Building a Case for Knowledge Management: Information is Everywhere, But Not Always Available When You Need It

Knowledge is a process of piling up facts; wisdom lies in their simplification.” Martin H. Fischer, German-born American physician and author

We’ve all experienced it: you’re frantically searching for a certain bit of important information, which you can’t locate in the FAQs or find anywhere else on a company’s website. So, you call into the contact center or initiate an online chat. You want to believe that the agent you encounter has the knowledge and experience to provide the answer to resolve your issue quickly and accurately. Sadly, that is not always a realistic expectation.

In a recent survey, Forrester Research asked 5000 customers “What creates the greatest pain when you contact a business for customer service?” The response was resoundingly clear: the lack of knowledge and consistency of information on the part of agents, followed by the difficulty of finding relevant answers on company websites. The feedback read like a litany of customer discontent:

  • Different customer service agents give different answers (41%)
  • Customer service agents don’t know the answer (34%)
  • Can’t find correct answers on website (31%)

This disconnect has contributed to a 3-year decline in the perception of customer service. In reviewing the Forrester CX Index for 2016, 2017, and 2018, no single company offered “excellent” customer service in 2017 and 2018, and the number of companies offering “good” customer service declined from 17% in 2016 to 15% in 2018.

While this seems like a dismal picture, it is certainly far from hopeless. Most businesses have no shortage of information, but have so much content scattered in different places that it is often nearly impossible to find what is needed in the moment. The” magic bullet” to make information immediately accessible to agents has been around for years, but for some reason, knowledge Management (KM) systems have not yet been adapted by the majority of companies.

By capturing, organizing, and analyzing data for shared intelligence and improved performance through best practice implementation, effective contact center KM solutions can dramatically enhance customer support and agent productivity while reducing training time and customer frustration. Having the right KM system in place enables wider sharing of information across the entire organization, spurs operational efficiencies in rapidly communicating accurate intelligence, and helps ensure consistency across an omnichannel implementation.

But building, implementing and maintaining a successful KM program can be a daunting process. A business needs to determine the right procedures to setting up a single source of the truth for all users across all channels and institute a reliable method of measuring its effectiveness at every stage.

Discover how your company can take the right approach to get the ball rolling and put your program on a trajectory to success. Listen to “The 10 Steps to Building a KM Program that Works” presented by Verint on Thursday, September 12, 2019 on CRMXchange. If you can’t attend the live webcast, you can download it 24 hours after it is completed.

 

It’s So Random: Changing the Culture of ‘Who’s Up Next’ with Intelligent Call Routing

With comprehensive information at everyone’s fingertips, few people now book a hotel room in a far-off location, make a reservation in an unfamiliar restaurant or hire an unknown contractor without carefully reviewing all relevant feedback. For the most part, businesses are even more cautious about making moves, industriously uncovering everything about prospective employees during the hiring process, and thoroughly investigating every angle of any potential partnership, investment strategy or technology purchase.

Yet, with all the rich data resources available to them, most organizations leave one crucial business process almost entirely to chance: which front-line representative takes the lead in customer interactions. Startlingly, 95 – 99% of companies still randomly route customer calls to the next available agent. Of course, it doesn’t have to be that way. Intelligent routing systems—with the capability to identify the caller and the reason for the call to assign the customer to the agent best skilled to handle the specific inquiry— have been around for years and are constantly becoming more efficient and affordable.

Rather than adhering to the circuitous procedure of using interactive voice recording (IVR) to send the customer to the most appropriate department or to an initial operator who will forward the call, intelligent call routing totally streamlines the process. It taps directly into customer records to retrieve information about the caller based on previous interactions and instantly directs the call to whom it judges to be the most qualified agent to handle the issue. In making split-second routing determinations, such systems not only take into account an agent’s track record, training and skills, but also consider caller priority, long-term customer value and more. Sometimes, the best responder for a specific call may already be engaged in another ongoing conversation that started only a few minutes earlier. Depending on how long the caller may have to wait, how wait time impacts that individual’s satisfaction and the skill level of others available, intelligent call routing decides to either have the caller wait or assign them to the next best agent.

