Author Archives: Braden Kelley

About Braden Kelley

Braden Kelley is a Human-Centered Experience, Innovation and Transformation consultant at HCL Technologies, a popular innovation speaker, and creator of the FutureHacking™ and Human-Centered Change™ methodologies. He is the author of Stoking Your Innovation Bonfire from John Wiley & Sons and Charting Change (Second Edition) from Palgrave Macmillan. Braden is a US Navy veteran and earned his MBA from top-rated London Business School. Follow him on Linkedin, Twitter, Facebook, or Instagram.

It’s the Customer Baby!

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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1,000+ Free Innovation, Change and Design Quotes Slides

LAST UPDATED: November 12, 2025 at 10:21AM
1,000+ Free Innovation, Change and Design Quotes Slides

Spice Up Your Meetings, Presentations, Keynotes and Workshops

I’m flattered that people have been quoting my keynote speeches and my first two books Stoking Your Innovation Bonfire and Charting Change (now in its Second Edition).

So, I’m making some of my favorite quotes available from myself and other thought leaders in a fun, visual, easily shareable format.

I’ve been publishing them on Instagram, LinkedIn, Facebook, and Twitter.

Find a compelling quote for a meeting, presentation, workshop or keynote speech on any of these topics:

  • Innovation
  • Design
  • Customer Experience
  • Digital Transformation
  • Change
  • Creativity
  • Leadership
  • Design Thinking

Download twenty (20) volumes of fifty (50) quote posters, for a total of 1,000 (with more on the way), for FREE from my store:

You can add them all to your shopping cart at once and download them for FREE.

Print them, share them on social media, or use them in your presentations, keynote speeches or workshops.

They are all Adobe PDF’s and the best way to add them to your presentation is to:

  1. Put the PDF into FULL SCREEN MODE
  2. Take a screenshot
  3. Paste it into your presentation
  4. Crop it and adjust the size to your liking
  5. Change the background color of the slide to a suitable color (if necessary)

Contact me with your favorite quote or to book me for a keynote, workshop, or piece of commissioned content to attract new customers.

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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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How to Make Your Employees Thirsty

LAST UPDATED: November 5, 2025 at 5:11PM

How to Make Your Employees Thirsty

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 what Shantel Love had to say about the importance of keeping employee engaged as artificial intelligence (AI) starts to take over, and a framework she shared that can help you do so.

Shantel spoke about how Gallup statistics show that for U.S. employees in early 2025, 31% are engaged, 17% are actively disengaged, and 52% are not engaged. This reflects a decade-low engagement level, with active disengagement also at 2014 levels. The global cost of disengagement is estimated at $8.8 trillion annually, or about 9% of global GDP. These statistics are shocking. Do you think they represent reality? If not, leave a comment below supporting your dissent.

Shantel also spoke about how employee disengagement can seep into your profits, customer experience and culture, and that while you can lead a horse to water, you can’t make it drink, but you can make it thirsty. Right on queue comes in Shantel’s WATER framework, for which I have summarized some of the key insights for each of the key components below.

Work That Matters

  • Does anyone even care about this?
  • 70% of employees disengage because they can’t connect their work to purpose (World Economic Forum)
  • If your team disappeared tomorrow, what would the business lose?
  • Write down what the business would lose and tell your team to give them the why (their value and their purpose)

AI as an Accelerator not a threat

  • AI won’t replace you but it will replace the invisible employee
  • Employees are still left with the work that nobody notices
  • As an exercise, ask AI to take your last big project and rewrite it in language that makes your leadership visible
  • How can I make our customer sentiment visible to leadership? (inputting the sentiments with this AI prompt)

Transparency and Trust

  • Disengagement is a hidden problem – a profit leak
  • “Psychological safety is the strongest predictor of innovation across distributed teams.” (MIT Sloan)
  • People don’t leave a company, they leave a manager – 70% of disengagement starts at the manager level – Managers account for 70% of the variance in team engagement (Is the real point this second one?) — Gallup
  • What is one belief my team or customer needs restored right now? (transformation you will lead – what you will act on)

