdeen study demonstrates how Big Data is an opportunity that can only be leveraged through technology.
Aberdeen identified three activities that best-in-class companies use for capitalizing on big data.
- Gather customer insights from employees across all parts of the organization to find opportunities to better sell, market and serve customers.
- Leverage the knowledge in your IT department to streamline technology to a single view of customer data.
- Take action! The data is only useful if you are able to take action on it. For example, analytical tools such as business intelligence and predictive analytics can help convert data into insights.
In addition there are some common strategy changes that top performers have employed to manage big data in CEM.
For all the effort put into collecting data, isn’t it time that the data started working for you?
by Tim Dreyer on September 23rd, 2014
We have written much about what we term the ‘relationship revolution’, that organic evolution of consumer control fueled by our hyper-connected behavior. It is a seismic shift in who has the upper hand in the customer-company relationship. But a few new trends percolating on the outskirts of the customer engagement industry could signal even greater power in the hands of consumers.
The first is Tor, a kind of web browser aims to make your internet activity stealth; unseen and undetected. Tor does this by routing traffic through a number of other connected internet users, making it very hard for governments or private companies to track internet usage. Over a million people use Tor, which became legendary after Edward Snowden clandestinely leaked information revealing that the NSA was eavesdropping on average citizens. Before Snowden, Tor was popular with drugs and hitmen trying to keep their illicit activities hidden from the law. Already sounds scary, huh?
So why should a company be concerned about Tor? Law abiding consumers, attempting to anonymously post negative comments on Yelp, may try to avoid creating a data trail that customer service departments can tap into. Stealth internet use makes it difficult for companies to engage their customers intelligently. Most consumers would not have a real need to conduct anonymous interactions with the companies they do business with but if more companies use or misuse that data to the annoyance of their customers, more people may feel the need to avoid data sharing altogether.
The solution of course is making sure consumer data is used to the benefit of the customer. An Aspect survey earlier this year found that 47% of consumers felt like the information companies had on them rarely resolves their issue but more than half of them are willing to provide personal information if those companies deliver targeted, relevant offers to them.
The other trend is consumer data protection in Internet of Things (IoT) applications. Customer service, relative to Machine-to-Machine communications is still in its very early infancy but as the ability for appliances and automobiles to communicate directly to manufacturers through cloud-driven service without the need for human intervention begins to take shape, the question arises as to what data are people willing to share. Or better, what are they willing to let their machines share. In the just-published piece in CIO, author Raman Mehta asks just who will the consumer be willing to give their appliance/machine data to. How long will that information exist in a public/private cloud? And who exactly will have access to that data?
Why should a company care? Much like how consumers have become ubersensitive about handing out credit card information to even the most trusted retailers, the theory that personal machine usage history could be used against them, or at least used to annoy them is only going to inch closer to reality.
- Will their furnaces be deluged with promotional spam emails for discount filters?
- Will their hatchbacks accept performance-improving application downloads that perhaps they don’t really don’t want?
- Could the warranty on that hatchback be voided if they miss an oil change?
- Do they need to place their ovens on no-call lists?
Companies looking at IoT-driven service need to have the same data sensitivity and create the same data protection trust they have when a customer talks to an agent or provides information through a web chat. Much like the trust consumers have that the buying and search history data they share will be used to present customized, relevant offers by the companies they do business with and not be used to annoy them, so should the data they choose to share from their connected machines. I’m going out on a limb here but I don’t think thermostats will like spam any more that humans do.
The relationship revolution was born out of consumer dissatisfaction. After years of tolerating having to repeat themselves and being treated like strangers, they have taken control of the conversation, and are more vocal and less tolerant than ever before. Machine-produced data presents incredible opportunities for proactive customer service but if companies squander those opportunities, the last thing we want is for the machines to join in the revolution.
by Kathleen Schroeder on July 7th, 2014
When speaking of the optimal patient experience, many healthcare organizations focus solely on direct patient care initiatives. Only recently have healthcare systems realized that the total patient experience starts with front end processes. Patients today expect to have multi-media channels for contacting a physician, the phone answered in a timely fashion, and their needs met at the first point of contact. They also want the agent answering the phone to be knowledgeable about their particular issue and be treated respectfully, with compassion, empathy and understanding.
According to HCP Associates’ Top 10 Changes in Patient Expectations, technology brings four fundamental changes to the patient experience:
- Access to Information: Eight of ten people do their health care research using the Internet, the vast majority using Google. They also post about their experiences with providers, good and bad, and these posts are all just a search phrase away. Search engine rankings not only make your practice more visible, higher rankings have a profound effect on how prospective patients view your capabilities, status and popularity as a provider.
