Artificial Intelligence

Culture Wins Championships and Customer Loyalty

Every leader talks about strategy. But the best teams in the world start somewhere else.  They start with culture.  In this episode of the Etech Leadership & CX Podcast, well-known leadership expert Don Yaeger joins Etech leaders to explore what truly separates championship teams from average ones — whether in sports, business, or customer experience.  After spending decades studying high-performing teams, Don shares a powerful truth:  Great performance doesn’t begin with strategy. It begins with culture.  From the way leaders treat their teams to how organizations serve customers, culture influences every outcome. And when leaders get culture right, performance follows naturally.  About the Episode   What makes a team truly exceptional?  Is it talent? Strategy? Technology?  According to Don Yaeger, the difference between average teams and championship teams often comes down to one powerful cultural trait: truth-telling.  High-performing teams create environments where honest feedback is encouraged and shared for the good of the entire team. In these environments, people trust each other, improve faster, and perform at a higher level.  In this conversation, Don joins the Etech leadership team to discuss how leaders can build stronger cultures, inspire employees, and create customer experiences that stand out.  Don also shares real examples from sports teams, businesses, and leadership experiences that show how culture influences performance, accountability, and long-term success.  This Episode Answers the Following Questions and More   What cultural trait separates championship teams from average ones?  Why is truth-telling essential for high-performing teams?  How does internal team culture influence customer experience?  Why do great leaders focus on curiosity and understanding people?  How can leaders create environments where employees feel valued and motivated to perform their best?  Top Takeaways   Culture Drives Long-Term Success: Organizations may achieve short-term results with strategy alone, but sustainable success comes from strong cultures built on trust and accountability.  Truth-Telling Builds Stronger Teams: High-performing teams encourage honest feedback that helps individuals and the entire organization improve.  Employees Shape Customer Experience: Customers can feel the difference between organizations that simply talk about values and those that truly live them.  Curiosity Is a Leadership Superpower: Great leaders stay curious about their teams, their customers, and the challenges they face.  Purpose Inspires Performance: When people feel connected to something meaningful, they bring more energy, commitment, and creativity to their work.  Quotes from the Episode   “Culture makes all the money. You can have the greatest strategy in the world, but without the right culture, success won’t last.”  “The number one cultural trait of championship teams is truth-telling. People share honest feedback because they want the whole team to get better.”  “Customers experience what we do to and for each other internally. The way teams treat each other shows up in the customer experience.”  “People buy from people they like. And people like people who are like them.”  “If you want to be exceptional every day, you are defying human nature — because human nature is to be average.”  Meet the Leaders   Don Yaeger: Hall of Fame Speaker | 13-time New York Times Bestselling Author | Host of the Top-Rated Corporate Competitor Podcast  Melissa Wood: Dean of Leadership Development at Etech Global Services  Jim Iyoob: Chief Revenue Officer at Etech Global Services & President of ETSLabs  Kaylene Eckels: President of Etech Global Services  Watch Now: Learn How Championship Cultures Are Built  Discover how leaders can build stronger teams, inspire employees, and create better customer experiences by focusing on culture first.  Gain practical leadership insights from real-world experience and decades of studying high-performing organizations.  ▶️ Watch the full episode now  📢 Stay updated with more conversations on leadership, AI, and customer experience — Subscribe to the  Etech Leadership & CX Podcast. 

Why Culture Still Fails In The Age of AI And How Leaders Actually Change Behavior

Every organization talks about culture. Every leader talks about transformation. And now, everyone talks about AI.  Yet many contact centers still struggle with the same challenge:  Why doesn’t behavior change — even when technology, tools, and data clearly show what needs to happen?  In this episode of the Etech Leadership Table & CX Podcast, Jim Iyoob is joined by Simon Thomson, Relationship Director at Steps Drama, to explore why culture initiatives often fail and what truly drives sustainable behavior change in high-pressure environments.  This conversation moves beyond theory. It focuses on practical leadership realities, human psychology, and why development must go deeper than traditional training.  About the Episode   Technology evolves fast. Behavior change does not.  Simon shares powerful insights from over two decades of drama-based learning and organizational development, working with global enterprises, leadership teams, and thousands of frontline employees.  At the center of the discussion is a simple but transformative framework:  See It → Own It → Change It → Live It  Rather than starting with tools, models, or policies, real development begins when people clearly see their everyday reality — the pressures, conversations, emotional moments, and decision-making challenges they face daily.  Because people rarely change behavior based on instruction alone.  They change through experience, reflection, and self-awareness.  Why Behavior Change Is So Difficult    Many organizations invest heavily in training programs. But training does not always equal development.  This episode explores why traditional learning approaches often miss the mark:  • Asynchronous learning disconnected from real work • Over-reliance on checklists and compliance models • Lack of emotional preparation for real conversations • One-size-fits-all development strategies  Simon explains why experience-based learning creates stronger, longer-lasting change — especially in environments like contact centers, where employees handle complex human interactions every day.  Why This Conversation Matters Culture Cannot Be Trained — It Must Be Experienced  True culture change begins when employees recognize their own behaviors, challenges, and impact.  Training vs Development: A Critical Difference  Discover why information delivery alone rarely changes performance.  Leadership Alignment Drives Everything  Without visible leadership buy-in and role modeling, transformation efforts collapse.  Behavior Change Requires Repetition  Sustainable improvement happens through consistent reinforcement, not one-time events.  Human Connection Still Wins in the Age of AI  Technology supports performance but people drive experience.  What You’ll Learn   Why culture initiatives often fail despite strong strategies  How experience-based learning changes behavior more effectively  The See It → Own It → Change It → Live It framework  Why leadership role modeling is non-negotiable  How peer learning accelerates development  Why measurement must go beyond metrics  The power of success stories in driving change  Leadership Lessons for CX & Contact Center Leaders    This episode offers practical guidance for leaders navigating transformation:  Start with awareness, not instruction Involve frontline employees in change design Focus on development, not just training completion Reinforce behaviors consistently Align leadership actions with stated values Measure confidence, knowledge, and real impact Share real success stories across the organization  Because culture is not built through policies.  It is built through everyday behaviors. Meet the Experts   Simon Thomson – US Client Relationship Director, Steps Drama.  Jim Iyoob – Chief Revenue Officer at Etech Global Services & President of ETS Labs  Watch Now: Transform Culture Through Behavior  Learn why culture change fails and how leaders can create meaningful, lasting impact.  Gain practical insights on leadership alignment, employee development, and behavior transformation in the age of AI.  ▶️ Watch the full episode now  📢 Stay updated with more conversations on leadership, AI, and customer experience — Subscribe to the  Etech Leadership & CX Podcast. 