With the increasing volume of available data on customer history and improved knowledge of agent capabilities, the traditional legacy routing strategy is evolving to become more intelligent, personalized, and able to effect specific improvements in a company’s metrics. Integrations now enable the use of data gleaned from previous interactions to provide insight into a customer’s personality and behavioral characteristics. By applying this knowledge, companies can gauge their customer’s communication preferences–intelligent routing can go beyond calls, helping to shape better outcomes on email, chat or messaging channels– and deliver the optimal experience.

Learn how your company can use this vital and improving technology to both reduce customer effort and create more personalized connections. Listen to a complimentary webcast “How Intelligent Call Routing Can Deliver Business Results,” presented by NICE Nexidia.

70% of U.S. Employees Hold Positive View of Artificial Intelligence in the Workplace Today

Despite recent doom-and-gloom anecdotal reporting, a nationwide survey of 1,001 workers in the United States (U.S.) finds that 70% have an upbeat attitude toward new workplace technologies involving artificial intelligence (AI), such as chatbots, robots and augmented reality. Only 5% say they dislike new technology for putting their jobs at risk today. In fact, 32% of U.S. respondents feel AI will have a positive impact on their job in the next five years, increasing from 26% today. Just 19% of those surveyed express fear that AI/bots could swallow their jobs within the next decade.

These findings stem from new research by Genesys® (www.genesys.com) into the attitudes of employed Americans regarding the rising adoption of AI in the workplace. Genesys conducted an identical survey in six countries — the U.S., Germany, the United Kingdom, Japan, Australia, and New Zealand — for a total of 4,207 participants.

The picture isn’t all rosy, however. While 75% of Americans surveyed say they are “rarely” or “never” threatened by new technology at work, one quarter do feel unsettled by it. Happily, only 4% “always” feel threatened. This is fairly similar to respondents in Germany, the U.K., Australia, and New Zealand, but in Japan that figure jumps to 12%.

Is AI a Friend or Future “Frenemy”?

While 52% of U.S. workers surveyed say AI has not yet affected their jobs, that number falls to 29% when asked about a five-year timeframe, with expectations for an increase in both positive and negative effects. Part of the reason for the low percentage of AI’s current impact? It’s not as ubiquitous in the workplace as many people would believe. Among U.S. respondents, 68% say they are not yet using tools that leverage AI; surprisingly, there is not a noteworthy difference between large and small companies.

Survey results also shed light on AI’s influence on employee social interaction, ethics and upskilling, with worker attitudes varying according to age, company size, job status and job function. The overall impression? Employees have a generally positive view of technology now, but are less certain if technology enabled with AI will be their friendly co-worker in the future, or a “frenemy.”

“The survey findings substantiate a long-held Genesys belief that a blended approach to AI is best in customer contact centers as well as the workplace in general,” said Merijn te Booij, chief marketing officer for Genesys.

“Some jobs will evolve as human work combines with the capabilities of AI. The key for organizations adopting this intelligent technology is to help employees understand its potential to make their jobs more fulfilling by taking the mundane, easily automated tasks off their plates. This opens the door for more employees to apply skills AI just can’t replace – like creativity, leadership and empathy.”

Considering 27% of Americans say they simply cannot predict the impact of AI on their jobs five years down the road, and only half feel they have the skills to compete effectively, it’s increasingly important for companies to closely monitor the pace of AI adoption and employee training programs to address it.

A few additional U.S. findings related to overall attitudes toward AI include:

  • Two-thirds (66%) of the U.S. cohort say technology makes them more efficient in their jobs. This response is exactly the same across the three age ranges surveyed.
  • 8% of U.S. employees say they dislike new workplace technology such as AI and bots because it takes away their easy tasks.
  • More part-time U.S. employees (25%) fear AI will take their jobs within 10 years than do full-time workers (18%).
  • Surprisingly, exactly twice as many (26%) of the U.S. employees in the youngest cohort (ages 18-38) fear replacement by AI within the next decade as do their over-55 co-workers (13%).
  • Nearly 70% of U.S. employees trust their employers to use AI in an ethical way.

Survey Methodology and Participants

Within the U.S., a total of 1,001 adults completed the online survey in April. Respondents were evenly divided into three age ranges: 18-38, 39-54, 55-73, with women accounting for 65% and men 35%; less than 1% did not categorize by gender.

