Category Archives: Customer Experience

Creating Memorable Experiences to Drive Loyalty

Memory-Driven CX

Creating Memorable Experiences to Drive Loyalty

GUEST POST from Shep Hyken

Why do customers come back to the places where they love to do business? Our annual customer experience research ranked the top experiences that get customers to come back:

Helpful employees
Knowledgeable employees
Friendly employees
A convenient experience
Hassle-free shipping and delivery
Easy returns
Personalized experiences
Empathy

The decision to come back could include any one of these or a combination of items on this list — or anything else that the customer experiences the first or last time they did business with the company or brand. The point is that it’s not the experience itself that drives loyalty — it’s the memory of the experience that truly determines loyalty.

This subtle but powerful distinction explains why some businesses enjoy fierce loyalty. The customer’s memory creates an emotional connection that transforms a simple transaction into one of many interactions—in other words, a repeat and/or loyal customer. A recent MarTech article about creating these emotional connections through CX memories and how B2B and B2C brands are winning over customers with “memory-driven CX” included some compelling ideas that validate this concept. The article emphasized the power of a sentence that starts with the words, “Remember when. …” It turns out that the memory of a good experience can boost dopamine in the brain, and the result is that customers are more likely to trust and stay with the brand.

And that is the basis of an emotional connection. Dopamine is a chemical the brain releases that makes you feel good. This chemical release potentially happens twice: during the actual interaction with the brand and when the customer recalls the interaction at a later time and date.

This doesn’t happen by accident. Just as a brand can be purposeful about giving the customer an experience worthy of remembering, it can also be purposeful about getting the customer to recall the experience.

Certain companies have done this at scale. Chewy, the online pet supply retailer, sends birthday cards to its customers’ pets. The cards are often personalized with the pet’s name. Starbucks sends its “members” a free drink or food item for their birthday. It also celebrates “coffee anniversaries,” reminding customers of when they first joined its rewards program. Netflix sends a “What We Watched” summary of what its subscribers have watched in the past year.

You don’t have to be a recognizable brand to do this. Any size company—in any industry—can do the same with a little thought and this five-step process:

Create the Experience: First, you must deliver an experience that is positive and worth remembering.
Identify Key Touchpoints: Map the customer journey (if you haven’t already done so) and identify the key touchpoints that could have the highest emotional impact.
Enhance the Key Touchpoints: Once you’ve identified the impactful touchpoints, engineer them to become memorable. For example, Trader Joe’s, the grocery store chain, trains its employees to interact with customers when they check out, enthusiastically commenting about what’s in the customer’s cart. This last impression leaves a lasting impression.
Design a Follow-Up Campaign: Design a campaign similar to Chewy, Starbucks or Netflix that reminds the customer why they enjoy doing business with you.
Measure the Impact: Don’t assume the prior four steps are working. Ask or survey your customers to ensure you’ve created the “Remember When” experience that will help drive repeat business.

When customers are excited about their experience, they say, “I’ll be back.” Taking that to the next level is doing something that gets the customer to think back on the experience, creating a “Remember When” dopamine reaction moment. That reinforces the original (or last) experience the customer had with you. By deliberately creating experiences worth remembering and then helping customers remember those memories, you are increasing the chances of the customer coming back. And the more they come back, the more likely they are to become a coveted loyal customer.

Image credit: Pexels

This article originally appeared on Forbes.com

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It’s the Customer Baby!

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Bringing the Voice of the Customer Together with a Pursuit of Excellence

LAST UPDATED: November 19, 2025 at 9:37AM

It's the Customer Baby!

by Braden Kelley

One treat at Customer Contact Week (CCW) in Nashville recently was having the opportunity to see and hear basketball legend Dick Vitale. I can’t all share all of the stories here, but one thing that stuck with me from his musings were that the keys to a successful life are passion, preparation and perseverance.

Whether you are successful at anything you attempt is going to come down to your desire, dedication, determination and discipline. AND, guiding your life by eternally asking yourself the following question:

“Was I better today than I was yesterday?”

After Dick Vitale’s talk I attended a few other sessions throughout the day, including one of the Voice of the Customer (VOC) with Tisha Cole of Kenvue. Key session insights include:

The core theme emerging from the session centers on the strategic interpretation and deployment of Voice of the Customer (VOC) data to drive tangible business value. A critical finding is the frequent decoupling of customer sentiment metrics, like Net Promoter Score (NPS), and actual purchase behavior or revenue. This suggests a scenario where customers may express dissatisfaction yet remain “trapped” due to high switching costs or lack of viable alternatives, highlighting the need to look beyond simple scores. To move from raw data to action, organizations must focus on actionable data — tying survey results and other VOC sources to operational metrics to identify specific levers. Analyzing trending topics in sentiment and breaking down verbatims against people, process, and technology provides the necessary granularity to pinpoint the root cause of issues and determine which business function (HR, Finance, etc.) is responsible for influencing the relevant outputs and value drivers.