Proving Quality at Scale – The New Standard for CX Accountability

Every contact center talks about quality, but very few can actually prove it at scale.  Most organizations still rely on outdated QA models — small sample sizes, delayed feedback, subjective scoring, and dashboards overloaded with metrics that don’t change behavior. The result? Leaders struggle to show real accountability, agents feel coached too late, and customers experience inconsistency.  In this episode of the Etech Leadership & CX Podcast, Jim Iyoob is joined by Scott Thomas, AVP, Client Support at Cox Automotive Inc with over 30 years of contact center experience, and Manu Dwievedi to explore what CX accountability truly looks like in today’s high-volume, fast-moving environment.  This conversation goes beyond theory. It focuses on how modern CX leaders are replacing checkbox compliance with real insight — and building quality programs that support customers, employees, and the business at the same time.  About the Episode   This episode dives deep into how quality and compliance must evolve as contact centers scale.  Scott shares how traditional QA programs built around a handful of monitored calls — no longer reflect reality when organizations handle millions of customer interactions each year. Instead of focusing on whether agents checked the right boxes, today’s quality programs must surface behavioral insights, customer sentiment, and patterns that leaders can act on immediately.  The discussion also explores why timing matters. Delayed feedback doesn’t improve performance — it reinforces mistakes. Real-time visibility allows agents to course-correct quickly, supervisors to coach effectively, and leaders to spot systemic issues before they impact customers.  You’ll also hear how quality data, when analyzed correctly, becomes far more than a compliance tool. It turns into a business asset — helping product teams, operations, and leadership teams identify recurring customer pain points and improve the end-to-end experience.    Why This Conversation Matters   Quality at Scale Is No Longer Optional Monitoring a few calls isn’t enough. Learn why CX accountability today requires analyzing interactions at scale — without losing context or accuracy.  Less Metrics. More Impact. Discover why overloading agents with dozens of KPIs backfires — and how focusing on a few meaningful goals drives better behavior and outcomes.  Objective Feedback Beats Subjective Scoring Understand how removing bias from quality evaluation improves trust, coaching effectiveness, and performance.  AI That Supports Humans — Not Replaces Them See how AI can remove human error, connect siloed data, and surface insights — while still preserving the human touch customers expect.  What You’ll Learn   Why traditional QA models fail in modern contact centers  How to prove quality and compliance across millions of interactions  The difference between measuring activity and measuring outcomes  Why solving customer problems matters more than handle time  How AI enables objective evaluation and real-time coaching  How better quality programs improve both CX and EX  Career Growth, Engagement, and Retention    One of the most powerful moments in this episode focuses on employee development.  Scott explains how structured career progression — clear skill paths, continuous learning, and visible growth opportunities — has helped his organization dramatically reduce attrition, even in a high-pressure contact center environment.  Rather than locking agents into repetitive roles, this approach allows employees to grow year over year, expand their expertise, and become valuable contributors across the business. The result? Higher engagement, stronger performance, and teams that want to stay and grow.  This conversation reinforces a critical truth: You can’t deliver consistent customer experience without investing in the people who deliver it.  Leadership Advice for CX Professionals   For leaders at any stage of their CX journey, this episode offers practical, experience-backed guidance:  Keep CX strategies simple and focused  Don’t try to fix everything at once — move the business forward in stages  Use partners and peers to challenge assumptions  Focus on outcomes customers care about, not vanity metrics  Start building AI understanding now — optimization is the next phase  These insights are especially valuable for emerging CX leaders looking to avoid common pitfalls and accelerate their impact.  Meet the Experts   Scott Thomas – AVP, Client Support at Cox Automotive Inc.  Jim Iyoob – Chief Revenue Officer at Etech Global Services & President of ETS Labs  Manu Dwievedi – AVP, Product Strategy & Innovation, Etech Global Services  Watch Now: Build CX Accountability That Scales  Learn how forward-thinking CX leaders are redefining quality — not as a checkbox, but as a measurable, scalable, and human-centered discipline.  Gain practical insights on quality transformation, AI readiness, leadership decision-making, and employee engagement — straight from real-world experience.  ▶️ Watch the full episode now  📢 Stay updated with more conversations on leadership, AI, and customer experience — Subscribe to the  Etech Leadership & CX Podcast. 

The Customer Experience Lie That’s Costing You Millions

Every business says customer experience matters — yet many organizations still treat it as a cost center instead of a growth driver. That disconnect is costing companies far more than they realize.  In this episode of the Etech Leadership & CX Podcast, Jim Iyoob sits down with Camila Ferreira, Global Customer Experience Leader and Strategist, to unpack one of the biggest misconceptions in CX today — the belief that customer experience lives only within customer support.  With over 20 years of experience leading CX transformations across the US, Latin America, and Europe, Camila explains why real customer experience must span the entire business journey — from sales and onboarding to service and support. When CX is isolated, growth stalls. When it’s connected, it becomes a powerful engine for revenue, retention, and loyalty.  This conversation goes beyond trends and tools. It focuses on what truly moves the needle: aligning people, processes, culture, and technology — including AI — without losing the human connection that customers and employees value most.  About the Episode   This episode explores how organizations can shift from viewing CX as a cost to treating it as a strategic advantage.  Camila shares why simply relabeling customer support as “customer experience” doesn’t solve the real problem — and how leaders can unlock far greater value by connecting every stage of the customer journey. The discussion also dives into AI adoption, explaining why technology should amplify strong processes, not mask broken ones.  You’ll also hear practical insights on why employee experience and customer experience are deeply connected — and why sustainable CX improvements can’t happen without investing in both.    Why This Conversation Matters   Rethink Customer Experience: Learn why limiting CX to support teams creates blind spots that directly impact growth.  Use AI the Right Way: Understand how to avoid AI hype and focus on readiness, data, and clear problem-solving.  Strengthen Employee Experience: See how engaged employees drive higher customer satisfaction and long-term loyalty.  Plan for Smarter Growth: Discover how breaking silos and aligning teams leads to better CX outcomes and stronger ROI.  What You’ll Learn   The biggest misconception about customer experience that costs companies millions  Why CX must be treated as a business-wide strategy, not a support function  How to prepare your organization for AI before investing in new technology  The link between employee satisfaction and customer satisfaction  Common planning mistakes leaders should avoid when budgeting for CX and AI initiatives  Meet the Experts   Camila Ferreira – Global Customer Experience Leader & Strategist  Jim Iyoob – President, ETS Labs  Watch Now: Build CX That Drives Real Value  Discover how leading organizations are moving beyond surface-level CX initiatives to build experiences that create lasting business impact.  Gain practical insights on CX strategy, AI readiness, employee engagement, and leadership — straight from real-world experience.  ▶️ Watch the full episode now  📢 Stay updated with more conversations on leadership, AI, and customer experience — subscribe to the  Etech Leadership & CX Podcast. 

How to Make Your Live Chat Service Smarter with Artificial Intelligence?

Live chat is a tool growing in popularity for consumer interactions. It is not an overly complicated system, involving a simple messenger window and sometimes a live chat customer service representative. However, more recently, companies have been turning to artificial intelligence in live chat for additional support to both team members and customers. While this updated approach may seem counterintuitive for improving consumer relations, there are several excellent reasons to incorporate AI into your companies chat sessions.

What are the 5 Crucial Metrics You Should Measure to Improve Your Contact Center Performance?

Are you a quality assurance manager in any contact center? If so, you know that it is a part of your work to make decisions that directly impact the contact center’s bottom line. You have to keenly monitor the performance of your contact center and figure out how your team members can deliver better customer experience each time they interact with customers.  How can you do this effectively? An excellent way to monitor call center performance is by measuring the productivity of your team members with stable and reliable metrics. There are several contact center software options available in the market that might give you a variety of metrics in real-time, however, you need to measure crucial and useful metrics for the most valuable insights information.  Read the following to explore these crucial contact center performance metrics you want to track in order to take your contact center performance to the next level: Average Rate of Call Abandonment Every contact center wants to deliver memorable customer experience, and so does yours! Right? Therefore, it is important to be available when your customers contact you for any assistance, otherwise, you should be able to give them a logical reason why you are unavailable and timeline about how soon you can get back to them. It is one of the effective ways to build a good rapport with your customers and keep them satisfied. But, it has been observed that most of the time, it is just the opposite that happens in contact centers.  Customers often hang up before they can even connect with a team member. This is what we call the average call abandonment rate. Monitoring this metric can give you an overall idea about your team members’ performance. If this rate is higher, try to identify the reasons behind why your people are unable to serve your customers in time, and take necessary steps to improve the scenario.  You may want to communicate with your customers what exactly they can expect their hold time to be based on the availability of your team members and, if needed, hire more people for frontline work when the inflow of customer calls is more, coach and empower your team members on how they can be faster in answering customer calls, or give the busy callers an option to leave a voicemail or request a call back instead. It all depends on what problem your contact center is facing. Once you are able to identify that, your contact center can take the relevant steps to solve these issues.  Blocked Calls Percentage   Blocked calls percentage is nothing but the proportion of incoming calls from customers that receive a busy tone. In an inbound contact center, even one blocked call can result in losing a customer forever. So, if you want to ensure your team is connecting with each inbound caller, you need to identify the common causes of blocked calls and encourage practices that can remarkably reduce them. One of the reasons behind increased blocked calls percentage could be that not enough team members are available in a specific shift and there are no call queues configured, so callers hear a busy tone. In such a scenario, you want to figure out the possible effective ways to solve this issue. Some of the major ones could be making sure your contact center software can support the call volume, optimizing call queuing, improving agent scheduling and adherence, as well as call forecasting, etc.  Average Duration of Time in Queue    Another important metric to keep an eye on is the measure of overall performance for your contact center. The measurement of overall performance is the average customer wait time in the queue. How you can derive this metric is by dividing the total time callers wait in the queue by the total number of calls answered. It is important to measure the average time that your customers have to wait in the queue to improve the experience that they are receiving from your end.  If you see that your customers end up waiting in line longer than usual, you can ask your team to be more efficient in handling calls and coach them accordingly so that they can drive this KPI to score lower. Also, you may choose to provide your customers with a facility to call back so that they don’t have to keep waiting.  When it’s about measuring contact center productivity Approximate Speed of Answer One of the best metrics you need to consider is the average speed in which your team members answer your customers’ questions. If you notice that this metric is too high, it may mean your people are not able to assist customers, as expected. In such a situation, you want to figure out the reason why they are slow to answer customer calls. It has been observed, most of the time, that the use of improved work tools can help increase your team members’ average answer speed.  Average After Call Work Time   You will see your team members’ work doesn’t end when calls are finished. In fact, they often end up spending quite a bit of time updating databases, sending emails and informing teammates about the call, etc. The time that your people spend completing a transaction after the caller has disengaged is the after call work time. As a quality assurance manager, you need to craft and leverage smart processes to reduce your team members’ after call work so that they can make the best use of their time interacting with customers while they are on the clock. It can help your contact center to solve more customer problems and ultimately deliver an effortless and consistent customer experience.   Summing Up The quality assurance managers at contact centers typically have a general sense of how the team members are performing, even before they look at the metrics. But, it’s crucial to measure the above specific key performance indicators to identify the areas of improvement and