Approximately 80% of those surveyed have full-time employee status with the remaining 20% working part-time. Respondents came from seven categories of company sizes, with a total of 42% employed in companies of fewer than 250 employees.

While U.S. survey respondents work in a wide variety of industries, 77% fell into one of 11 functional job categories: Administrative, Assembly Line/Manufacturing, Customer Service/Retail, Doctor/Nurse/Caregiver, Education/Training, Finance/Accounting, Food Service, Human Resources, Marketing/Inside Sales, Media, and Driver/Transportation Provider. The remaining 23% fell into an “Other” job category.

For a copy of the full survey data, please contact genesys@sterlingpr.com

Seven “Must Have” Capabilities for Customer Service Applications

Written by Basabdutta Chakraborty

In the era of technological advancement, customers have endless choices of what products and services to purchase. To capture and maintain a higher market share require companies to create a meaningful corporate distinction. One way to accomplish this goal is by delivering a superior customer experience—one that capitalizes on the first impression about the brand and carries through on every interaction thereafter. To bring the best customer experience to life, consider these seven essential features:

  1. Omni-channel – Most customers seek the ability to engage from any channel of their choice from any device—email, telephone, chat, SMS, web, social or mobile app. To support a consistent experience across all the channels in the user’s journey, agents need to be able to respond to any inbound voice/text inquiries seamlessly. Therefore, to increase the productivity of an agent, a call center software needs to include a single user interface, where all inbound messages are tracked as tickets with contexts.
  2. Efficient ticket management – In order to resolve customers’ issues and queries efficiently and effectively, there are several factors to address:
    • Context and History. For each ticket, customer information and past ticket history should be available to the agent with relevant context.
    • Categorizing. Based on the ticket type, agents need to capture specific information, and perform grouping, merging, linking, cloning, and filtering.
    • Intelligent routing. Automated workflow can be configured to assign and route inbound tickets based on the agent’s skill, knowledge and workload.
    • Knowledgebase support. Depending on the issue type, relevant knowledge articles should be automatically shared with agents to provide better assistance.
    • Timely alerts. Based on Service Level Agreements (SLA) priority, agents and their supervisors should be notified on time.
    • Collaboration. Often complex issues require inputs from multiple agents. A live discussion forum can help them to collaborate instantly.
  3. Unified interface – While engaged in an interaction with a customer, an agent might require navigating through multiple systems. To minimize the screen switches, a unified user interface brings relevant applications to a single desktop. In this way, the agent can focus on the customer as opposed to the complexity of multiple systems.
  4. Self-service and chat-bots – In many cases, today’s customers prefer to resolve their issues themselves. Self-service options and capabilities empower customers by providing them with online searchable knowledge articles, FAQs, and discussion forums. Chatbots, on the other hand, help customers with informational and transactional inquires in a personalized fashion. Customers, however, should still have the ability to escalate to a live agent seamlessly in case of a complex inquiry.
  5. Personalized recommendations – Customers really appreciate it when they feel a representative is interested in them. The system should be capable of displaying personalized, targeted messages to the CSRs to assist them to develop a deeper bond. For example, while engaged in a conversation with a customer, if a CSR proactively says, “Ms. Smith, your credit card is going to expire in a month” or “your renewal is pending,” these personalized outreaches help build appreciative customers and long-term relationships.
  6. Predictive analytics – Knowing the next move of customers, ahead of time, is becoming increasingly more critical. Predictive analytics is the tool that measures customer satisfaction and determines future trends by analyzing past transactions and call history. Thus, businesses can identify potential threats in a customer’s journey and can take appropriate corrective actions. Similarly, the huge amount of call center data, such as average call handle time, ticket volume, etc. can predict if any agent’s performance needs to be improved or any additional staffing is needed or if the system’s performance should be enhanced.
  7. Cloud based application – Given there is a steady internet connection, a cloud-based customer service platform is undeniably a smarter choice than an on-site one for the following reasons:
    • It is easy to scale. Adding agents is just a matter of subscription, and so is spinning a new instance. It’s just a few clicks, and no infrastructure changes are required.
    • It is flexible. Agents can assist customers remotely, from any internet-connected device. Admins can make configuration changes and publish real-time.
    • It performs well and is stable. Most of the cloud providers ensures 99 percent+ uptime.
    • It saves infrastructure and maintenance costs. No hardware equipment is required. Patch, data backup-recovery are taken care of by the provider. It is secure. Dealing with personalized information of customers requires stronger data security and privacy, which is safeguarded by cloud applications.

