Category Archives: Customer Experience

Re-engineering Trust and Retention in the AI Contact Center

The Empathy Engine

LAST UPDATED: November 9, 2025 at 1:36PM
Re-engineering Trust and Retention in the AI Contact Center

by Braden Kelley

The contact center remains the single most critical point of human truth for a brand. It is where marketing promises meet operational reality. The challenge today, as highlighted by leaders like Bruce Gilbert of Young Energy at Customer Contact Week(CCW) in Nashville recently, is profound: Customers expect friction-less experiences with empathetic responses. The solution is not merely throwing technology at the problem; it’s about strategically weaving automation into the existing human fabric to create an Empathy Engine.

The strategic error most organizations make is starting with the technology’s capability rather than the human need. The conversation must start with empathy not the technology — focusing first on the customer and agent pain points. AI is not a replacement for human connection; it is an amplification tool designed to remove friction, build trust, and elevate the human agent’s role to that of a high-value relationship manager.

The Trust Imperative: The Cautious Adoption Framework

The first goal when introducing AI into the customer journey is simple: Building trust. The consumer public, after years of frustrating Interactive Voice Response (IVR) systems and rigid chatbots, remains deeply skeptical of automation. A grand, “all-in” AI deployment is often met with immediate resistance, which can manifest as call abandonment or increased churn.

To overcome this, innovation must adhere to a principle of cautious, human-centered rollout — a Cautious Adoption Framework: Starting small and starting with simple things can help to build this trust. Implement AI where the risk of failure is low and the utility is high — such as automating password resets, updating billing addresses, or providing initial diagnostics. These are the repetitive, low-value tasks that bore agents and frustrate customers. By successfully automating these simple, transactional elements, you build confidence in the system, preparing both customers and agents for more complex, AI-assisted interactions down the line. This approach honors the customer’s pace of change.

The Agent Retention Strategy: Alleviating Cognitive Load

The operational cost of the contact center is inextricably linked to agent retention. Finding and keeping high-quality agents remains a persistent challenge, primarily because the job is often highly stressful and repetitive. AI provides a powerful retention tool by directly addressing the root cause: cognitive load.

Reducing the cognitive load and stress level on agents is a non-negotiable step for long-term operational health. AI co-pilots must be designed to act as true partners, not simply data overlays. They should instantly surface relevant knowledge base articles, summarize the customer’s entire history before the agent picks up the call, or even handle real-time data entry. This frees the human agent to focus entirely on the empathetic response — active listening, problem-solving, and de-escalation. By transforming the agent’s role from a low-paid data processor into a high-value relationship manager, we elevate the profession, directly improving agent retention and turning contact center employment into an aspirational career path.

The Systemic Challenge: Orchestrating the AI Ecosystem

A major limiting factor in today’s contact center is the presence of fragmented AI deployments. Many organizations deploy AI in isolated pockets — a siloed chatbot here, a transcription service there. The future demands that we move far beyond siloed AI. The goal is complete AI orchestration across the enterprise, requiring us to get the AIs to talk to each other.

A friction-less customer experience requires intelligence continuity: a Voice AI must seamlessly hand off its collected context to a Predictive AI (which assesses the call risk), which then informs the Generative AI (that drafts the agent’s suggested response). This is the necessary chain of intelligence that supports friction-less service. Furthermore, complexity demands a blended AI approach, recognizing that the solution may involve more than one method (generative vs. directed).

For high-compliance tasks, a directed approach ensures precision: for instance, a flow can insert “read as is” instructions for regulatory disclosures, ensuring legal text is delivered exactly as designed. For complex, personalized problem-solving, a generative approach is vital. The best systems understand the regulatory and emotional context, knowing when to switch modes instantly and without customer intervention.

The Strategic Pivot: Investing in Predictive Empathy

The ultimate strategic advantage lies not in reacting to calls, but in preventing them. This requires a deeper investment in data science, moving from descriptive reporting on what happened to predictive analytics to understand why our customers are calling in before they dial the number.

This approach, which I call Predictive Empathy, uses machine learning to identify customers whose usage patterns, payment history, or recent service interactions suggest a high probability of confusion or frustration (e.g., first-time promotions expiring, unusual service interruptions). The organization then proactively initiates a personalized, AI-assisted outreach to address the problem or explain the confusion before the customer reaches the point of anxiety and makes the call. This shifts the interaction from reactive conflict to proactive support, immediately lowering call volume and transforming brand perception.

The Organizational Checkpoint: Post-Deployment Evolution

Once you’ve successfully implemented AI to address pain points, the work is not finished. A crucial strategic question must be addressed: What happens after AI deployment? What’s your plan?

As AI absorbs simple transactions, the nature of the calls that reach the human agent becomes disproportionately more complex, emotional, and high-value. This creates a skills gap in the remaining human workforce. The organization must plan for and fund the Up-skilling Initiative necessary to handle these elevated interactions, focusing on conflict resolution, complex sales, and deep relationship management. The entire organizational structure — training programs, compensation models, and career paths — must evolve to support this higher-skilled human workforce. By raising the value of the human role, the contact center transitions from a cost center into a profit-generating Relationship Hub.

Conclusion: Architecting the Human Layer

The goal of innovation in the contact center is not the elimination of the human, but the elevation of the human. By using AI to build trust, reduce cognitive load, enable predictive empathy, and connect disparate systems, we free the human agent to deliver on the fundamental customer expectation: a friction-less experience coupled with an empathetic response. This is how we re-engineer the contact center from a cost center into a powerful engine for talent retention and customer loyalty.

“AI handles the transaction. The human handles the trust. Design your systems to protect both.” — Braden Kelley

Your first step into the Empathy Engine: Map the single most stressful task for your top-performing agent and commit to automating 80% of its cognitive load using a simple AI co-pilot within the next 90 days.