Human Intelligence + Artificial Intelligence – The ‘Winning Formula’ to Deliver Remarkable Customer Experience

If I were to ask a bunch of people the last time they had a really great experience as a customer, it probably wouldn’t take them long to come up with a story of how the lasting impression of the experience made them happy and satisfied. And the same goes for a poor customer experience, too- customers could probably think of the story and reason within seconds, and how the feeling afterwards was just the opposite. They probably had felt angry, upset, annoyed, frustrated, or any combination of these negative emotions. When we say positive customer experience, it doesn’t only mean making your customers happy, it also leads to additional revenue. It’s imperative that brands understand the best marketing that money can buy is simply a customer who will promote their business – because they will refer their friends and family to the company, free of charge!  Customer Experience – The Only Differentiator in Today’s Business World! Today’s consumers want a positive experience, not just a transactional relationship, with the brands and companies they engage with. So, customer experience plays a significant role for brands to develop a productive relationship with them. According to a recent study, 86% of buyers will pay more for a better customer experience, 70% of the buying experience is based on how customers feel they are treated, and 70% of customers will do business again with the company that resolves their complaints. Customer experience is proactive, cross-functional, feelings-oriented, and also defines the customer’s perception of the company. The customer experience, that is, making each of its clients feel special, has become the critical factor for a business to stand out from its competitors. The rise of the customer experience as a critical competitive differentiator has led to the growing importance of design thinking in the last few years. So, if the customer experience your business has created is not great, you should know how you can improve it and where to start. To leverage the power of Human Intelligence (HI) combined with Artificial Intelligence (AI) in contact center quality monitoring is probably the most effective way to do that. It’s apparent that AI is quickly becoming a baseline requirement for even the biggest brands to compete in an increasingly globalized market. According to Forbes, more than 80% of businesses are already planning to use automated technology as a customer experience strategy by the end of 2020. However, many businesses still have concerns regarding the effects that AI will have on customer relations. Although the efficiency and economical cost-cutting benefits of automated technology are well documented now, there still exists a widespread myth that customers will always prefer to resolve their issues with live agents rather than a front-end AI-powered chatbot. However, the truth is that AI, when properly integrated with HI, can vastly improve the effectiveness of contact center quality monitoring. This can ultimately transform the customer experience delivered by brands. HI +AI – The Ultimate Way to Transform Customer Insights There are five crucial steps involved in this process: Listen to the customers Identify their problems Analyze the issues Take the right steps to improve customer experience Predict successful behaviors  HI and AI Together Can Take Customer Experience to the Next Level    Role of HI to Improve CX Human Creativity and Imagination can better craft the customer experience strategy Intuition and emotion of humans can transform the customer experience Humans can adapt to different customer behaviors and deliver an effortless experience accordingly Human Intelligence offers better foresight about future alternatives and risks Role of AI to Improve CX Provides a larger knowledge base Offers consistent reasoning Drives goal-directed, focused tasks Better evaluation and integration of past observations Artificial Intelligence – The Right Element to Decode True Customer Sentiments Harnessing AI helps contact centers discover people’s opinions, emotions, and feelings about a product or service. AI data-unification tools make daunting tasks such as data cleaning, combining data, etc. very inexpensive and quick. By assessing interaction history, AI tools can predict interaction context and aid in improving customer interaction(s).AI can sift through the data to determine customer trends and several AI- driven tools can help contact centers better manage large customer data sets from disparate sources, and integrate them with existing data to extract valuable insights with speed and precision. Data scientists with the knowledge and power of Artificial Intelligence can identify performance-enhancing behaviors and voice-of-customer insights while analyzing the AI-driven data that’s not easily discernible through traditional quality management processes. Artificial Intelligence (AI) and machine learning technologies can be integrated into call center Quality Monitoring solutions to overcome challenges of handling and analyzing 100% of customer interaction data. At Etech, we have hands-on experience with this. Etech’s A.I engine which is powered by Artificial Intelligence and machine learning platforms, has efficiently overcome the challenges of handling and analyzing large volumes of customer interactions for years. Delivering Effortless Customer Experience is Impossible without Human Wisdom Etech believes technology represents the HOW of change; humans represent the WHY of change.  AI will always be crucial to contact centers, but it’s not the only piece that drives memorable customer experience. We have to go beyond technology and data to reach human wisdom. Some of the effective roles that our people play in contact centers that remarkably help brands deliver memorable customer experience are customer sentiment analysis, gathering insights for strategic decisions, customer effort analysis, training need analysis and coaching and developing agents. Only Our People Can Make the Best Out of Artificial Intelligence The best way to make use of analytics gleaned through AI is to keep the human element involved. Data Scientists are crucial links between pinpointing customer needs and developmental weaknesses among team members. The human element is the key to instituting actionable coaching and development plans to spur continued improvements. The key to continued success and growth for any company lies in embracing new advancements in AI technologies while realizing the importance of utilizing human intelligence.   So, we can clearly say that