    Key contributor to business growth – Customer experience is an important contributor to business growth. When done well, companies earn the trust and loyalty of their customers. Technology can provide the features that enable CSRs to do their job efficiently and effectively. The real success, however, comes from the commitment of the top executives to make customer experience excellence a key corporate initiative. When this happens, business and IT teams align on the strategy while defining the unique business and technical needs of their organizations. Continuous feedback from CSRs is a critical input in this process. Together they can build a better customer experience—one that enables them to stand out in the marketplace.

In the era of technological advancement, customers have endless choices of what products and services to purchase. To capture and maintain a higher market share require companies to create a meaningful corporate distinction. One way to accomplish this goal is by delivering a superior customer experience—one that capitalizes on the first impression about the brand and carries through on every interaction thereafter. To bring the best customer experience to life, consider these seven essential features:

  1. Omni-channel – Most customers seek the ability to engage from any channel of their choice from any device—email, telephone, chat, SMS, web, social or mobile app. To support a consistent experience across all the channels in the user’s journey, agents need to be able to respond to any inbound voice/text inquiries seamlessly. Therefore, to increase the productivity of an agent, a call center software needs to include a single user interface, where all inbound messages are tracked as tickets with contexts.
  2. Efficient ticket management – In order to resolve customers’ issues and queries efficiently and effectively, there are several factors to address:
    • Context and History. For each ticket, customer information and past ticket history should be available to the agent with relevant context.
    • Categorizing. Based on the ticket type, agents need to capture specific information, and perform grouping, merging, linking, cloning, and filtering.
    • Intelligent routing. Automated workflow can be configured to assign and route inbound tickets based on the agent’s skill, knowledge and workload.
    • Knowledgebase support. Depending on the issue type, relevant knowledge articles should be automatically shared with agents to provide better assistance.
    • Timely alerts. Based on Service Level Agreements (SLA) priority, agents and their supervisors should be notified on time.
    • Collaboration. Often complex issues require inputs from multiple agents. A live discussion forum can help them to collaborate instantly.
  3. Unified interface – While engaged in an interaction with a customer, an agent might require navigating through multiple systems. To minimize the screen switches, a unified user interface brings relevant applications to a single desktop. In this way, the agent can focus on the customer as opposed to the complexity of multiple systems.
  4. Self-service and chat-bots – In many cases, today’s customers prefer to resolve their issues themselves. Self-service options and capabilities empower customers by providing them with online searchable knowledge articles, FAQs, and discussion forums. Chatbots, on the other hand, help customers with informational and transactional inquires in a personalized fashion. Customers, however, should still have the ability to escalate to a live agent seamlessly in case of a complex inquiry.
  5. Personalized recommendations – Customers really appreciate it when they feel a representative is interested in them. The system should be capable of displaying personalized, targeted messages to the CSRs to assist them to develop a deeper bond. For example, while engaged in a conversation with a customer, if a CSR proactively says, “Ms. Smith, your credit card is going to expire in a month” or “your renewal is pending,” these personalized outreaches help build appreciative customers and long-term relationships.
  6. Predictive analytics – Knowing the next move of customers, ahead of time, is becoming increasingly more critical. Predictive analytics is the tool that measures customer satisfaction and determines future trends by analyzing past transactions and call history. Thus, businesses can identify potential threats in a customer’s journey and can take appropriate corrective actions. Similarly, the huge amount of call center data, such as average call handle time, ticket volume, etc. can predict if any agent’s performance needs to be improved or any additional staffing is needed or if the system’s performance should be enhanced.
  7. Cloud based application – Given there is a steady internet connection, a cloud-based customer service platform is undeniably a smarter choice than an on-site one for the following reasons:
    • It is easy to scale. Adding agents is just a matter of subscription, and so is spinning a new instance. It’s just a few clicks, and no infrastructure changes are required.
    • It is flexible. Agents can assist customers remotely, from any internet-connected device. Admins can make configuration changes and publish real-time.
    • It performs well and is stable. Most of the cloud providers ensures 99 percent+ uptime.
    • It saves infrastructure and maintenance costs. No hardware equipment is required. Patch, data backup-recovery are taken care of by the provider. It is secure. Dealing with personalized information of customers requires stronger data security and privacy, which is safeguarded by cloud applications.