What is that task for your organization?

Image credits: Google Gemini

Content Authenticity Statement: The topic area, key elements to focus on, insights captured from the Customer Contact Week session, panelists to mention, etc. were decisions made by Braden Kelley, with a little help from Google Gemini to clean up the article.

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The AI Agent Paradox

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How E-commerce Must Proactively Manage Experiences Created Without Their Consent

LAST UPDATED: November 7, 2025 at 4:31 PM

The AI Agent Paradox

GUEST POST from Art Inteligencia

A fundamental shift is underway in the world of e-commerce, moving control of the customer journey out of the hands of the brand and into the hands of the AI Agent. The recent lawsuit by Amazon against Perplexity regarding unauthorized access to user accounts by its agentic browser is not an isolated legal skirmish; it is a red flag moment for every company that sells online. The core challenge is this: AI agents are building and controlling the shopping experience — the selection, the price comparison, the checkout path — often without the e-commerce site’s knowledge or consent.

This is the AI Agent Paradox: The most powerful tool for customer convenience (the agent) simultaneously poses the greatest threat to brand control, data integrity, and monetization models. The era of passively optimizing a webpage is over. The future belongs to brands that actively manage their relationship with the autonomous, agentic layer that sits between them and their human customers.

The Three Existential Threats of the Autonomous Agent

Unmanaged AI agents, operating as digital squatters on your site, create immediate systemic problems for e-commerce sites:

Data Integrity and Scraping Overload: Agents typically use resource-intensive web scraping techniques that overload servers and pollute internal analytics. The shopping experience they create is invisible to the brand’s A/B testing and personalization engines.
Brand Bypass and Commoditization: Agents prioritize utility over loyalty. If a customer asks for “best price on noise-cancelling headphones,” the agent may bypass your brand story, unique value propositions, and even your preferred checkout flow, reducing your products to mere SKU and price points. This is the Brand Bypass threat.
Security and Liability: Unauthorized access, especially to user accounts (as demonstrated by the Amazon-Perplexity case), creates massive security vulnerabilities and legal liability for the e-commerce platform, which is ultimately responsible for protecting user data.

The How-To: Moving from Resistance to Proactive Partnership

Instead of relying solely on defensive legal action (which is slow and expensive), e-commerce brands must embrace a proactive, human-centered API strategy. The goal is to provide a superior, authorized experience for the AI agents, turning them from adversaries into accelerated sales channels — and honoring the trust the human customer places in their proxy.

Step 1: Build the Agent-Optimized API Layer

Treat the AI agent as a legitimate, high-volume customer with unique needs (structured data, speed). Design a specific, clean Agent API separate from your public-facing web UI. This API should allow agents to retrieve product information, pricing, inventory status, and execute checkout with minimal friction and maximum data hygiene. This immediately prevents the resource-intensive web scraping that plagues servers.

Step 2: Define and Enforce the Rules of Engagement

Your Terms of Service (TOS) must clearly articulate the acceptable use of your data by autonomous agents. Furthermore, the Agent API must enforce these rules programmatically. You can reward compliant agents (faster access, richer data) and throttle or block non-compliant agents (those attempting unauthorized access or violating rate limits). This is where you insert your brand’s non-negotiables, such as attribution requirements or user privacy protocols, thereby regaining control.

Step 3: Offer Value-Added Agent Services and Data

This is the shift from defense to offense. Give agents a reason to partner with you and prefer your site. Offer exclusive agent-only endpoints that provide aggregated, structured data your competitors don’t, such as sustainable sourcing information, local inventory availability, or complex configurator data. This creates a competitive advantage where the agent actually prefers to send traffic to your optimized channel because it provides a superior outcome for the human user.

Case Study 1: The Furniture Retailer and the AI Interior Designer

Challenge: Complex, Multivariable E-commerce Decisions

A high-end furniture and décor retailer struggled with low conversion rates because buying furniture requires complex decisions (size, material, delivery time). Customers were leaving the site to use third-party AI interior design tools.

Proactive Partnership:

The retailer created a “Design Agent API.” This API didn’t just provide price and SKU; it offered rich, structured data on 3D model compatibility, real-time customization options, and material sustainability scores. They partnered with a leading AI interior design platform, providing the agent direct, authorized access to this structured data. The AI agent, in turn, could generate highly accurate virtual room mock-ups using the retailer’s products. This integration streamlined the complex path to purchase, turning the agent from a competitor into the retailer’s most effective pre-visualization sales tool.

Case Study 2: The Specialty Grocer and the AI Recipe Planner

Challenge: Fragmented Customer Journey from Inspiration to Purchase

An online specialty grocer, focused on rare and organic ingredients, saw their customers using third-party AI recipe planners and shopping list creators, which often failed to locate the grocer’s unique SKUs or sent traffic to competitors.

Proactive Partnership:

The grocer developed a “Recipe Fulfillment Endpoint.” They partnered with two popular AI recipe apps. When a user generated a recipe, the AI agent, using the grocer’s endpoint, could instantly check ingredient availability, price, and even offer substitute suggestions from the grocer’s unique inventory. The agent generated a “One-Click, Fully-Customized Cart” for the grocer. The grocer ensured the agent received a small attribution fee (a form of commission), turning the agent into a reliable, high-converting affiliate sales channel. This formalized partnership eliminated the friction between inspiration and purchase, driving massive, high-margin sales.

The Human-Centered Imperative

Ultimately, this is a human-centered change challenge. The human customer trusts their AI agent to act on their behalf. By providing a clean, transparent, and optimized path for the agent, the e-commerce brand is honoring that trust. The focus shifts from control over the interface to control over the data and the rules of interaction. This strategy not only improves server performance and data integrity but also secures the brand’s place in the customer’s preferred, agent-mediated future.