Thinking beyond Artificial Intelligence to improve the Customer Experience

When people think of departmental barriers, they tend to think of bigger organizations. The larger a company is, the more specialized it becomes, thereby deepening departmental differences. However, Forbes notes that organizations of all sizes struggle with departmental silos. This can make it almost impossible to deliver a reliable end-to-end customer experience. Many companies turn to artificial intelligence as a crutch to resolve the issue, but this is one problem that requires a stronger focus on interpersonal skills. Identifying the Source of Turf Wars Companies require harmonious interactions to maintain high productivity levels and provide a consistently good customer experience. However, turf wars are one of the biggest organizational struggles. This may stem from differences of opinion at the top management level, which trickles down to middle management and then regular employees. Note also that turf wars may stem from competition for scarce resources. Examining the Effects of the Silo Mentality The constant turf wars further drive a wedge between workers, making it more difficult for them to collaborate. Some of the problems this can create include the following: Limited sharing of information between departments Reduced efficiency in the business Lower employee morale and trust Lower productivity levels Lower customer satisfaction All of these problems need to be addressed for a company to run smoothly. However, low customer satisfaction may quickly become the highest priority. While artificial intelligence can certainly help to bridge the gap between departments, focusing on building strong relationships and changing the organizational culture may be more effective. Using Human Intellect To Destroy Silo Barriers One of the greatest aspects of human intelligence is the capacity for change. People do not act on instincts alone. They can learn, change and grow. This is the human trait that businesses need to capitalize on to break down silo barriers. Departments can then take more effective steps toward solving this problem, instead of using artificial intelligence as a crutch. Here’s how. Encourage More Transparency Transparency in an organization demystifies what goes on in different departments. Without this, employees can work for a company for years without ever really understanding how different departments fit together to bring one common vision to fruition. When employees are more aware of what each department, manager or team is responsible for, they can better reach out for assistance when they or a client’s customers need it. Make Interdepartmental Integration Seamless Sometimes a customer may call a contact center with a problem that requires an interdepartmental solution. For example, an employee may have upgraded a subscription, but a glitch in the system led to two charges: the original price and the upgraded price. The finance department will need to provide a refund. The tech team will need to address the glitch. The customer service rep may then act as a liaison. Companies may use artificial intelligence to automate updates to the customer as well as the feedback process. Create More Interdepartmental Goals Companies too often create goals backed by incentives that pitch employees, teams, and departments against each other. Instead, managers should work together to create goals that require collaboration across the board. For example, a company may decide to improve efficiency by 10% in 180 days. To achieve this, they may task the engineers with improving the functions of applications that rely on artificial intelligence, such as data analytics and chatbots. Engineers would need to work with customer service reps to find out more about the customer experience and their concerns. Provide Opportunities for Socializing When it comes to solving serious problems like low customer satisfaction and reduced employee productivity, social gatherings are the last thing on a manager’s mind. However, social events can help to reduce some of the tension between departments by compelling people to get to know each other better in a more relaxed setting. Companies can increase the likelihood of this on a daily basis by providing more interdepartmental common areas. The Bottom Line When It Comes to Silos Companies across multiple industries rely on artificial intelligence to help them tie all the different aspects of a business together. AI also helps them to transform the customer experience for the better. However, AI alone cannot save a business from itself. Managers must encourage interdepartmental collaboration to break down internal barriers. Until this happens, a company’s divisiveness will continue to reflect in increased call transfers and overall confusion when handling customer requests. At Etech, we believe combing a mix of human intelligence & Artificial Intelligence is the key to tackle the damaging effects of silos. By focusing more on cooperating across departments, we are better able to serve our clients and their customers. Contact us today for more information. This blog was earlier published on LinkedIn.

What are the Important Operations Management Trends to Follow?

Call center operations are vital to the success of any business enterprise. Representatives in these pivotal positions are often the first line of contact with the consumer, meaning the client’s first impression of corporate vision and culture is through a chat or phone conversation. Therefore, it is crucial that these interactions are well-crafted and do not put off potential customers. The best way to ensure satisfaction and control is to enlist the most updated tools in operations management. The following five trends offer the most support and significance to contact center operations. Artificial Intelligence There is no need to fear artificial intelligence. The technology is not a threat to employment but rather a useful tool to aid in the management and collection of essential client information. Many call center operations use chatbots and automated voice systems to help sort through the incoming call logs. This in no way eliminates the human element. AI systems assist call operations by providing consumers with the most frequently requested information, which enables contact center employees to spend more time with customers who really need it; this is especially helpful for IT assistants. However, any company currently operating will find great value in the implementation of some AI elements for their contact solutions. Serverless Computing and Cloud Storage Upgrades to infrastructure are necessary for all business operations, including call center operations. Through the integration of serverless computing and a reduction in data centers, companies will be able to conduct business at a more rapid pace without the need for redundant operations. These tools are especially useful to contact center workers because much of their job involves the repeated entry of data and the repetitive use of forms. If any of these operations can be sped up, then these individuals can perform complex tasks in less time and assist more clients in a single day. Automating Processes Automating contact points or call center operations is not the same as eliminating the human element of your business. Instead, it is aimed at improving efficiency through the use of improved software and tools. For example, reservations, check-ins, even translations once ate up significant amounts of time, but now, with advanced technology, these things can coincide in chatbot windows without needing to distract employees or take away time from customers. Beyond improving customer relations, tools for automating processes will also have a tremendous effect on internal communications, scheduling, group messaging and other operational processes that directly affect the day-to-day corporate culture. Mobile and Digital Communications Cell phones, tablets, laptops are all signs of the growing trend of mobility. While it has been a trend for some time, the technology and abilities of smaller and smaller devices to carry out complex tasks has made mobile and digital communications an essential part of any growing business model. Also, Call center operations are heavily rooted in communications, which is why mobile and digital platforms serve as the cornerstone of successful contact centers. However, not every company is on-board or updated on these current trends. Some critical elements of a mobile platform are team apps, client portals, accessibility, messaging and other features targeted toward frontline and remote workers. Culture and Workplace Experience Beyond the technological advancements necessary for call center operations, over the last two decades, it has become overwhelmingly clear that managing call center operations are also about developing and nurturing a positive culture. The benefits of an influential company culture have long been known, but only as the world has taken a closer look at work-life balance have businesses really understood what it means to be a team. A healthy team atmosphere establishes an identity and improves employee retention, which is critical in call centers. Also, when a team mentality is correctly developed, it enhances the level of satisfaction people have in the workplace, allowing them to be more productive with their time and energy. Call center operations are a crucial element of any business, but they must be nurtured. It is not enough for an operator to simply answer the phone anymore. Customers expect more, and team members deserve more, especially when there are technologies that can significantly increase productivity and effectiveness. However, implementing such a change is not easy and demands a skill set that not every company has on-hand. Therefore, when your contact center solutions are lacking an expert in the field, contact  Etech Global Services. With over 20 years of experience, Etech understands the shifting trends and growing need for effective and efficient call center services. Contact a representative and find out what they can do for you. This blog was earlier published on LinkedIn.

Analytics and the Power of the Human Touch: 5 Predictions for the Future

Everyone knows the story behind the demise of at least one brand or company that eventually failed to thrive due to an inability or refusal to innovate and change with the times. Many of these major businesses that experienced failures were, at one time, hugely successful and popular. Perhaps you remember the joy and anticipation of searching the shelves for that newly released video on a Friday night at Blockbuster or browsing aisles of new toys at Toys R Us. These are just two examples of large companies that thought incorporating new and evolving technologies into their game plans weren’t necessary, and ultimately paid the price for those decisions in the end. The truth is new technology is king and it’s constantly evolving. When it comes to successful business strategies, staying up-to-date on what’s new and what’s to come in the world of analytics is a must. To be clear, there’s certainly expected to be huge advancements in technological resources in this field over the next decade. The question is, which of the technologies should you keep your eye on and how can you ensure you don’t lose the human touch needed to get the most out of the analytical breakthroughs? You read that right: while artificial intelligence (AI) and analytics continue to grow and become increasingly important for sustained success, so will human intelligence (HI). Read on for five predictions on what’s ahead and how AI and HI will need to work hand in hand to reach their maximum potential. AI Isn’t Going Anywhere and Is Growing Larger Currently, most businesses across a wide expanse of fields utilize AI in some way. The technology is often used for providing predictive analysis on customers and for automating some work processes. It’s expected that AI will eventually be interwoven with how consumers communicate and engage with nearly anyone and anything, including friends, companies, other technologies and even their homes. What’s important to not lose sight of in this technological advancement equation is the equal importance of human intelligence. AI is only as good as the people that know what to do with it. In the case of analytics, if it can’t be deciphered and put to good use to make positive and effective changes, what difference does having the data make? The best way to make use of analytics gleaned through AI is to keep a human element involved. Experts, such as Data Scientists, will be a crucial link between pinpointing customer needs and developmental weaknesses among team members. The human element is the key to instituting actionable coaching and development plans to spur continued improvements. Evolving AI Will Allow Team Members To Reprioritize Tasks While many companies already rely on some form of AI or system to generate their customer and performance data, most of them still count on people to detect anomalies, compile reports, score leads and any number of other manual processes. It’s predicted in the not-so-far-off future that most, if not all, these tasks will be automated thanks to marketing software and analytics updated with more advanced AI features. This provides benefits to help companies improve two-fold. First, this technology is able to evaluate all the data points available to it, not just a single one at a time. This provides a deeper look into a brand’s performance and where additional focus is needed. Second, with the software compiling the data, leaders are free to focus on training and coaching team members and putting actionable plans in motion. Consumers Will Demand Personalized Service The cold, hard truth is that many businesses will only be as successful as their customers are happy in relation to the experience they’re provided. The customer experience (CX) offered by a brand can easily make or break it. According to a survey from the Sitel Group, more than half of the consumer market is willing to spend extra money on a product or service from a company that provides top-notch CX. Businesses would be wise to take note of this important statement. It will no longer be enough for a brand to take a channel perspective and expect all customers to want the same experience and modes of engagement. Businesses will require a deep understanding of the various ways customers wish to communicate and will then need to act and deliver upon these customer expectations. Continued and heightened engagement over social media, online chat services and email will likely stay relevant and popular for the time being. This doesn’t necessarily mean all automation, bots, online interactions and the like. Sitel points out in its study that human interaction is still preferred by 70% of consumers, so having a live voice ready to assist will continue to be crucial to delivering excellent customer experiences. The Goal of Personalized Customer Experiences Will Be Achieved Through Prescriptive Analytics Speaking of exceptional and personalized customer experiences, prescriptive analytics may well be the key that pinpoints what that customer will need or want next. For some businesses, that may take the form of offering the right product or service at just the right time to the right customer. For other companies, implementing more effective prescriptive analytics may involve putting into play a recommended solution to a found problem. Human intelligence will drive positive outcomes here as solutions are implemented, monitored and adjusted in real-time, as needed. No matter what this looks like for a particular brand, inviting in some form of prescriptive automation will be imperative for quickly meeting customer needs. Businesses Will Gain a Better Understanding of End-User Happiness With Sentiment Analytics Gone will be the days of solely relying on traditional surveys and call-center data. The wave of the future is gaining a sense of customer attitudes, loyalty and satisfaction through the collection of additional behavioral data. This could include the analyzing of customer interactions through a brand’s website and any other offered channels of communication and engagement. Although it’s still in the very early stages and not nearly ready to be rolled out in