- Quality of Service and Care: It is necessary not only to say what you do, but to do what you say professionally, effectively and consistently. In short, your operational processes from the first telephone encounter to discharge should be equal parts quality of care and quality of service.
- Differentiation: Providing quality of service equates directly to the perception of competence. You may be getting away with doing things the way they have always been done, but not for long. The industry is changing, and perceptions and expectations continue to change with it. Those who fail to adapt will likely become the employees of those who do.
- Access to Care: The primary decision metric for most patients is accessibility. Waiting to be seen when you are sick and scared, whether it is for an appointment or in the waiting room, does not enhance the patient experience. In fact, it complicates it on numerous levels including clinically. It impacts physician and patient referrals, patient retention, patient acquisition, patient attitude, patient perception and a host of other issues. Prompt, professional and accessible service wins every time.
Meeting patient expectations is about more than accommodation—it is risk management (happy patients do not sue.) It keeps you competitive and results in improved clinical care (good patient experiences lead to better outlooks, outcomes, an enhanced sense of security and well-being.) These are tall orders for all healthcare organizations, but these goals are attainable with the right tools and the right people.
How can technology help you meet patient expectations?
The patient experience is about more than customer service and provider expectations. The optimal patient experience encompasses the entire patient journey, beginning with the first point of contact. Meeting the needs of patients will ensure a life-long journey with the patient. If you are not successful with engaging and satisfying the patient at the initial point of contact, then the quality of care may not matter. They will search for another provider who they feel they can trust and who will meet their needs.
Offering multi-channel methods for contacting a physician’s office is critical. Today’s patients have varied lifestyles and demands on their time, expecting to be treated like a valued consumer – not just another caller. Talking to a “live person” may be important to one patient, but not another. State-of-the-art multi-channel options such as texting, on-line scheduling and chat are available to help your organization respond to patients’ individual preferences. Interactive chat can help you capture new patients by offering website visitors a warm invitation to chat, encouraging them to take the next step of actually contacting your organization.
It is surprising how many healthcare organizations cannot tell you how many dropped calls they have, what their first-time call resolution is, and how satisfied the patient was with the contact experience. Does your organization have the capability to call back dropped calls? Dropped calls, prior to the patient talking to an agent, or during the conversation, are a reality. Fortunately, technology is available to re-engage with the patient.
Utilizing the right contact center technology can help ensure that you not only meet patients’ expectations, but that you exceed them. This is all part of the journey to establishing a life-long relationship with the patient.
by Christine OBrien on June 23rd, 2014
Patient satisfaction is a growing area of focus in healthcare. According to Kaiser Health News 69% of patients would recommend a hospital based on a prior encounter, which makes every positive experience all the more critical. In fact, as highlighted in the same study, 70% of healthcare providers rank improving the patient experience as their #1 priority. But despite this growing emphasis, many providers are falling short on delivering the kind of experience that generates positive referrals and word-of-mouth interest.
What can providers do to improve the patient experience?
The key may be uncovering and addressing the root causes of patient dissatisfaction, which can range from individual concerns to systemic gaps in care. This information comes to you in the form of patient and clinical data, and analyzing the data you have can help unlock new solutions and solve existing challenges.
Attend the online panel discussion, Improving the Patient Experience with Healthcare Analytics, with Healthcare Intelligence and Aspect Software on Monday, June 30 from 2:00-3:00 pm ET. Speakers will include: Patty Nahra, Senior Partner, Healthcare Intelligence LLC; Rodina Bizri-Baryak, Senior Partner, Healthcare Intelligence LLC; and Glenn Hoffer, Senior Account Executive, Healthcare Practice, Aspect.
During this hour-long discussion we’ll explore the business benefits of utilizing healthcare analytics to improve the patient experience, as well as:
- Leveraging clinical data for more informed business and patient care decisions
- Developing strategies to reduce costs and deliver more accessible care
- Improving quality of care and enhancing the overall patient experience
Improve care quality and reduce costs while effectively managing larger patient populations. Find out more — Register for the webinar!
by Kathleen Schroeder on June 2nd, 2014
Defining Key Performance Indicators
Key Performance Indicators (KPIs) are metrics that are put in place to ensure that patients are being serviced in a timely way. Patients often call for billing claims, appointment requests, nurse triage, forms, prescription refills, etc… Some of these calls may be routine while others may be life or death. Given the variety of requests that come through the contact center, how does a healthcare system set performance metrics? Most contact centers focus on the Average Speed of Answer (ASA), the Abandonment Rate (ABR), First Time Call Resolution (FTR), the Average Handle Time (AHT) and Service Level (SLA).