“The AI agent is your customer’s proxy. If you treat the proxy poorly, you treat the customer poorly. The future of e-commerce is not about fighting the agents; it’s about collaborating with them to deliver superior value.” — Braden Kelley

The time to move beyond the reactive defense and into proactive partnership is now. The e-commerce leaders of tomorrow will be the ones who design the best infrastructure for the machines that shop for humans. Your essential first step: Form a dedicated internal team to prototype your Agent API, defining the minimum viable, structured data you can share to incentivize collaboration over scraping.

Image credit: Google Gemini

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Why Amazon Paid $3.9 Billion to Get into the Healthcare Business

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Why Amazon Paid $3.9 Billion to Get into the Healthcare Business

GUEST POST from Shep Hyken

Amazon is known for its amazing customer experience, despite most customers never talking to an Amazon employee. How does this digital experience — with no human interaction—drive so much loyalty? The short answer is confidence. There is very little that goes wrong with an Amazon experience, and if by chance it does, its system takes care of almost all problems—again, without human interaction. That said, if a customer does need to talk to a human, which is very seldom, the customer support team is there.

But what happens if you combine technology with a high-touch business, like a doctor’s office? You get One Medical, which Amazon bought in 2023 for $3.9 billion. One Medical’s founder, Dr. Tom Lee, is a Harvard-trained primary care physician who then went on to Stanford to get an MBA. Before opening his first clinic, he asked himself, “Why do we do these in healthcare like we’ve always done them? Why does every waiting room look like some sterile IKEA? Why do I wait in a reception area and then wait again in the exam room?” It was questions like these that caused Lee to tinker with and disrupt the traditional medical visit model.

Starting with one clinic, Lee created a different experience. He built an app and charged patients an $89/year subscription that gave them access to doctors. He focused on simple things like getting an appointment without making a call. Those little things were the start of what turned out to be a stellar experience that allowed him to expand, ultimately catching the eye of Amazon.

When the Amazon deal was completed, HealthCare Dive reported that Amazon now had a network of more than 220 medical offices in 27 U.S. markets with more than 836,000 members plus 9,000 enterprise clients. Neil Lindsay, SVP of Amazon Health Services said, “We’re on a mission to make it dramatically easier for people to find, choose, afford and engage with the services, products and professionals they need to get and stay healthy, and coming together with One Medical is a big step on that journey.” That’s what Amazon does. They make it easy for customers.

Joseph Michelli, bestselling business author of numerous books that tell the stories of iconic brands like The Ritz-Carlton, Starbucks, Mercedes and others, recently released a new book, All Business Is Personal: One Medical’s Human-Centered, Technology-Powered Approach to Customer Engagement, that tells the One Medical story. I had a chance to interview him on Amazing Business Radio, and here are the highlights that will give you some insight into why Amazon became interested in acquiring this amazing company.

Question Everything

Just ask, “Why?” It doesn’t matter what type of business you are in, there are reasons for everything. Often the reason a company or person does something is because “We’ve always done it this way.” So, question everything. Maybe you’ll still do it the way you’ve always done it, but at least you will have tried to find a better way.

Create a Stellar Customer (Patient) Experience

As Lee created a Customer Experience (CX) that drove impressive ratings, he looked at the friction most patients experienced. He started with an obvious pain point, the waiting room, which is, as the name implies, a room for people to wait. Some patients in traditional medical practices are forced to wait for unreasonable amounts of time. But not at One Medical. In addition to being easy to get a same-day or next-day appointment, Michelli shared that 95% of patients are seen within three minutes of their scheduled times. As already mentioned, Lee questioned every aspect of the patient’s experience, and he found many ways to make it better.

Blend Technology with the Human Touch

Technology, like apps and AI, makes life more convenient for customers by allowing things like easy online scheduling or getting immediate answers from AI chatbots. Often, technology can feel cold and impersonal, especially in healthcare. The best use of technology is to make things faster and simpler, but smart businesses, like One Medical, know to offer human backup when a customer/patient needs it. Finding the right balance between tech and the human touch keeps your business from being a commodity—just “another faceless service.”

Convenience Is King

People love doing business with companies that create convenient experiences. For One Medical, this means offering same-day appointments, speedy callbacks or handling many issues online versus the phone, so the patient doesn’t have to wait on hold or wait for a callback. Research shows that 73% of customers will pay more for a convenient experience. The easier you make someone’s experience, the more likely they will come back as well as tell others about you.

Make It Personal, Not Just Personalized

It’s great to remember a customer’s name or recall past purchases. That’s personalization. To take it a step further, make it personal. Make the customer feel that you care about them. That means when the customer (or patient) talks to an employee, they feel cared for, listened to and valued. Personal connections build trust and confidence, which leads to repeat business and potential loyalty.

The Effort Is Worth It

These five reasons (and a few more) are what gave Amazon 3.9 billion reasons (as in dollars) to acquire One Medical. Even if you were to practice these reasons flawlessly, you may never catch Amazon’s attention, but you will catch your customers’ (and potential customers’) attention. And that will make the effort worthwhile.

Image Credits: Pixabay

This article originally appeared on Forbes.com

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Why Going AI Only is Dumb

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I’m Sorry Dave, But I Can’t Do That

LAST UPDATED: November 3, 2025 at 4:50PM

Why Going AI Only is Dumb

by Braden Kelley

Last month I had the opportunity to attend Customer Contact Week (CCW) in Nashville, Tennessee and following up on my article The Voicebots Are Coming I’d like to dig into the idea that companies like Klarna explored of eliminating all humans from contact centers. After all, what could possibly go wrong?