Why Machine Learning and Artificial Intelligence Are Crucial To Your Business?

Artificial intelligence often brings to mind images of sentient robots and futuristic science fiction movies. However, human intelligence gets assistance from AI and machine learning every day. Even if you don’t live in a smart home, you may use AI for tasks you have long detached from the pop-culture idea of AI. One common use of AI and machine learning at work and home is Google search. This is true whether you shout “Hey Google!” across the room to ask questions, or manually type it into the search bar on your computer. Because of how accessible AI became in everyday life, it became easier to introduce technology into the workplace. Proactive businesses have now become so dependent on technology that it is crucial to their continued success. Here are some of the recent developments and why it may become an essential ingredient in your business’ recipe for growth.   New Trends in AI and Machine Learning   You can hardly go a full month without hearing about new developments in technology. It is a rapidly changing market, bringing innovations with each sweeping change. One impressive test of technology comes in the form of artificial intelligence in call center settings. Many companies now trust chatbots to answer customer queries until the office re-opens during regular business hours. Call centers also employ technology to recognize customer requests. As Forbes points out, AI operators were initially programmed to understand one or two-word requests, such as “make a payment,” but many are now able to accept and understand full sentences. Another aspect of sales that AI penetrated is inventory management. From auto parts to the food and beverage industry, companies now rely on AI to tell them what items are out of stock. Some systems are so advanced that they can even place new orders on the company’s behalf. Doctors often think of their jobs as the most secure, but they have recently received a helping hand as well. Because medical errors are frequently caused by burnout, many doctors may welcome the assistance. Google recently launched a pilot project aimed at predicting whether or not a patient will die. The AI system did so with surprising accuracy. Artificial intelligence also powers and secures many homes. From security systems, you can access via an app to strategically placed AI assistants. People can now pay bills, open and close doors, or set reminders without lifting a finger. Why is AI and Machine Learning Important?   Workers often worry that machines will soon take their jobs. They envision walking into work one day to see a robot comfortably seated at their desk. Fortune predicted that 40% of jobs would be replaced by AI in the next decade and a half. Naturally, customers do not ask companies to fire their valued workers. However, they do demand better service, at faster speeds, and for less money. The only way to achieve this without underpaying and overworking humans is to pass jobs on to machines. This helps companies to remain competitive while keeping their customers satisfied and happy. Netflix, for instance, estimates that its personalized recommendation engine saves the company $1 billion every year. Consistently receiving tempting recommendations encourages customers to stay.   How Does AI and Machine Learning Benefit Business and Commerce?   However, businesses aren’t the only ones who benefit from AI. Customers benefit too. How so? Take Uber, for example. There are plenty of cab companies that hire human agents to handle calls from customers and match them with a cab driver, but the cost of a ride is significantly more expensive. Machines do not get paid days off, health benefits or wages. They also don’t need their cubicles or a corner office. That translates to savings for Uber customers and better satisfaction. As companies continue to rack up savings from these investments in technology, they can bring customers even better value for their money by expanding. This could mean growing their service areas, or it could mean increasing the products and services they offer. In Uber’s case, this resulted in self-driving cars and electric Jump bikes. What Should You Expect in the Near Future?   As machines learn better techniques to emulate human intelligence, menial and tedious jobs will begin to disappear from the market. This will help companies to become more and more efficient while reserving actual human intelligence for jobs that require creativity, ingenuity, and real human touch. As a result, workers who refuse to grow with technological changes may be pushed out of the job market. However, for those who are willing to adapt and even create these advancements in artificial intelligence, the possibilities are endless. Are you ready to embrace AI and ML to increase customer satisfaction for your business? Contact Etech at info@etechgs.com to see how we can help. This blog was earlier published on LinkedIn.

Do We Need AI to Truly Transform the Customer Experience for the Better?

According to a Gartner Report, 85% of customer interactions will take place without human involvement by 2020. Put simply, artificial intelligence is transforming the way companies interact with their customers. But, do we really need AI to maintain high levels of customer satisfaction, or can we rely solely on human intelligence? To answer this question, here are some of AI’s transformative qualities and how they complement human intelligence. Constant and Immediate Availability   When customers call customer service or initiate a chat, the wait time is longer without the help of artificial intelligence. Bots can at least begin the greeting process while customers wait for an available agent. Bots can also help to confirm what kind of help customers need, ensure they are communicating with the right department and redirect them if they’re not. Forbes notes that because bots never need to sleep, they can handle these tasks even when there are no available agents, because it is outside of business operating hours. This is especially important for business with restrictive hours, such as the post office, banks or government institutions. Artificial intelligence also reduces the pressure on contact centers to schedule more agents to work at nights. The Financial Times notes that night shifts present a fundamental biological challenge to the human body. People who work nights generally sleep less. Note that routinely getting less than six hours of sleep can increase mortality risks by 13%. Improves the Work Process for Human Agents   Sorting calls and verifying that customers are on the right line is the less exciting part of customer service. It can also be the one most frustrating for customers because they hate to be transferred. When bots handle the sorting in chats or automated operators handle this on the phone, people can focus on aspects where human intelligence is best applied. Humans are more urgently needed for the real people skills and creative problem-solving. These are the aspects where artificial intelligence may fall short, no matter how brilliant the coding is. Bots may, for instance, fail to understand a message riddled with typos or which is written by someone who does not speak English as a first language. Humans would pick up on these errors, whereas bots tend to need more specific parameters to act. When bots can handle sorting, scheduling appointments and other small tasks, it further helps to make work easier for human agents. It reduces the bottleneck they may otherwise meet in the morning when they begin their shifts. Bots can also help to reduce the pressure when centers are short-staffed during an unexpected incident related to the client’s products and services, such as a service outage. Provides Actionable Data and Predictions   Artificial intelligence may also provide personalized information on customers. Depending on how advanced the system is, this information may even include predictions based on a customer’s purchasing behavior. For example, agents may see current subscriptions, how long customers have done business with the company and even ratings on the likelihood of successfully upselling certain products and services. By arming agents with this valuable information, it prepares them for higher levels of success in interactions. This is true even when the customer begins the conversation frustrated or upset. Forbes notes that this personalized data helps companies to tap into the coveted 1% of the customer pool. These are the highly discriminating customers worth more than 18 times the value of a regular buyer. One bank even uses it to maintain unsolicited but helpful contact with customers. When a customer of the Royal Bank of Scotland continuously overdrafts their account, bots flag the account for a follow-up. The best employee for the job then calls the customer to offer financial advice. The Bottom Line: The Argument for AI in Business   Put simply, artificial intelligence is an indispensable part of transforming the customer experience for three main reasons: • It reduces the cost companies would otherwise sustain for providing 24/7 customer support and a strong commitment to customer satisfaction. • It reduces the workload for customer service agents, while increasing their effectiveness through personalized data. • It keeps customers happy. It does this by helping companies to better cater to a buyer’s individual needs, while being available right around the clock. At Etech, we are in the people business. We believe that the role of AI in transforming customer experience is to complement the work of our amazing team by taking over menial work. This allows workers to shine at the tasks that require creativity and interpersonal skills. For more information on how we use artificial intelligence at our contact centers, email us at info@etechgs.com. This blog was earlier published on LinkedIn.