    Key contributor to business growth – Customer experience is an important contributor to business growth. When done well, companies earn the trust and loyalty of their customers. Technology can provide the features that enable CSRs to do their job efficiently and effectively. The real success, however, comes from the commitment of the top executives to make customer experience excellence a key corporate initiative. When this happens, business and IT teams align on the strategy while defining the unique business and technical needs of their organizations. Continuous feedback from CSRs is a critical input in this process. Together they can build a better customer experience—one that enables them to stand out in the marketplace.

New CX Metrics for Today’s Digital World

Consumers want omnichannel but conversations and measurements haven’t kept pace by Ted Hunting, Bright Pattern

The customer experience (CX) is increasingly digital with over 95% of customer interactions starting on websites. Forrester research shows that customers are using and hopping between an increasing number of media channels, such as chat, text, messengers, and of course, traditional channels like email and voice calls. Even though “omnichannel” is still an industry buzzword and there has been a dramatic shift to new channels, fewer than 20% of companies offer a seamless, continuous conversation across channels. Ninety percent of consumers want this type of effortless customer experience without friction or silos, but companies are failing to deliver.

Similar to the gap between customers’ expectation for omnichannel and companies’ ability to offer it, metrics for customer experience have also remained siloed and focused all too often on voice. Traditional CX metrics like Average Handle Time are still valid but today’s digital world requires new metrics. In this blog, I will discuss and propose some new metrics as well as some keys to measuring them.

Key #1: To improve the journey, you must see and measure the journey.

Recent metrics that attempt to move beyond siloed metrics for the voice-only world include Reichheld’s Net Promoter Score (NPS), Customer Satisfaction (CSAT), and Sentiment, which rate overall how customers feel about a company and their customer experience.

To improve the customer experience, I recommend using NPS, CSAT, and Sentiment as guiding lights for three new metrics: NPSJT,  and CSATJT, and SentimentJT . These metrics measure NPS, CSAT, and Sentiment by journey type (JT). For example, banks may want to measure CSAT, NPS, or Sentiment by journey type—think mortgages, credit cards, or home equity line of credit. Likewise, retailers may want to measure NPS by journey types like TV sales versus refrigerator sales. By measuring at the journey level, you can improve the quality of each journey type.

CSAT is typically obtained by a simple survey (e.g., rate your experience by giving 1–5 stars) at the end of the given customer’s journey. Sentiment can be measured by an average sentiment score or ending sentiment score for each journey using AI measurements.

Tip: Add new metrics for omnichannel digital CX: NPSJT , CSATJT , and SentimentJT .

Key #2: To improve channel CX and customer segment CX, institute quality measurements at the channel level and measure at the customer level.

It is also important to measure CSAT, NPS, and Sentiment at the channel level and customer level. To do that, I propose using these new metrics for channel type (C): NPSC, CSATC, and SentimentC . These new metrics measure the CSAT, NPS or sentiment on each channel, letting you see which channels are performing well or poorly. They require a simple survey at the end of all interactions within the larger customer journey. If you can see which channel is performing poorly (e.g., chatbots), you can improve the channels and smooth out any points of friction in the customer’s journey. A Bright Pattern survey of consumers showed that NPS scores for bots, text messaging, IVRs, email, and social interactions ranked low, showing common areas along the customer journey that companies should improve.

To measure CX at the customer level, I propose these new metrics for key customer segments (CS): NPSCS, CSATCS, and SentimentCS. Similarly you can look at CSAT, NPS or Sentiment by customer segment, such as gold customers, bronze customers, and new prospects. This provides you with the opportunity to provide specialized care to your best customers by personalizing their experience.

Tip: Add new metrics needed for Digital Omnichannel CX? NPSC and CSATC and SentimentC for channel and NPSCS and CSATCS and and SentimentCS for customer segment

Key #3: Enable omnichannel conversations and omnichannel quality assurance measurements via a platform approach.