When I first heard that Klarna was going to eliminate humans from their contact centers and go all in on artificial intelligence I thought to myself that they would likely live to regret it. Don’t get me wrong, artificial intelligence (AI) voicebots and chatbots can be incredibly useful, and that proves out in the real world according to conference speakers that almost half of Fanatics calls are automated on the phone without getting to an agent. A lot of people are experimenting with AI but AI is no longer experimental. What Klarna learned is that when you choose to use AI to reduce your number of human agents, then if the AI is down you don’t have the ability anymore to just call in off duty agents to serve your customers.

But, on the flip side we know that having AI customer service agents as part of your agent mix can have very positive impacts on the business. Small businesses like Brothers That Just Do Gutters have found that using AI agents increased their scheduling of estimate visits over humans alone. National Debt Relief automated their customer insufficient funds (CIF) calls and added an escalation path (AI then agent) that delivered a 20% revenue lift over their best agents. They found that when an agent gets a NO, there isn’t much of an escalation path left. And, the delicate reality is that some people feel self conscious calling a human to talk about debt problems, and there may be other sensitive issues where callers would actually feel more comfortable talking to a voicebot than a human. In addition, Fanatics is finding that AI agents are resolving some issues FASTER than human agents. Taken together these examples show that often a hybrid approach (humans plus AI) yields better results than humans only or AI only, so design your approach consciously.

Now let’s look at some important statistics from Customer Management Practice research:

2/3 of people prefer calling in and talking by phone, but most of that is 55+ and the preference percentage declines every ten years younger you go until 30% for 18-24
3/4 of executives say more people want self service now than three years ago
3/4 of people want to spend less time getting support – so they can get back to the fun stuff, or back to business

Taken together these statistics help make the case for increasing the use of AI agents in the contact center. If you happen to be looking to use AI agents in servicing your customers (or even if you already are) then it is important to think about how you can use them to remove friction from the system and to strategically allocate your humans towards things that only humans can do. And if you need to win support from someone to go big with AI voicebots then pick an important use case instead of one that nobody cares about OR even better, pick something that you couldn’t have done before (example: a ride sharing company had AI voicebots make 5 million calls to have drivers validate their tax information).

Finally, as I was listening to some of these sessions it reminded me of a time when I was tasked with finding a new approach for staffing peak season for one of the Blue Cross/Blue Shield companies in the United States. At that time AI voicebots weren’t a thing and so I was looking at how we could partner with a vendor to have a small number of their staff on hand throughout the year and then rely on them to staff and train seasonal staff using those seasoned vendor staff instead of taking the best employees off the phone to train temps.

Even now, all contact centers will still need a certain level of human staffing. But, AI voicebots, AI simulation training for agents, and other new AI powered tools represent a great opportunity for creating a better solution for peak staffing in a whole host of industries with very cyclical contact demand that is hard to staff for. One example of this from Customer Contact Week was a story about how Fanatics must 5x their number of agents during high seasons and in practice this often results in their worst agents (temps they hired only for the season) serving some of their best customers (high $$ value clients).

Conclusion

AI voicebots can be a great help during demand peaks and other AI powered tools (QA, simulations, coaching, etc.) can help accelerate and optimize both your on-boarding of full-time agents, but also of seasonal agents as well. But don’t pare back your human agent pool too far!

What has been your experience with balancing human and AI agents?

Image credits: Google Gemini

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Top 10 Human-Centered Change & Innovation Articles of October 2025

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Top 10 Human-Centered Change & Innovation Articles of October 2025 Drum roll please…

At the beginning of each month, we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are October’s ten most popular innovation posts:

AI, Cognitive Obesity and Arrested Development — by Pete Foley
Making Decisions in Uncertainty – This 25-Year-Old Tool Actually Works — by Robyn Bolton
The Marketing Guide for Humanity’s Next Chapter – How AI Changes Your Customers — by Braden Kelley
Don’t Make Customers Do These Seven Things They Hate — by Shep Hyken
Why Best Practices Fail – Five Questions with Ellen DiResta — by Robyn Bolton
The Need for Organizational Learning — by Mike Shipulski
You Must Accept That People Are Irrational — by Greg Satell
The AI Innovations We Really Need — by Art Inteligencia
Three Reasons You Are Not Happy at Work – And What to Do to Become as Happy as You Could Be — by Stefan Lindegaard
The Nuclear Fusion Accelerator – How AI is Commercializing Limitless Power — by Art Inteligencia

BONUS – Here are five more strong articles published in September that continue to resonate with people:

McKinsey is Wrong That 80% Companies Fail to Generate AI ROI — by Robyn Bolton
The Most Challenging Obstacles to Achieving Artificial General Intelligence — by Art Inteligencia
The Great American Contraction – Population, Scarcity, and the New Era of Human Value — by Art Inteligencia
Three Steps from Stuck to Success – Managing Uncertainty — by Robyn Bolton
Building a Learning Organization — by Stefan Lindegaard

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last four years:

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Measuring Human vs. AI Satisfaction

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Insights from Customer Contact Week (Nashville)

LAST UPDATED: October 30, 2025 at 1:00PM

Measuring Human vs. AI Satisfaction

by Braden Kelley

One of the sessions I had the opportunity to attend at Customer Contact Week in Nashville featured Brian Cantor (Customer Management Practice), Gene Kropfelder (Ally Financial) and Scott Rhinehart (Alorica). Two overarching themes of the session were that bringing technology and human elements together continues to be a challenge and that with every interaction you are either building or destroying trust. Gene highlighted that his outlook is that people don’t need another bank they need a better bank, and this mindset is something that he tries to help permeate throughout the organization. Two ways they try to be that better bank in customer experience terms is by first, creating transparency around the wait times in different support channels and second, by trying to make every interaction feel different/better than the interactions they have with Ally’s competitors.