How Artificial Intelligence Is Revolutionizing the Customer Journey

As traditional brick and mortar stores continue to struggle in an increasingly global economy, businesses have been forced to shift their approach to customer engagement just to survive. While metrics, such as carrying a superior product or offering the lowest price, may have attracted consumers in the past, almost 90 percent of companies are now focusing their competitive energy on providing an elevated customer experience.  The successful integration of artificial intelligence (AI) into a front-end interface is one of the most important factors when it comes to delivering the personalized encounters that customers now expect. AI is revolutionizing the customer experience in so many ways, that it’s becoming vital for businesses to adopt AI technologies to stay relevant into the 21st century.  The Customer Engagement Process Is Streamlined. AI has improved front-end efficiency so much that over 67 percent of consumers now expect the option of chatbots or messaging apps to help them resolve a problem before speaking to a live customer service agent. The benefit of fusing technology into your business model is twofold: providing a fast and personalized method for resolving common high-volume issues with customers while live service agents can focus on more complex problems that require human intervention; delegating the bulk of consumer interactions to AI, which provides a superior customer experience while improving the cost-effectiveness of your live chat agent training resources. Market Potential for Visual Search Options Has Exploded. As smartphone technology continues to improve, customer engagement has become centralized on pictures and graphics instead of written descriptions. Today’s consumers expect companies to offer phone applications that can search, track, and order past-history purchases while intuitively filtering products and services based on their needs by offering a simple, visually organized format. AI has disrupted the customer experience so much that 72 percent of internet users now expect access to visual content before deciding on a purchase. Businesses that fail to adapt to the “one-touch” smartphone shopping concept, ushered in by technological advances, will likely falter in the current marketplace. Consumer Insight Capabilities Are Rapidly Advancing. An influx of customer data will not be helpful without adopting the latest AI programs to collate it efficiently. A quality Customer Relationship Management (CRM) system capable of tracking purchase data while also building targeted consumer profiles and alerts, such as reminders to send a follow-up marketing email, can dramatically improve your customer engagement. What’s more, an AI-backed CRM system can help you retain more customers while building a brand based on the highly personalized experience that’s expected in a global economy. And with an average return on investment (ROI) of $8.71 for $1 spent on CRM implementation, your business will only benefit from integrating this technology into your consumer interface. AI-powered CRM’s can also be very valuable in information pass-through and ensuring the customer doesn’t have to repeat information at each interaction point, thus significantly reducing customer friction points. While the global marketplace of the 21st century has created a hypercompetitive economy, developing a focus on the elevated customer engagement that today’s consumers take for granted can give your business the best chance of success. Adapting to rapidly evolving technologies by putting them to work for your company is one of the most important ways to improve front-end customer interface. AI systems and software can revolutionize your customer’s journey, which in turn, help you develop a strong brand while attracting and retaining a steady customer base. With over 20 years of experience in providing superior customer engagement solutions across a wide range of industries, Etech is a world leader in helping companies integrate the latest artificial intelligence automation that allows them to compete in a diverse and globalized marketplace. Contact us today to learn how we can assist you in utilizing technology to advance your business. This blog was earlier published on LinkedIn.

How Big Data Analytics Is Gold for Call Centers?

Call centers generate data like no other department within a company. Information coming in from the outside, such as customer demographics, common questions, and favorite product features are gold mines for marketing, development, and customer engagement. Data gleaned from internal processes such as hold times, how long it takes to resolve an issue, and the number of calls managed per shift provides valuable information for departmental and company management. Best of all, the automated nature of a call center means that almost everything is recorded, cataloged, tracked, and measured with accuracy. As a bonus, it’s available indefinitely for future analysis and decision making. How Can Companies Use All This Data? • Unstructured data : Unstructured data can be defined as “information, in many different forms, that doesn’t hew to conventional data models.” An example is voice recordings from callers to a call center. The efficient call center software can analyze the tone of voice, content, and emotion. That knowledge can help a representative gauge the caller’s mood even before the conversation starts. This kind of processing is also called speech analysis or natural language processing (NLP). • Text data analytics : Call center is something of a misnomer as consumers now interact with companies via social media, email, messaging apps, and more. Text analytics programs can evaluate all those forms of communication, looking for themes and potential issues. The software can perform this kind of study on messages going out as well as those coming in. • Cross channel analytics : Customers use multiple avenues to interact with vendors, and it’s critical for businesses to understand those methods. For example, if a customer makes most purchases online, the company will want to make sure the client knows that he or she can get support the same way. Knowledge of how customers interact lets a company put more resources into the most used forms of engagement. • Quality control : Every call center has metrics related to customer service and the engagement experience. The data gathered through the call center makes this easier. Friction points become clear, and areas of difficulty for your agents are easier to spot. Also, all this data is prime material for training new agents, and better-trained agents mean improved customer metrics. The Process of Using Big Data Big Data analysis is a four-stage process: 1. Defining the data sources : This involves setting forth a description of all the pathways by which data is collected. You’ll want to include social media, email, and all other forms of communication. 2. Data gathering : This data involves the transformation of raw data into something manageable and organized. Depending on the nature of the data, this may or may not be a traditional database. Unstructured data requires more work to put into a manageable form. 3. Modeling : The data is used to create a hypothetical model for testing and evaluation. Big data gives you a laboratory to try out new ideas in a safe environment. 4. Deploying a model : At this stage, the company takes some action based on the information from the models. The management team has more confidence in decisions based on hard evidence. Get Started Now Businesses from healthcare to banking to manufacturing are finding uses for the big data collected through their call centers. Whether it’s artificial intelligence, machine learning, or predictive analytics, big data is becoming a priceless resource. If you’re ready to make the most of the information flowing through your call center, you have many options, and Etech Insights can help you with data insights for your organization. Contact Etech to find your way to improved customer experience and increased profitability through the use of data you’re probably already collecting. This blog was earlier published on LinkedIn.