Let’s examine these key performance indicators from the patient’s perspective. The ASA, ABR and SLA ensure that the call is answered quickly. The FTR ensures that the patient’s request is handled the first time to eliminate wasted time and frustration. The AHT ensures that your staff is capable of handling the patient’s requests with agility and skill.
How do you know if these key performance indicators really matter to the patient? How do you know if the targets you set are meaningful? Have you asked your patients for their opinion on the subject?
Meeting Patient Needs
Meeting the needs of patients is based on a simple premise – if you understand and measure what is relevant in the eyes of your patient, you can improve their experiences.
With this in mind, it’s important to involve the patient in setting performance targets. Aspect has post call survey tools which are a great way to capture key pieces of patient provided information. Patients should be asked to indicate acceptable wait times on the phone as well as comment on wait times for appointments and their willingness to be entered into the system as a referral. By collecting and analyzing this information, patients can be stratified into groups as some may have different needs than others, ex: Adult vs. Pediatrics, General vs. Specialty and Routine vs. Cancer Screening requests. Assessing the soft skills of your staff and the simplicity of getting through the appointment scheduling process are two key pieces of the patient experience puzzle that can be captured in post call surveys.
Aspect allows contact center analysts to assess the patient’s needs through statistical measures. The Data Views affords the analysts to extract any metric and extrapolate the statistical connection, ex: ‘How long do patients wait before they abandon a call’?
There are many paths on the road to understanding the patient’s needs. Data analysis and post call survey solutions from Aspect help you create the most direct way to establish meaningful key performance indicators and ultimately better patient experiences.
Want to learn more about how healthcare analytics can improve your patient’s experience? Join Aspect and Healthcare Intelligence for a complimentary one-hour webinar on June 30 at 2:00 p.m. ET (11:00 a.m. PT.) Register today!
by Kathleen Schroeder on May 1st, 2014
Co-authored by Aspect and Healthcare Intelligence
Analytics and benchmarking are the foundations of a well-run contact center. Non-healthcare industries have known this for years. Healthcare contact centers are now embracing these goals, realizing the measurements are pertinent to their industry. In addition to the basic contact center metrics, patient-centric metrics must be infused into the daily operations as well.
The basic measurements of a well-run healthcare contact center are focused on time to answer, abandonment rate, average handle time, idle time, talk time, agent occupancy and non-productive time. Focusing on the abandon rate may eliminate the need to monitor time to answer. Patient tolerance levels vary by service line. Since there is a direct correlation between the speed of answer and the abandon rate, patient tolerance will let you know when the hold time is too long with higher abandon rates. First time call resolution in a healthcare contact center also ranks high when analyzing metrics. Meeting the patient’s needs during the first call will improve patient satisfaction and employee productivity. First time call resolution can also create efficiencies by decreasing unnecessary call volumes and alleviating pressure on the workforce during peak call periods.
Quality assurance is one of the most important things to measure, but seems to be the one metric that is not measured consistently. Other expectations of the healthcare contact center manager at times supersede this goal. Knowledge of whether employees are asking the correct questions for demographic, registration and appointment processes will ensure patients are scheduled correctly, billing information is available for reimbursement of services, and patients are being communicated with in an empathetic manner.
Healthcare analytics is not merely about collecting data; it’s about analyzing the data and creating actionable improvement processes. Patient expectations will dictate what you measure and analyze.
As the healthcare industry and the contact center industry begin to fuse, it is essential to establish patient-centric key measures of success. Aspect Healthcare and Healthcare Intelligence can help you take your first steps to creating better patient access and experiences through proven analytical processes.
by Jeannie Jackson on March 19th, 2014
With a newer, trimmer outlook on clothing, I was ready to dive in. What I learned very quickly in entering the store, unfortunately, is that the style they sold had changed dramatically. Cute skirts, silk blouses, and sparkly jewelry had somehow turned themselves in to a massive overload of fashion faux pas that definitely did not appeal to me. One mannequin alone had a solid 7 different pieces of clothing and to me it was just way too much. WAY. TOO. MUCH.