Artificial Intelligence (AI) was obviously a focus of the session and the fact that personalization requires knowing the interactions a customer has had and what they’ve been exposed to, but AI (or humans) have to leverage that knowledge in a helpful and not a creepy way.

When it comes to AI, it’s not what AI can do, but what does it do better and what activities should it take on. Implementing AI in any situation should start with a shared understanding of what problem you’re trying to solve, clearly defined outcomes (work backwards from these, utilizing well-defined checkpoints), a well-communicated WIFM (What’s in it for me?), and a crawl/walk/run approach. Don’t go too big too fast.

We have learned along the way that artificial intelligence can be very useful for helping support agents lean in with the information they (and customers) need. AI as a tool to summarize research query responses versus a list of search results (links). AI can help us understand where agents are spending the time and serve as a knowledge base auditor (article inconsistencies, gaps, etc.).

One important question that came up is “How can we help with handle time?”:

CSAT and NPS are important but handle time is important not just for the company (cost) but also for the customer – so they can get back to their life

A more challenging question that all contact center managers must ask is “How do you measure AI satisfaction versus human satisfaction?”:

The reason this is a challenging questions is because most of the easily solvable questions will go the AI and the cases that often don’t have a good resolution will be the ones that go to humans
At the same time we need to consider the impact of automating certain types of calls (often the easy ones). Will this make the human’s job more stressful (no easy calls)? Will they need more breaks as a result?
In the quest for efficiency be careful not to have your humans provide a robotic experience (reading scripts, no authority or decision making capability or flexibility)

Our humanity (both customer and employee) will always be important. Both have to learn to trust AI outputs, impacting the rate and amount of adoption, especially if you don’t have a plan for how to build that trust over time. And, it is important to have human retain accountability – AI generated, human reviewed before submission (i.e. call summaries). Finally, it is important to understand that while we may view the digital native generations as preferring a technological solution, the reality is that even the younger generations will still reach out for a human touchpoint on important questions/issues. So we humans are safe – for now.

HALLOWEEN BONUS: Save 30% on the eBook, hardcover or softcover of my latest book Charting Change (now in its second edition) — FREE SHIPPING WORLDWIDE — using code HAL30 until midnight October 31, 2025

Image credits: Customer Management Practice

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Doing the Basics Can Be Surprising

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Doing the Basics Can Be Surprising

GUEST POST from Shep Hyken

Just in case you didn’t know, I have a weekly customer service and Customer Experience (CX) podcast, Amazing Business Radio, that has been running for 12 years. Each week, I get the honor of interviewing some very smart people. Recently, I met Eric Stone, author of Jumpstart Your Workplace Culture. One of the topics we discussed was the WOW experience.

Before we go further, I have always had concerns about organizations that attempt to WOW their customers at every interaction. It’s just impossible to do. The concept of WOW is often associated with going above and beyond what’s expected, so much so that the customer is “blown away” by the experience. The problem is that’s not always possible. That’s why I took it out of my vocabulary and started using the word amazing to describe what I think WOW really is all about, which is a consistent and predictable experience that ALWAYS meets, and only occasionally exceeds, the customer’s expectations. It’s easy to say, “The people at that company are amazing.” It’s a little clunky and awkward to say, “The people at that company are WOW.”

That’s why I loved what Stone said: “Wow is a surprise.” In other words, it’s not about every experience. It’s about the occasional opportunity to surprise a customer. It could be something big, such as handling an emergency situation in which employees go above and beyond. As I said earlier, you can’t count on that type of opportunity for every transaction, but what you can do is find little ways to surprise your customers. For example, if you return a call quickly, the customer might say, “Wow, that was fast!” That’s not an over-the-top or above-and-beyond experience, but it’s a small surprise.

With that in mind, let’s use the return phone call as an example. When you know people are often surprised and make comments like, “Wow, that was fast,” simply because you called them back quickly, don’t just say, “Thank you,” and feel good about the experience. Instead, operationalize the experience. In other words, make quickly returned calls part of your official process. Set a standard, such as all calls are to be returned within two hours (or whatever the appropriate length of time you feel is right for you).

With that as an example, what other interactions do you have with customers that need to be formally operationalized? Here are a few ideas to get your creative juices flowing:

All phone calls are to be answered within three rings.
A promise to only transfer a customer once, knowing you’ll get the customer to the right person the first time.
Proactive updates to inform customers before they reach out to you asking for information.
Following up after a resolution to make sure a customer is still happy.
Acknowledging customer milestones, such as congratulating them on their 10th order with you, their birthday, etc.

None of these ideas are above-and-beyond types of WOW experiences, but they will cause a customer to notice. Use these examples to help you get creative about finding other simple or small WOWs you can operationalize and make part of the customer’s regular experience when they do business with you.

HALLOWEEN BONUS: Save 30% on the eBook, hardcover or softcover of Braden Kelley’s latest book Charting Change (now in its second edition) — FREE SHIPPING WORLDWIDE — using code HAL30 until midnight October 31, 2025

Image Credits: Pexels

This article was originally published on Forbes.com

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The Indispensable Role of CX

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Insights from CCW’s 25-Year Journey

LAST UPDATED: October 28, 2025 at 12:00PM

by Braden Kelley

I recently had the privilege of sitting down with Mario Matulich, President of Customer Management Practice, at Customer Contact Week (CCW) in Nashville. As an organization celebrating its 25th anniversary, CCW has been a critical barometer for the entire customer experience and contact center industry. Our conversation wasn’t just a look back, but a powerful exploration of the strategic mandate facing CX leaders today, particularly how we manage innovation and human-centered change in an era dominated by AI and tightening budgets.