How to Connect Data and Artificial Intelligence for Personalized Touch Points

Artificial intelligence is currently being propagated as the consumer experience champion and for a good reason. The ability and evolution of computer learning have led to improved efficiency, personalization and excellent analysis of big data, thereby transforming the e-commerce landscape and created a standard of expectation from customers. It is no longer feasible to appease the base with stagnant, unresponsive platforms. Patrons expect businesses to be not only accommodating but personable in both physical and digital locations. The expectation of such customization and personalization is only possible and cost-effective through the implementation of automated and analytical systems. However, many companies struggle with implementing such machine learning structures, which is why it is vital to understand how to connect data and AI with business objectives. Identify Problems and Seek Solutions   While big data offers tremendous insight into operations and corporate structure, it does nothing without the computational ability to analyze and produce actionable information succinctly. Incorporating AI into existing products and services is likely the best place for most businesses to start. Review your products, services, and operations to see where machine learning, natural language processing or image recognition could be used to streamline data and eliminate redundancies. Seek Value Not Reinvention   It is easy to get caught up in the technological advancements offered through AI platforms, but it is not wise to embrace it in its entirety. While these systems are excellent tools for data analytics and insights into the consumer experience, they should not be used at the detriment of your business and brand identity. If your model is built on approachability and personable communications with consumers, then implementing chatbots for all consumer interactions will only dilute that image. Do not reinvent the business for the sake of being technologically advanced. Do implement AI strategies that add value and help the company in finding improved efficiency and effectiveness. Know Your Capabilities   A large corporation with many big data sets is going to require more robust solutions than a small business with a limited consumer base and digital footprint. While every company can grow to the point of needing complex analytic tools that are housed in high-security facilities, not all businesses require such extensive technologies currently. Know your capabilities and where you want your business to grow. Don’t over-implement AI systems because it is what the larger corporations are doing. Your computer systems and processes should grow with the business and not necessarily surpass it. Integrate Integral Data   Though big data is the foundation for the success of automated systems, many corporations are plagued by redundancies in these data sets. Before implementing any advanced computer learning system, a business should weed through their data and eliminate any unnecessary or repetitive information. Once a new system is in use, it should only be fed integral data, allowing it to learn what information is valuable. Set Up Tests and Start Small   As mentioned, AI does require training which is why it is essential to manage the implementation of such systems. It is best to start small and tests the results, only moving further when the machine proves its capabilities on limited data sets. This structured implementation can be used in every aspect of your business from the front-end consumer experience to back-end operational usage. No matter the desired result, slow and structured is the path to a successful installation. Big data is only a piece of the implementation puzzle when it comes to artificial intelligence. While AI can help to transform a business into a consumer-focused and efficient machine, it can also inhibit a company’s progress if it is utilized too quickly and with little forethought. Therefore, if you are looking to incorporate advanced analytics and computer learning in your business model, then contact Etech to discuss and discover a customizable solution. This blog was first published on LinkedIn.

How Artificial Intelligence Humanizes Employee Communications and Customer Engagement

Images from the movies and popular culture might have you believing that machines are taking over the world. Cars carry on conversations with drivers or just drive themselves, robots are depicted as suitable dating partners, and that smartphone you keep on hand 24/7 probably recognizes your voice, face, and other biometrics. Contacting your utility company, buying groceries online, and ordering pizza delivery may not involve interacting with a human at all. In the world of business, Gartner estimates that by 2020, 85 percent of customer experience tasks will not involve a human. However, while it’s true that many functions in society can be automated, there’s still no substitute for the human touch. Many people are fairly adept at determining whether they’re dealing with a human or a machine and show a strong preference for the former. For that reason alone, fully automated customer experience tools are frustrating for many consumers, but that doesn’t mean they don’t have a place. When it comes to engaging your customers and crafting meaningful communications, you can draw on the best traits of human intelligence when combined with artificial intelligence to create a quality customer engagement experience. For example, you might use an AI tool to walk customers through very common tasks or questions. But when a complex problem emerges, and you have an exasperated client on your hands, you need a human to de-escalate the situation, share insights and find creative alternatives that preserve the relationship with the client. How does AI Helps in Customer Engagement? Data management: Customer service is more data-driven than ever. Demographics, buying preferences, touch points, and many other factors contribute to a massive set of data that no one person can cross reference and analyze alone. Artificial intelligence excels in that arena, but it’s still impossible to map out every possible scenario of behavior where humans are concerned. Buying decisions and concepts like customer loyalty are purely emotional concepts. Pairing a robust set of data points with a human mind that can interpret the emotions of a customer and pivot accordingly to is a winning formula. Faster response times: Even if the response to the customer is delivered by a human, using AI tools in the background to generate responses and possible courses of action make your representatives more agile and efficient. No more “brief holds to research this matter” unless it’s a lengthy and complex problem. Simple and common questions can be handled in their entirety by machines faster and more accurately than your human agents. You can even configure the AI tools to lead customers down a particular path and divert them to a human representative under certain conditions. Always available: Artificial intelligence tools can work round the clock every day of the year, so even when your human staff is off, automated responses can help clients find basic information. Customers who are ready to buy can do so on the spot. When your employees return to the office, they can focus on the more complicated tasks rather than wading through piles of routine requests that can consume the day. Why Does It Matter? A 2013 Zendesk report found that: Survey respondents indicated that customer service was the primary factor in whether or not they trusted a vendor. A good customer service experience led 42 percent of B2C customers to buy more from that provider. A bad experience led 52 percent to stop buying from that vendor. More than half of the companies surveyed by Gartner are using or will be using some form of artificial intelligence to improve customer experiences by 2020. If you’re ready to develop a plan for implementing artificial intelligence tools into your business processes, contact Etech today.  This blog was earlier published on LinkedIn.

Artificial Intelligence: Streamlining Contact Center Technology

It is hard to believe it now, but artificial intelligence used to be nothing more than a futuristic dream. It was portrayed in old movies as the vehicle that would completely change the world and propel our culture to unimaginable heights. Now, artificial intelligence—the stuff of the future—is all around us, and we are still learning just how much it can benefit us. In addition to improving our daily lives by helping us find restaurants, driving us around in our vehicles, and even controlling the lights and appliances in our homes, AI is also improving the world of business in a variety of ways. Automated systems are especially helpful for call centers, and Gartner predicts that non-voice interactions in customer service settings will likely rise to 85 percent by the year 2020. Many contact centers are discovering how artificial intelligence can benefit them and help them turn a greater profit while serving customers’ needs more effectively. If your contact center does not currently make use of AI, you may be spending more than you need to and missing out on your full potential to appease the needs of your customers. Consumers are increasingly desiring self-service options, but they still want the ability to speak with a live customer service agent if needed. When you offer digital solutions that recognize and predict the needs of your customers, you create a seamless user experience. While artificial intelligence should never replace the human component of your contact center, it can be used to help busy call centers handle larger call volumes with greater efficiency. How Artificial Intelligence Drives Effortless Customer Experience With Human Touch   One of the most universal challenges experienced by businesses of all types is the constant struggle to improve the customer experience. In fact, 72 percent of businesses list customer experience improvement as their top priority, according to recent data published by Forrester. Call centers that experience a high volume of customer service calls may consistently struggle to deliver a quick and effective customer service experience. Since recent research from NewVoiceMedia reveals that companies in the United States lose approximately $62 billion each year as a direct result of poor customer service, it is imperative for companies to turn the statistics in their favor by taking actionable steps to improve the customer experience for their consumer base. One of the most effective ways to do this is by incorporating artificial intelligence into the call center customer service process. Using AI in the call center can improve customer service operations in the following ways: Improving business agility Achieving operational excellence Providing machine-centric intelligence with human-centric interaction Increasing versatility and flexibility Predicting customer behavior Maximizing available resources and reducing operating costs Delivering a consistent, reliable experience to each customer Meeting customer needs around-the-clock Creating relationship-based interactions instead of transaction-based interactions Speech recognition systems can be implemented to relieve the burden of high call volume from human agents. Such systems can also take care of after-hours phone calls when call center agents are not available. This benefit makes it possible for businesses to take care of customer needs around-the-clock, without paying call center agents for graveyard shifts or overtime. In a digital age, more customers expect businesses to be able to meet their demands 24/7, and implementing a speech recognition into your call center can help you live up to evolving consumer expectations. When integrated into the call center, advanced speech recognition systems, such as interactive voice response (IVR) systems, make it possible for customers to easily navigate through a menu of options by using their voice instead of the telephone keypad. Other call center speech recognition options include speech-to-text, voice search, call routing, and voice dialing. For many businesses, automating the telephone answering system is an efficient way to handle anywhere between 40-85 percent of incoming calls. More and more businesses are leveraging the efficiency and predictability of speech recognition systems to improve efficiency and anticipate customer needs. Achieving the ideal blend between an automated, self-service environment and live agent interaction in the call center is a challenge worth pursuing. Providing customers with the option to navigate self-service systems without taking away their ability to talk to a real person as needed comes with a variety of benefits, including cost savings, more efficient customer service and improved customer experience. How to Use Artificial Intelligence As an Effective Quality Monitoring Solution   If you were to ask 10 different companies for the definition of “excellent customer service”, you would probably get 10 different answers. There is no single, universal definition of superior customer service that can be applied to all businesses. For this reason, it can be hard to nail down the standards that you need your call center team to adhere to in order to deliver the highest level of customer satisfaction. The challenge of determining, analyzing, and enforcing behaviors and actions that meet excellent service standards for your business most likely falls on the shoulders of your quality monitoring group. Their task is a monumental one, but it is necessary for delivering a concise, uniform approach to customer service. By using updated Artificial Intelligence software, it is possible to increase the effectiveness of your quality monitoring team. The highly accurate data provided by the AI software can direct your quality monitoring team to changes that may need to be made by call center representatives. The end result is an improvement in your contact center’s processes and methods for interacting with customers. Automating your quality monitoring system can provide some of the following improvements to your business: Reduced agent effort Better sales results Compliance with regulatory requirements Improved customer experience Artificial intelligence, when used correctly in a call center, can effortlessly monitor and gather valuable data from your team’s phone calls, chats and emails. It can also assist management in identifying opportunities to improve customer satisfaction, sales conversions and processes. Speech recognition technology is capable of anticipating customer needs and quickly delivering predictions and solutions that are specific to each