So how to get started? First and foremost, to offer a seamless conversation across channels while measuring these omnichannel conversations to improve quality requires that you take a platform approach. All channels must be native in the platform so that a single conversation can be offered to your customers and all interactions can be measured from a quality management standpoint. An end-to-end omnichannel CX platform with omnichannel conversation capability and omnichannel quality management embedded within the platform is the key to easily creating and measuring great omnichannel customer journeys. Contrast this to bolt-on systems that are expensive and time-consuming to implement with siloed conversations and data.

Agent churn: It’s not you, it’s your employee engagement strategy

Jeff Gallino, CTO and founder of CallMiner

It’s no secret that contact centers are infamous for their high turnover rates, which average 45 percent year-over-year—more than double the average for all U.S. occupations. What most companies don’t realize, however, is that this doesn’t have to be the status quo. Identifying the signs an agent is about to check out and having solutions in place to change the outcome can dramatically reduce agent churn well before they decide to give their notice.

If retention isn’t motivation enough, research shows that an astonishing 77 percent of employees worldwide are not engaged, which, according to Gallup, can cost upwards of $605 billion in lost productivity per year. There’s incredible value in spotting non-engagement signs and addressing the lack of productivity that often lead to agent turnover early. This can ensure strong employee engagement and stop the turnover cycle. Not only will it save billions in lost revenue, it will promote better customer experiences through an organization’s No. 1 advocate—its employees.

Warning Sign 1: They go into silent mode

One of the primary indicators of an unengaged employee is silence. Silence is commonly caused by a lack of agent training, but this isn’t only applicable immediately after onboarding. Agents require extensive knowledge of your company’s products and services; however, many employees miss out on new product information because organizations neglect to offer continual education programs.

Employee silence can also happen outside of customer interactions, as managers of unengaged agents tend to notice an increase in the amount of time between each call. Although this doesn’t usually stem from a lack of company knowledge, it’s a telltale sign an employee is experiencing a lack of motivation. Distant employees are comfortable with doing the bare minimum to get by and will likely keep their heads down, and calls quietly recording, to purposely limit the number of customers they interact with.

Warning Sign 2: Under (but not terrible) performance

Decreased performance in areas such as average handle time (AHT), call volume, and following a script could all point to a lack of engagement that, if not fairly addressed, can lead to lower NPS scores, turnover, and even compliance risks.

Sometimes, however, quantifiable performance metrics aren’t the sole indicator of an agent’s performance—as agents aren’t at-fault for many of the disruptions that happen during the call. Companies need to take training, tools and technical factors into consideration when it comes to gaps in an agent’s performance and use contextualized scoring methods to accurately and thoroughly understand where performance issues are occurring and the root cause.
Warning Sign 3: Inconsistent feedback on their work

According to research by Gallup, less than 21 percent of employees strongly agree their employee implements fair evaluation processes. Contact center agents handle dozens of calls per day, but many outbound surveys and manual quality management reviews only account for three to five percent of an agent’s interactions—leading to ill-informed assessments of their overall performance.

In addition to being inaccurate and irregular, many legacy feedback systems are impersonal. Call center feedback usually only involves reprimanding, despite the employee’s desire to be recognized for exceptional service. The lack of effort put into celebrating successes usually causes agents to feel unappreciated and less likely to advocate for the business.

How to Stop the Cycle

Proper training—during and after onboarding: Before sending your agent out on their own, how do you know you’ve given them the proper training to handle the influx of problems they’ll face out on the floor? To keep up with the fast-paced environment of the contact center, they need to stay informed, especially if your products and services are constantly evolving. Each one of your employees is unique and despite what’s suggested by legacy employee education programs—their training processes should be as well. Speech analytics data can help managers offer personalized training programs in accordance with agents’ specific needs, even after onboarding.

Tools to optimize performance: Aside from training, contact center operators need to ask themselves whether their agents have the resources they need to succeed. While two-thirds of customers dial in with a problem, some caused by lack of self-serving options on other channels, they expect your agent to be able to solve, lack of resources is one of the biggest factors leading to job-related stress. It’s impossible to guide each of your representatives through every single interaction—but tools and customer engagement analytics software can take information in real time and apply historical data to provide your agent with better insight and guide them through the call based on the context of the conversation.