Effectively leveraging VOC insights also requires robust governance and communication strategies. A significant challenge is defining ownership of insights when multiple groups within an organization are collecting customer feedback, which can lead to fragmented or inconsistent action. To ensure that the data creates value, a Cascade Calendar approach is vital for sharing VOC insights with all relevant teams, facilitating meetings where the information can be discussed and acted upon. Furthermore, as organizations increasingly use AI to process vast amounts of unstructured data like customer recordings, the quality of the analysis depends on the input; utilizing prompts that stress “make no assumptions” can help ensure the AI extracts genuine, unbiased themes from advisory boards and other feedback sources.

🏀 Applying the Fundamentals to Customer Strategy

Ultimately, the challenge of leveraging Voice of the Customer (VOC) data — whether it’s overcoming the disconnect between NPS and revenue, ensuring ownership of insights, or setting up a Cascade Calendar for sharing — comes down to applying the fundamentals of passion, preparation, and perseverance.

The pursuit of truly actionable data requires the passion to look beyond easy vanity metrics and deeply analyze the roots of customer sentiment across people, process, and technology. It demands the preparation to integrate disparate VOC sources with operational metrics, ensuring you aren’t just collecting data but building genuine intelligence. And finally, it requires the perseverance to navigate organizational complexity, break down departmental silos, and consistently act on the insights, even when the required changes are difficult.

Just as Dick Vitale suggests we ask, “Was I better today than I was yesterday?”, organizations must ask themselves: “Was our customer experience better today than it was yesterday?” By dedicating your organization to the determination and discipline of VOC management, you move past simply tracking customer complaints and begin the continuous, dedicated process of making the customer experience undeniably “Diaper Dandy.”

Image credits: Customer Contact Week (CCW)

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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Don’t Adopt Artificial Incompetence

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Don't Adopt Artificial Incompetence

GUEST POST from Shep Hyken

I’ve been reviewing my customer experience research, specifically the section on the future of customer service and AI (Artificial Intelligence). A few findings prove that customers are frustrated and lack confidence in how companies are using AI:

In general, 57% of customers are frustrated by AI-fueled self-service options.
49% of customers say technologies like AI and ChatGPT scare them.
51% of customers have received wrong or incorrect information from an AI self-service bot.

As negative as these findings sound, there are plenty of findings that point to AI getting better and more customers feeling comfortable using AI solutions. The technology continues to improve quickly. While it’s only been five months since we surveyed more than 1,000 U.S. consumers, I bet a new survey would show continued improvement and comfort level regarding AI. But for this short article, let’s focus on the problem that needs to be resolved.

Upon reviewing the numbers, I realized that there’s another kind of AI: Artificial Incompetence. That’s my new label for companies that improperly use AI and cause customers to be frustrated, scared and/or receive bad information. After thinking I was clever and invented this term, I was disheartened to discover, after a Google search, that the term already exists; however, it’s not widely used.

So, AI – as in Artificial Incompetence – is a problem you don’t want to have. To avoid it, start by recognizing that AI isn’t perfect. Be sure to have a human backup that’s fast and easy to reach when the customer feels frustrated, angry, or scared.

And now, as the title of this article implies, there’s more. After sharing the new concept of AI with my team, we brainstormed and had fun coming up with two more phrases based on some of the ideas I covered in my past articles and videos:

Feedback Constipation: When you get so much feedback and don’t take action, it’s like eating too much and not being able to “go.” (I know … a little graphic … but it makes the point.) This came from my article Turning Around Declining Customer Satisfaction, which teaches that collecting feedback isn’t valuable unless you use it.

Jargon Jeopardy: Most people – but not everyone – know what CX means. If you are using it with a customer, and they don’t know what it means, how do you think they feel? I was once talking to a customer service rep who kept using abbreviations. I could only guess what they meant. So I asked him to stop with the E-I-E-I-O’s (referencing the lyrics from the song about Old McDonald’s farm.) This was the main theme of my article titled Other Experiences Exist Beyond Customer Experience (EX, WX, DX, UX and more).

So, this was a fun way at poking fun of companies that may think they are doing CX right (and doing it well), but the customer’s perception is the opposite. Don’t use AI that frustrates customers and projects an image of incompetence. Don’t collect feedback unless you plan to use it. Otherwise, it’s a waste of everyone’s time and effort. Finally, don’t confuse customers – and even employees – with jargon and acronyms that make them feel like they are forced to relearn the alphabet.

Image Credits: 1 of 950+ FREE quote slides available at http://misterinnovation.com

This article originally appeared on Forbes.com

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Re-engineering Trust and Retention in the AI Contact Center

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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

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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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