How Integrating Artificial Intelligence With Human Intelligence Can Delight Your Customers

Incorporating artificial intelligence (AI) into your call center quality monitoring can feel like an uncertain prospect. With over 80 percent of businesses already using or planning to acquire automated technology as a customer service strategy by 2020, it’s apparent that AI is quickly becoming a baseline requirement to compete in an increasingly globalized marketplace. However, many business owners still have concerns regarding the effects that AI will have on customer relations. While the efficiency and cost-cutting benefits of automated technology are well documented, there is a widespread myth that consumers will always prefer to resolve issues with a live customer service agent rather than a front-end AI-powered chatbot or interactive voice response system. The truth is that AI, when properly integrated with human intelligence, can vastly improve the effectiveness of your call center quality monitoring. Success depends on aptly assimilating technology into the existing corporate structure and promoting a workplace culture that embraces AI as a helpful resource. By keeping this philosophy in mind, you can use automation to develop an elevated front end experience that will dazzle your customers. Harness AI To Improve Overall Efficiency Surveys have shown that customers place a high level of importance in how quickly their issue with a company is resolved, while fiercely resenting the need to explain their problem to multiple people before reaching a solution. And nearly 70 percent of customers prefer the convenience of a messaging program over a live phone call to resolve an issue. Consequently, the speed and organization of your customer service matter just as much as the quality of engagement. This is where artificial intelligence in a call center can be a game changer. By streamlining some of your most repetitive, low level customer queries to a front-end AI-powered chatbot that consumers can communicate with at their own pace, you’re able to provide an immediate response to a simple question while freeing up time for your live call center service agents to address more complex issues or to speak with older customers who may not feel comfortable utilizing technology. Implementing AI to supply rote solutions to recurrent consumer complaints allows you to offer personalized, consistent service based on the level of engagement required. The result is a more effective system of call center quality monitoring. Use Automated Technology for Enhanced Training When humans are tasked with assessing customer service agent performance, limitations become evident. Most companies without a dedicated AI platform only have the resources to analyze a tiny fraction of recorded interactions. This means that they’re only getting a restricted sampling of vital call centers quality monitoring metrics such as voice analysis, predictive patterns of behavior, and productivity rates. By adopting an automated quality assurance program that can easily track every call, you’ll jump to a 100 percent monitoring rate that gives you the full picture of service center strengths and weaknesses. The analytic capabilities of a good AI quality assurance system also have the potential to transform your training strategies. Automated technology can easily identify hundreds of different variables to a human voice and develop predictive models for emotions that can be applied to specific customer queries and demographics. This data can then be used to formulate standard live agent responses to common consumer complaints, resulting in a higher level of satisfaction. By using AI to enhance the effectiveness of your live service team, you can channel the combined power of technology and human intelligence to provide a superior level of customer support. Ask for Live Agent Feedback on AI Systems While weaving artificial intelligence into call center structure can dramatically improve your customer satisfaction and retention rate, the truth is that no current AI software can operate completely independent of human supervision and interaction. Even the most sophisticated automated call center quality monitoring network will struggle with complex customer queries that require the empathy and emotional intelligence of a live agent. That’s why it’s imperative to develop appropriate escalation procedures with your customer support team in the event that a front-end AI-powered chatbot or interactive voice response system is unable to adequately resolve a consumer complaint. To prevent AI from mishandling customer service interactions, incorporate periodic reviews of call center transcripts to pinpoint areas of weakness in system analytics that may need to be supplemented by live agents. You should also assign a dedicated team to monitor all call center automated functions and make quality control adjustments as needed. Keep in mind that the purpose of AI is to delight your customers, so utilize insight from your live agents to continuously improve your automated systems and avoid frustration and confusion from consumers that may cause them to move on to a rival company. While upgrading your call center quality monitoring system to incorporate AI may seem like a big investment, the truth is that you can’t afford to forego automated quality assurance in today’s marketplace. With over 91 percent of top branded companies that boast superior levels of customer satisfaction utilizing AI, embracing technology is a fundamental strategy for converting and retaining a loyal consumer base. The key to providing the consistent, personalized service that customers now expect is to use AI in tandem with a talented pool of live agents who are trained to view automation as a useful tool, not a competitor. By implementing AI to improve efficiency and provide faster response times to customers, amplify training strategies, and integrate feedback from your call center team, you’ll be offering a premium level of service to consumers that will build long term brand loyalty. With over 20 years of experience in providing superior outsourcing solutions across a wide range of industries, Etech is a world leader in helping companies develop a seamless customer service experience. We offer a variety of artificial intelligence strategies including inbound and outbound call center service, live chat messaging, quality assurance monitoring, tech support, and software application. Systems are customized to meet your individualized needs while allowing you to compete in a diverse and globalized marketplace. Contact us

Want to improve Customer Experience? These are the 3 Technologies that you should be aware of!

Customer Experience successfully drives the business to the path of growth and profit. It is the critical competitive differentiation that sets a business apart from its competitors. Here are the three technologies that are imperative for delivering the best customer experience. Said so, it is essential to understand that the technology is just the enabler and a good CX is the outcome of the consolidation of people, processes, and technology. Most importantly the company’s people are the face of CX. “A brand is defined by the Customer’s experience. The experience is delivered by the employees.”  – Shep Hyken Live Chat Today’s customers don’t like to wait. They want an immediate response and what can be a better way than Live Chat! Live Chat helps to cater customer needs efficiently. It gives an open-ended platform for offering instant support and timely assistance. Various studies have shown that implementing live chat services has significantly improved customer satisfaction. In one of Inc’s article, it was stated that 92% of customers feel satisfied when they use the live chat feature. WHY? Customers find live chat to be very convenient as they can connect with an agent instantly and get real-time and personalized support. Their issues get addressed swiftly. The other best thing they find about live chat is that they can multi-task while having a conversation with the live chat agent, which they consider to be an added advantage. Artificial Intelligence It’s no secret that Artificial intelligence is flourishing and expanding its horizons every single day. With AI companies will be more efficiently and effectively be able to meet customer’s requirement and needs. HOW? For instance, data insights play a pivotal role in CX enhancement. However, customer experience data comes in the form of messy, unorganized datasets that need to be reformed into rational patterns to derive positive outcome. The tedium of pulling the data sets together and transforming them into no-complex consistent patterns is overwhelming. But for AI this is the prime stomping ground. It does it seamlessly and in a minor time frame. It’s high time that people start looking at AI with a different paradigm; it is not here to replace humans but to assist them. Combining AI and Human Intelligence can lead to seamless customer experience! Big Data Analytics Big data analytics is a game changer of the CX world. The application of this technology is transforming the way the businesses are interacting with their customers. WHERE? Big Data Analytics comes handy while analyzing the data collected from customers, and providing tailor-made solutions as per the expectations and aspiration of the customer. As showcased in a Salesforce survey 57% of customers share their personal data with companies for receiving discounts and personalized offers. Big Data Analytics helps in analyzing this humongous amount of data obtained from customers into an actionable way. It thus, aid in providing personalized services and delivering a better customer experience. Integrating these technologies into your business will help you to meet today’s customers’ expectations and to stay at the top in the battlefield of customer experience. This blog was earlier published on LinkedIn.

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