It could just be that I’m not up to date on the latest fashion trends that inspired the thigh-high boots with lace leggings and a semi-skirted corset look with lots of layers to go over it. It could also be that those excessive wardrobe choices were never meant to be part of the same ensemble. Perhaps I’ll never know.
What I do know is that this hodge-podge approach is not new to the world of Contact Center metrics. One might even say it was “in style.” For example, it’s not uncommon for me to visit a Contact Center and while discussing performance a neatly stapled packet of daily reports comes out. These packets vary in thickness, but they’re almost always topped off by some universal view that has an extensive array of every metric known to mankind jammed in small font on the top sheet, or better yet on a TV screen hovering over everyone’s heads.
Trying to pull meaning out of the extensive array of numbers is definitely challenging on the eyes, and trying to see the relationship between the metrics is even worse. I had a flashback to that mannequin and had to ask, “Do those even go together?”
What feeds this madness? Usually my experience is there’s a Contact Center executive with a healthy appetite for data but very little time to consider it, so this “jam it all on one view” approach evolves to try to feed both needs. Those who venture beyond the first view of the report get treated to even deeper dives in to the metrics. While I have to admit I do see real value in these reports, the percentage of people who actually LOOK further in to these metrics can be counted on one hand.
So what is a Contact Center Reporting Analyst to do? Continue to lay out a banquet of data in a single view, or trim the menu and focus on more meaningful consumption one meal at a time?
How do you handle the need to report on and display a wide variety of metrics in your contact center?
What is your approach to representing the extensive array of metrics available in Contact Centers today?
by Jane Hendricks on July 12th, 2013
If big data is beginning to feel like a big headache, you’re not alone. Over half of contact center decision makers say that they struggle with data challenges. Much of this is due to the fact that many of us simply don’t know how to manage the data we have.
In the contact center, mastering big data can provide amazing value—from $500 to $2,000 per agent, per year.
With the right tools, analytics can tame big data to reveal insights to management faster. It can also help make workflows and business processes smarter and more adaptive. The key to getting value out of big data is to make big data dimensions work for you:
- Rather than worrying about data velocity, establish and measure to multi-dimensional KPIs to accelerate decision velocity.
- Place volume secondary to relevance when it comes to accessing and having an in-depth understanding of the data you need
- Transform the variety of data they have into useful breadths of knowledge that can be turned into valuable metrics
It is commonly recognized that 80% of an organization’s data is unstructured. That unstructured data is often that which contains the richest insight into customers need and operational execution. For the contact center, recordings and agent desktop activities remain a vast, untapped data store of insight.
Speech analytics helps companies structure the concepts that are occurring within customer conversations. New data points that are uncovered can then be integrated with other performance and quality metrics. Desktop analytics – often part of back office optimization solutions — capture not only process behavior but also how applications are being utilized so companies can benchmark and track process performance as well as compliance.
Behind all of these measurements, performance management can turn these metrics into meaningful insights that allow companies to create multi-dimensional KPIs, align personal activities to organizational initiatives, and optimize coaching sessions to drive corrective action.
In the contact center, big data has the ability to turn every customer interaction into a productive one. How is your company using big data to inform decisions and provide better customer service?
by Paul Stockford, Chief Analyst, Saddletree Research on March 4th, 2013
Predicting industry trends is a practice about as old as the contact center industry itself. Conventional wisdom tells us that the best way to spot or predict trends is to talk to a bunch of different solutions providers and see what’s flying off the shelves, then extrapolate that trend into the future. At Saddletree Research we take a decidedly different approach. Instead of asking vendors what they’re making or what they think will sell, we ask buyers what they’re buying.
We consider our demand-based forecasting to be superior to supply-based forecasting and a more accurate means of gaining insight into the mindset of the industry. With that qualification in mind, here are the five mega-trends that we believe will have a significant impact on the industry this year:
- Big Data
- Real-Time Analytics
- Human Capital Management
- Shifting Purchase Influencers
The trend toward Big Data speaks for itself. With so much structured and unstructured data residing in the contact center combined with the advent of reasonable analytics solutions there is no doubt in my mind that Big Data will be a big trend this year. This was further verified by the demand for analytics solutions, which heads the list of the top contact center solutions that will be evaluated for purchase this year.
Mobility is another intuitive trend given the fact that there are 330 million mobile devices in use in our country of 315 million people, and over half of these devices are smart phones or tablets. Our user surveys revealed that mobility is a customer service issue that is worthy of investment in 2013. Our year-end research verified that over 40 percent of contact centers in the U.S. are now supporting both iPhone and Android mobile devices.