Real-time feedback: Agents should always know where they stand when it comes to their performance. A discussion a week, a month, or a year later about a specific interaction with a customer will not help anyone succeed. Having an analytics tool removes any sense of unfairness that’s usually associated with random selection by providing an inclusive and holistic view of your caller engagement data, ensuring a stronger voice of your employee. It also helps with coaching by automatically scoring 100 percent of your agents’ customer interactions to pinpoint the exact areas they need to both improve customer experiences in real-time and add business value in the long run.

While employee turnover is one of the biggest problems companies face today, employee engagement is just as impactful to your business’s bottom line, as those with highly-engaged workforces outperform their peers by nearly 150 percent. All problems associated with the warning signs of an unengaged employee point to a similar source—the company’s inability to fully understand the needs of their employees from both a personal and professional perspective. Similar to how analytics and artificial intelligence work to strengthen customer loyalty, these tools and concepts can help personalize your organization’s approach to agent management—offering a fully-developed employee engagement strategy that involves critical coaching and feedback procedures. In doing so, companies can foster a positive work culture and keep employees from feeling as though they are ‘just another number’.

CX Transformation Benchmark Study from NICE inContact

The 2019 NICE inContact Customer Experience (CX) Transformation Benchmark gauges the changing attitudes of business contact center leaders and consumers in key areas of customer experience. The report compares global findings to the 2018 consumer wave of the study, and includes year-over-year findings for the US. Results reveal that businesses are confident in artificial intelligence’s (AI’s) role in delivering exceptional customer service experiences, but they overrate their own CX performance. Compared to consumers, businesses overreach when estimating their own net promoter scores (NPS), overrate their own CX success, and underperform when it comes to delivering seamless omnichannel experiences.

The results reveal that businesses are confident in artificial intelligence’s (AI’s) role in delivering exceptional customer service experiences, but they overrate their own CX performance. A few of the core findings from NICE inContact’s CX Transformation Benchmark include:

  1. Significantly more US businesses now offer automated assistants / chatbots online, at 54% compared to 44% the prior year.
  2. 63% of contact center leaders agree that chatbots and virtual assistants make it easier for consumers to get their issues resolved
  3. While 93% of businesses agree that consumers expect companies to provide a seamless experience when moving between channels, only 24% of businesses globally give themselves an excellent rating on allowing consumers to switch seamlessly between methods of communication.

To read more: http://get.niceincontact.com/Q219-CX-Transformation-Benchmark-Business-Wave.html

 

CGS Survey Discovers that Security and Privacy are Top Concerns for Customer Service Interactions

CGS, a global provider of business applications, enterprise learning and outsourcing services, discusses its findings from its 2019 CGS Customer Service Security and Compliance Survey. The results showed that despite demands for faster, more personalized interactions, consumers have strong opinions when it comes to their security and privacy rights. With reports from the latest Edelman Trust Barometer showing that only 49 percent of the U.S. general population trusts businesses (down from 52 percent in 2017), companies must work to strike a balance between providing a tailored customer experience and respecting their customers’ data preferences.

CGS surveyed more than 500 U.S. consumers to assess their preferences and concerns around customer service interactions. The survey looked at what types of information individuals are willing to share, how they are willing to share (e.g., through a human agent, social media, chatbot) and any apprehensions they have with sharing their personal data. Key findings from the survey include:

Automated Technology Still Lacks Consumer Trust 
Despite the rapid adoption of mobile and artificial intelligence (AI) technology, almost 60 percent of respondents still believe that phone interactions are the most secure customer service channel. In fact, more than two-thirds (68 percent) of respondents said they don’t trust automated technology with personal data including birthdates, account numbers and social security numbers. As more businesses adopt automated and AI-driven service solutions, they must be transparent about how customer data will be stored and managed to encourage consumer confidence in next-gen technology.   