CCW at 25: The Hub for Benchmarking and Breakthroughs

Mario underscored that CCW is far more than just a conference; it’s a living repository of industry knowledge. Professionals attend for actionable takeaways, which primarily fall into three categories: benchmarking performance against industry leaders, learning about new trends (like Generative AI’s impact), and, critically, sourcing the right vendors and capabilities needed to execute their strategies. It’s where leaders come to calibrate their investment strategies and learn how to do more with their finite resources.

This pursuit of excellence is driven by a single, powerful market force: The Amazon Effect. As Mario put it, customers no longer judge your experience solely against your industry peers. They expect every single touchpoint with your company to be as seamless, intuitive, and effective as the best experience they’ve had anywhere. This constantly escalating bar for Customer Effort Score (CES) and Customer Satisfaction (CSAT) makes a complacent CX investment a near-fatal strategic mistake. The customer experience must always be top-tier, or you simply lose the right to compete.

The Strategic Disconnect: CX vs. The Contact Center

One of the most valuable parts of our discussion centered on the subtle, yet crucial, distinction between a Customer Experience (CX) professional and a Contact Center (CC) professional. While both are dedicated to the customer journey, their scope and focus often differ:

The CX Professional: Often owns the entire end-to-end customer journey, from marketing to product use to support. Their responsibilities and definition of success are deeply influenced by where CX sits organizationally — is it under Marketing, Operations, or the CEO?
The CC Professional: Focused on the operational efficiency, quality, and effectiveness of the voice and digital support channels. Their reality is one of doing a lot with a little, constantly asked to manage complex interactions while being, ironically, often looked to as a prime source of cuts in a downturn.

Social media, for instance, is still a relevant customer service channel, not just a marketing one. However, the operational reality is that many companies, looking for cost-effective solutions, outsource social media support to Business Process Outsourcing (BPO) providers, highlighting the ongoing tension between strategic experience design and operational efficiency.

“Being a CX leader in your industry is not a temporary investment you can cut and reinstate later. Those who cut, discover quickly that regaining customer trust and market position is exponentially harder than maintaining it.” — Braden Kelley

AI in the Contact Center: From Hypothesis to Hyper-Efficiency

The conversation inevitably turned to the single biggest factor transforming the industry today: Artificial Intelligence. Mario and I agreed that while the promise of AI is vast, the quickest, most immediate win for nearly every organization lies in agent assist.

This is where Generative AI tools empower the human agent in real-time — providing instant knowledge base look-ups, auto-summarizing previous interactions, and drafting responses. It’s a human-centric approach that immediately boosts productivity and confidence, improving Agent Experience (AX) and reducing training time.

However, implementing AI successfully isn’t a “flip-the-switch” deployment. The greatest danger is the wholesale adoption of complex technology without rigor. True AI success, Mario noted, must be implemented via the classic innovation loop: hypothesis, prototyping, and testing. AI isn’t a solution; it’s a tool that must be carefully tuned and validated against human-centered metrics before scaling.

The Mandate for Enduring Investment

A recurring theme was the strategic folly of viewing CX as a cost center. In a downturn, the contact center is often the first place management looks for budgetary reductions. Yet, the evidence is overwhelming: CX leadership is not a temporary investment. When you are leading in your industry in customer experience, that position must be maintained. Cut your investment at your peril, and you risk a long, painful road to recovery when the market turns. The CX team, despite being resource-constrained, often represents the last line of defense for the brand, embodying the human-centered change we preach.

As CCW moves into its next 25 years, the lesson is clear: customer expectations are only rising. The best leaders will leverage AI not just to cut costs, but to augment their people and apply the innovation principles of rigorous testing to truly master the new era of customer orchestration. The commitment to a great customer experience is the single, enduring investment that will future-proof your business.

Image credits: Customer Management Practice

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Google Gemini to clean up the article.

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The Voicebots are Coming

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Your Next Customer Support Agent May Not Be a Human

LAST UPDATED: October 27, 2025 at 1:00PM
The Voicebots are Coming

by Braden Kelley

Last week I had the opportunity to attend Customer Contact Week (CCW) in Nashville, Tennessee and learn that the familiar, frustrating tyranny of the touch-tone IVR (Interactive Voice Response) system is finally ending. For too long, the gateway to customer service has felt like a maze designed to prevent contact, not facilitate it. But thanks to the rapid evolution of Conversational AI — fueled by Generative Large Language Models (LLMs) — the entire voice interaction landscape is undergoing a revolutionary, and necessary, change. As a thought leader focused on human-centered change, innovation and experience design, I can tell you the future of the call center isn’t purely automated; it’s intelligently orchestrated.

The voicebot — the modern AI-powered voice agent — is moving past its days as a simple chatbot with a synthesized voice. Today’s AI agents use Natural Language Processing (NLP) to understand intent, context, and even tone, allowing them to handle complex, multi-step issues with startling accuracy. More importantly, they are ushering in the era of the bionic contact center, where the human agent is augmented, not replaced. This hybrid model — where AI handles the heavy lifting and humans provide empathy, complex reasoning, and necessary approvals — is the key to achieving both massive scale and superior Customer Experience (CX).

Overcoming the Voice Friction: The Tech Foundation

The shift to true voice AI required overcoming significant friction points that plagued older systems:

Barge-In and Latency: Modern voicebots offer near-instantaneous response times and can handle barge-in (when a customer interrupts the bot) naturally, mimicking human conversation flow.
Acoustic Noise: Advanced speech recognition models are highly resilient to background noise and varied accents, ensuring high accuracy even in noisy home or car environments.
Intent Nuance: LLMs provide the deep contextual understanding needed to identify customer intent, even when the customer uses vague or emotional language, turning frustrated calls into productive ones.