Real-time analytics will be driven by a combination of customer experience, regulatory compliance and remote agent management objectives. 2012 research revealed that the majority of performance analytics users are dissatisfied to some degree with the time it takes to get performance metrics to supervisors and agents. Real-time analytics addresses this shortcoming.
In addition, real-time analytics enables the management of remote agents as the at-home agent movement gains industry momentum in 2013. 2012 research showed that 53 percent of U.S. contact centers have some percentage of their workforce working from home. About 70 percent of these contact centers intend to increase their at-home agent population in 2013. Real-time analytics offers the only timely means of managing this remote workforce.
Human Capital Management will also be driven by the at-home agent movement as companies attempt to recruit and hire agents with the appropriate attitudes and attributes that will make them successful remote workers. Specialized needs of large outsourcers, who have to hire large numbers of employees in a short period of time and at a reasonable cost in order to compete with offshore outsourcers, will also contribute to this trend. Year-end survey results show that 33 percent of the market will be evaluating hiring software for purchase during 2013.
Shifting purchase influencers speak to the fact that price is not as influential in the purchase process as it used to be. Every year since 2008 we’ve asked participants in our year-end user survey to choose the two top factors that influence their technology purchase decisions. Return on Investment (ROI) and Price always top the list and they did this year too, but nipping on the heels of Price are such factors as company reputation, prior relationship with the vendor and trust in the brand name. This indicates the return of intangible purchase influencers in the post-recession contact center industry. It also means that the lowest price won’t always win the deal.
It is clear that analytics will be an important industry growth driver in 2013, but it will not be dominant. This year’s mega-trends indicate an overall focus on efficiency, most likely driven by conservative management in the post-recession era.
If you’re interested in learning more about the major technology trends shaping communications and collaboration, join Aspect at Enterprise Connect, March 18-20. Billed as the industry’s premier event for systems, software, services and applications for enterprise communications and collaboration, we’re looking forward to three days of high-level, forward-thinking, relevant and reliable information presented by thought leaders in keynotes, workshops and breakout sessions. Come find us at booth 1137!
Sign up now to view a demo of Aspect’s next-generation solutions and be automatically entered to win a Microsoft Surface!
by David Harper on February 8th, 2013
Speaking of “big data,” this is a term that’s becoming more and more common in the workplace as business continue to generate massive amounts of information and knowledge. What isn’t very clear at this point is what exactly big data is and how it can be leveraged. Depending on whom you talk to, big data has a few different meanings. If you look up what it means to IBM, Oracle, SAP, and others you will see a different definition. Microsoft isn’t any different when it comes to this dilemma.
What most people can agree on is that it is defined by three (ok, sometimes five, see – they can’t even agree upon that) V’s:
- Volume – how much data are we capturing
- Velocity – how fast are our data volumes growing (exponentially vs. linear)
- Variety – structured vs. semi-structured vs. unstructured
Now it’s clear as day right?! Many organizations are still in the “Web 2.0” world. This means that we have moved beyond capturing information about payroll or our sales pipeline, and are gathering information around search marketing, web logs, and eCommerce. The world of big data rests just beyond that. Information such as click-stream analysis, log files, weather, text/image data where the only rule is that there are no rules. The trick to be able to gain insights from this data is to find the meaningful data points and add structure to them so it may be digested by our standard BI tools.
The current task at hand is finding customer scenarios that lend themselves to this sort of data exploration:
- IT Infrastructure
- Traffic flow optimization
- Weather forecasting
- Smart meter monitoring
There are generally about 10 to 15 common scenarios that can be addressed readily by big data solutions. The better question is what’s next. A Fortune 1000 executive was recently overheard saying, “Big Data reminds me of ‘Cloud’ five years ago, nobody knows what it is, but everybody wants one.” This person is absolutely right – I can’t tell you want I want, but I will know it when I see it.
What is your take on big data? Is your company delving into this new world? Tell your take in the comments.
Dave Harper, Director of Aspect Analytics National Practice, speaks nationally on industry technology trnds and at many events in all vertical markets. Dave continues to serve as the technical architect on many of Aspect’s large-scale analytics projects. He has more than 12 years of experience developing and implementing solutions for all types of organizations, with significant experience in creating leading-edge Microsoft Business Intelligence solutions.
Read more about big data:
- What Big Data Means to the Customer Experience
- Re-visiting a Highlight of Aspect Customer Experience
- Big Data and the Contact Center