Past Experiences with Data Exposures Leave Consumers Feeling Vulnerable 
Data breaches have become commonplace for many consumers: 63 percent of respondents reported receiving an alert that their personal data had potentially been exposed or breached. Such experiences are affecting future interactions. Nearly 70 percent of respondents said they are unlikely to return to a company that has exposed their personal information. With data exposures and breaches happening more frequently, companies must have a plan in place as to how they will notify customers if an incident occurs. Being completely prepared for data vulnerabilities may be impossible, but offering remediations and additional protections in the future could help rebuild consumer trust.

Consumers Consent to Providing Information – If They Trust the Brand 
Although consumers are looking for personalized interactions, they are wary of sharing their information with companies. When asked if they would give a company the authority to store their information for future interactions, only three percent of respondents said they would always give consent. More than half of the respondents (56 percent) would give consent if they trusted the brand, but 41 percent would never allow their information to be stored, citing security concerns.

Additionally, consumers are uncertain about how their data is currently being managed by companies. Only 15 percent of respondents felt that they have a clear understanding of what information is being stored from their interactions with companies. While personalized customer service interactions are essential to success, organizations must demonstrate respect for their customers’ data privacy preferences. This means being transparent with customers about how their data will be used and protected.

To view the findings, see the  infographic.

 

 

How Robotic Process Automation Makes Contact Centers More Efficient

Automation isn’t new. Technologies like Interactive Voice Response have been around for a long time. But while advancements like these have reduced costs for the contact center, they’ve also managed to annoy customers. In the case of IVR, callers often get stuck in menu loops or struggle with systems that don’t understand what they’re saying. Enter robotic process automation.

Robotic Process Automation and Artificial Intelligence

Contact centers are in the business of serving the customer, and in an effort to improve the customer experience, technologies are always emerging. Robotic process automation (RPA) is one of them, automating tasks and freeing up agents to personally handle complex issues. RPA uses Natural Language Processing, which is related to artificial intelligence, an even more advanced type of automation that can make human-like judgments about tasks.

Interactive Text Response for Customer Service

Interactive Text Response (ITR), more casually referred to as chatbots, goes hand-in-hand with the increasing popularity of messaging apps. Brands that want to improve the customer experience are making themselves available on chat – and it’s working. More than 70% of 1-800-Flowers’ chatbot orders come from first-time customers, and the company’s commitment to new tech has attracted tens of thousands of users. Chatbots are more effective than IVR because text input is easier for the system to understand than spoken language. AI can then be used to gain a deeper understanding of what the customer is saying, accounting for the different ways a customer may phrase a sentence or question.

Sample Phone Call with RPA

RPA can also be used with phone calls, not just chatbots. Here’s an example of how RPA can help with a live call:

  • Jane calls to speak with an agent.
  • Your RPA takes the call and authenticates Jane by confirming her account number and call-in PIN.
  • Your RPA analyzes Jane’s account and sees that she has an open ticket and that she’s just been on the website to look at the status.
  • Your RPA says something like, “I see that you have an open ticket with us. Is that the reason for your call?” Jane confirms that this is the reason for the call.
  • Jane is transferred to an appropriate live agent.

Contact center technology like RPA can help customers solve their issues more quickly, but it can also provide much-needed support to agents by making them more efficient.

How Will Contact Center Channels Change in 2019?

Customer-centric businesses are working harder than ever to support all of the channels that their customers want to use. That’s why 84% of companies who consider themselves to be customer-centric have a heavy focus on supporting mobile channels for a greater customer experience. COPC reported that mobile care increases by 41% in 2018 alone.

The results from the 2018-2019 ContactBabel Report, as shown, illustrate that as mobile becomes more widely used by end users, channels like email, telephone, letter, and fax are expected to decrease in interactions. The channel with the largest expected increase in interactions for 2019 is web chat, with 56% of survey respondents believing there will be an increase. Social media customer service and SMS followed with 46% and 36% expecting an increase in interactions.inbound channnels

Both the need to retain strong CX strategies around traditional channels like email, voice, and IVR, and the need to add new channels has companies wondering how to create and run a true omnichannel contact center that empowers agents and delights customers. The ContactBabel Omnichannel Report walks though more stats from their survey, which could help you in your omnichannel journey.

inbound calls 2019

With traditional channels like voice, email, and chat, as well as channels like SMS/text, video, in-app, social messengers, and bots, Bright Pattern is the only true omnichannel provider that can be turned on in just days!