The Dual Pillars of Voice AI in CX

Conversational AI is transforming voice service through two primary deployment models, both of which reduce Customer Effort Score (CES) and boost Customer Satisfaction (CSAT):

1. Full Call Automation (The AI Front Line)

This model is deployed for high-volume, routine, yet critical interactions. The voicebot connects directly to the company’s backend systems (CRM, ERP, knowledge base) to pull personalized information and take action in real-time. Crucially, these new AI agents move beyond rigid scripts, using Generative AI to create dynamic, human-like dialogue that resolves the issue instantly. This 24/7 self-service capability slashes queue times and dramatically lowers the cost-to-serve.

2. Human-AI Collaboration (The Bionic Agent)

This is where the real human-centered innovation lies. The AI agent handles the bulk of the call — identifying the customer, verifying identity, diagnosing the problem, and gathering data. When the request hits a complexity threshold — such as requiring a policy override, handling an escalated complaint, or needing a final human authorization — the AI performs a contextual handoff. The human agent receives the call along with a complete, structured summary of the conversation, the customer’s intent, and often a recommended next step, turning a frustrating transfer into a seamless, empowered human interaction.

OR, even better can be the solution where a single human agent provides approvals or other guidance to multiple AI voice agents that continue owning their calls while waiting for the human to respond (possibly simultaneously helping the customer with additional queries) before continuing with the conversation through to resolution.

Customer Contact Week Nashville

“The most powerful application of voice AI isn’t automation, it’s augmentation. By freeing human agents from transactional drudgery, we elevate them to be empathic problem solvers, enhancing both their job satisfaction and the customer’s outcome.” — Braden Kelley

Measuring the Success of the Handoff

The quality of the transitions between AI and human is the true measure of success. Leaders must track metrics that assess the efficacy of the handoff itself:

Repeat Story Rate: The percentage of customers who have to repeat information to the human agent after an AI handoff. This must be near zero.
Agent Ramp-up Time (Post-Transfer): The time it takes for the human agent to absorb the AI-generated context and take meaningful action. Lower is better.
Post-Handoff CSAT: The customer satisfaction score specifically captured after a complex AI-to-human transfer, measuring the seamlessness of the experience.

The Agentic Future

The voicebots are indeed coming, and they are bringing with them the most significant shift in customer service since the telephone itself. The next evolution will see agentic AI — bots that can dynamically choose between multiple tools and knowledge sources to resolve novel problems without being strictly pre-scripted. The challenge for leaders is to ensure that as this technology scales, our focus remains firmly on the human experience, leveraging the best of AI’s speed and the best of human empathy to create a truly effortless and satisfying customer journey.

🤖 Companies to Watch in AI Voicebots

The voicebot space is rapidly evolving, driven by generative AI, and the recent Customer Contact Week (CCW) in Nashville highlighted several key players. Companies to watch in this generative AI voicebot and contact center space include market-leading platforms like NICE, Genesys, Zoom and Five9, all of whom are heavily integrating generative and agentic AI features—such as real-time coaching and automated post-call summaries — into their core Contact Center as a Service (CCaaS) offerings.

Beyond the traditional CCaaS providers, specialist AI firms like Replicant, Voice.AI and ASAPP (who had a significant presence at the event) continue to stand out by focusing on either full end-to-end voice automation for complex transactions or providing advanced Human-in-the-Loop AI features to augment live agents, particularly in regulated industries like financial services.

Additionally, major cloud vendors like Google Cloud and AWS (Amazon Connect) are increasingly aggressive, leveraging their foundational AI models to provide scalable, next-generation AI agents and contact center platforms, ensuring they remain transformative forces in customer experience (CX) automation.

Image credits: Customer Management Practice, Google Gemini

Content Authenticity Statement: The topic area, key elements to focus on, vendors to mention, etc. were decisions made by Braden Kelley, with a little help from Google Gemini to clean up the article.

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Why Putting Employees First and Customers Second Works

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Why Putting Employees First and Customers Second Works

GUEST POST from David Burkus

What if your company announced that, moving forward, it would be place customers second on its list of priorities?

Sounds crazy. The customer is always right. Surely the customer is always first as well.

But that’s exactly what Vineet Nayar, CEO of HCL Technologies did over a decade ago. He announced that the company’s senior leaders would be placing the needs of employees first, and customers second. And the results have been spectacular.

How The Employees First Strategy Started

In 2006, Vineet Nayar, CEO of HCL, a digital engineering company based in India, boldly told his clients they were no longer the company’s top priority. Instead, the focus would be put on employees first. His belief was simple: happy employees make happy customers. Nayar labeled employees who actually interacted with customers as the “value zone,” where the real business magic happens — and any employee in the value zone received the dedicated focus of managers and support functions.

To bring this to life, he flipped the traditional management structure. He made the organizational chart look like an upside-down pyramid. Turning the hierarchy upside down required making managers accountable to front-line employees and ensuring that those in the support functions actually supported those front-line employees, instead of just insisting that they follow the hierarchy’s rigid systems.

Nayar focused his attention on two areas to ensure that the management and support functions served the front-line: reversing accountability and building transparency. Specifically, 360-degree feedback evaluations were expanded to include more front-line workers’ feedback for managers and senior level executives (that’s the accountability), and crucially those evaluations were made public so everyone who contributed to the survey could see the results (there’s your transparency). In addition, when problems occurred for front-line workers, they could create and own support tickets that their managers would have to address (usually, it’s the other way around in top to bottom organizations).

It’s important to note that HCL Technologies wasn’t a little start up in a garage or even a 50-person company. This was done at a 55,000 person, multinational organization. And, spoiler alert, it’s now grown to over 200,000 employees. Pulling off this flip was no small feat, but the results speak for themselves. Employee satisfaction soared, customer service improved, and revenues nearly tripled. By 2009, HCL was named India’s best employer.

Contrast this story with an example of what can go wrong when employee experience is overlooked. In 2001, Robert Nardelli was the newly minted CEO of Home Depot. Expectations were high given his track record at his old job at General Electric, where he had led several successful manufacturing operations.

At Home Depot, Nardelli noticed the stores were staffed with knowledgeable, full-time employees, and in his opinion, a bit too many. What do new leaders, wrongfully, do when they want to make waves and save money?

Yep, he downsized to optimize costs.

He decided to hire more part-timers, many of whom had less expertise in home improvement. The results were not what he expected. Customers quickly noticed the absence of their favorite employees and the decline in service quality. It turned out that managing a service organization like Home Depot was very different from managing a manufacturing operation.

This story underscores a critical point: leading a service organization requires a different approach — one that prioritizes employee engagement and expertise.

“Employees first, customers second” is still about serving the customer, but it’s about serving the customer through the employees whose job it is to serve the customer. Weird how that works, isn’t it? Understand that helping your employees helps your customers. These two parties are intrinsically tied together.

Research On Employees First

Nayar’s success story isn’t an isolated incidence of dumb luck. There’s research behind this. Researchers at Harvard University found a link between employee satisfaction and profitability. They took aim at a long-standing assumption in the business world that market share is the primary driver of profitability. If a company can increase market share, the thinking went, it will increase sales while taking advantage of economies of scale to lower costs and thus increase profits.

However, when they examined a variety of companies and the existing research, they found that market share is one factor in profitability. But that another factor better explains the most profitable companies: customer loyalty.

Based on their research, they estimated that a mere 5 percent increase in customer loyalty can yield a 25 to 85 percent increase in profitability.

Here’s how it works in practice: Profits are driven by customer loyalty. Customer loyalty is driven by employee satisfaction. And employee satisfaction is driven by putting employees first. They called this The Service-Profit Chain and managers who understand this can create a thriving cycle where employee and customer satisfaction drive each other, ultimately leading to greater business success.

In simple terms, if your business provides a service that your employees have front-line participation in, they are in essence an embodiment of the company, not you or the CEO. The entire brand, the experience, the service rests on those front-line employees. If they aren’t taken care of — if they aren’t satisfied — the customer tends to notice.

How Employees First Creates Customer Loyalty

Employee loyalty is a deep indicator of future performance for service organizations. It’s worth noting that there is a subtle difference between employee satisfaction and employee loyalty. Satisfaction derives from how happy employees are in their role. Loyalty comes from having a real stake in the success of the business. Without loyalty, employees leave for better opportunities, then high turnover rates drive up recruitment and training costs, disrupt productivity, and can negatively impact customer experiences. When employees stay longer, companies save on hiring costs, maintain productivity gains, and create a more positive environment for customers.

Simply put, loyal employees lead to loyal customers.

Great service leaders recognize that improving employee retention involves providing opportunities for growth and advancement. This approach keeps talented employees closer to the customer for longer periods, which directly impacts customer satisfaction and loyalty.

Take Whole Foods Market, for example. They have crafted their entire system — from their rigorous selection process to compensation methods — to encourage front-line employees to stay and thrive. Teams at Whole Foods are responsible for setting key metrics, making decisions on how to meet these targets, and even choosing what food items to buy locally. They’re rewarded with bonuses based on team performance, which often includes finding creative ways to boost sales to balance out labor costs. After three years on the job, employees receive stock options, which further incentivizes them to stay.

Additionally, Whole Foods allows employees to vote every three years on various aspects of the benefits package, from community service pay to health insurance provisions. All these factors contribute to Whole Foods’ remarkably low turnover rate of less than 10 percent for full-time employees after the probationary period — far below the industry average.

The results speak for themselves: Whole Foods is regularly rated as one of the best places to work, known for excellent customer service, and boasts some of the highest profits per square foot in the grocery retail industry.

This success is a testament to the power of employee loyalty in driving exceptional service. Great service leadership isn’t just about managing day-to-day operations — it’s about creating an environment where employees feel valued, empowered, and committed. By focusing on employee loyalty, service leaders can build stronger customer relationships and achieve sustainable success.

Employees First For All Leaders

You may not have the power in your organization to completely flip the hierarchy. But there’s still an important lesson for leaders at all levels: Flip the accountability. This can look like bringing in more feedback from front-line employees or just seeing the structure of your team differently. You work for your team. Don’t squeeze your team; foster them to do well.

In addition, give your employees real stakes and invest in them. Prioritize training and growth opportunities for your employees so they know you’re committed to not just their output, but their career. Parties, gift certificates, awards, summer Fridays, bonuses — all of these are great. Do those things. But those are more employee appreciation, not real development. Development looks like sending your rising stars to conferences, workshops, night school even, if you have the budget. Things you think will help them grow as employees, spark innovation, and create future leaders.

Conclusion

If I could put a message on a billboard in front of every Fortune 500 company, it would be this:

People don’t work for you.

Smart leaders know that employees work with them, and ultimately, leaders work for their people. Embracing the “employees first, customers second” philosophy means prioritizing the well-being and growth of employees, enabling them to deliver outstanding service. Happy, engaged employees create satisfied customers. When leaders invest in their teams’ success and happiness, they cultivate a culture where customers feel valued, leading to long-term loyalty and a thriving business.

Image credit: David Burkus

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