Embrace Personal Branding

  • Most organizations believe that if you encourage your employees to invest in their personal brand, then they are going to leave
  • Most people achieve less than 20% of their true potential (Forbes)
  • 73% of social media managers say employee post have double the engagement of regular business posts, and 26% say employees triple brand engagement (GaggleAMP)
  • The biggest room in the world is the room for improvement

Recognition That’s Real

  • “79% of employees quite because they feel underappreciated.” (OC Tanner research)
  • You made an impact this week because …

It goes without saying that if you lead your employees to WATER you will find them more engaged (meaning they are no longer disengaged) and as a result they will be of greater service to your customers, and by extension your shareholders. Employee engagement matters, and the pursuit of it by your managers will not only create better leaders, but it will also engage your managers. So, are you ready to give your employees a drink of WATER or are going to insist on keeping them thirsty?

Image credits: Customer Management Practice (CMP)

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Why Going AI Only is Dumb

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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Measuring Human vs. AI Satisfaction

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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The Indispensable Role of CX

Insights from CCW’s 25-Year Journey

LAST UPDATED: October 28, 2025 at 12:00PM
The Indispensable Role of CX

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.

Mario MatulichThis 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.

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

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

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.

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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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The Marketing Guide for Humanity’s Next Chapter

How AI Changes Your Customers

Exclusive Interview with Mark Schaefer

Mark W Schaefer

LAST UPDATED: October 1, 2025 at 12:00PM

The rise of artificial intelligence isn’t just an upgrade to our technology; it’s a fundamental shift in what it means to be human and what it takes to lead a successful business. We’ve entered a new epoch defined by “synthetic humanity,” a term coined by Mark Schaefer to describe AI interactions that are indistinguishable from real human connection. This blurring of lines creates an enormous opportunity, which Mark Schaefer refers to as a “seam” — a moment of disruption wide open for innovators. But as algorithms become more skilled at simulating empathy and insight, what must leaders do to maintain authenticity and relevancy? In this exclusive conversation, Mark Shaefer breaks down why synthetic humanity is the most crucial concept for leaders to grasp today, how to use AI as a partner rather than a replacement, and the vital role of human creativity in a world of supercharged innovation.

The Internet, Smartphones, Social Media, and Now AI, Have All Shifted Customer Expectations

Mark Schaefer is a globally-acclaimed author, keynote speaker, and marketing consultant. He is a faculty member of Rutgers University and one of the top business bloggers and podcasters in the world. How AI Changes Your Customers: The Marketing Guide to Humanity’s Next Chapter is his twelfth book, exploring what companies should consider when it comes to artificial intelligence (AI) and their customers.

Below is the text of my interview with Mark and a preview of the kinds of insights you’ll find in How AI Changes Your Customers presented in a Q&A format:

1. I came across the term ‘synthetic humanity’ fairly early on in the book. Why is this concept so important, and what are the most important aspects for leaders to consider?

“Synthetic humanity” is my term for describing the emerging wave of AI interactions that appear, sound, and even feel human — yet are not human at all. This is not science fiction. Already, chatbots can hold natural conversations, generate art, or simulate empathy in ways that blur the line between authentic and artificial.

For leaders, this matters because customers don’t care whether an experience is powered by code or carbon; they care about how it feels. If synthetic humanity can deliver faster, easier, and more personalized service, people will embrace it. The more machines convincingly mimic us, the more vital it becomes to emphasize distinctly human qualities like compassion, vulnerability, creativity, and trust.

Leaders must navigate two urgent questions: Where do we lean into automation for efficiency? And where do we intentionally preserve human touch for meaning? Synthetic humanity can scale interactions, but it cannot scale authenticity. The most successful brands will be those that strike this balance — leveraging AI’s strengths while showcasing the irreplaceable heartbeat of humanity.

2. We discuss disruption quite a bit here on this blog. Can you share a bit more with our innovators about ‘seams’ and the opportunities they create with AI or otherwise?

Throughout history, disruptions to the status quo, such as pandemics, wars, or economic recessions, can either sink a business or elevate it to new heights. Every disruption creates a seam — a moment where the fabric of culture, business, or belief rips just wide enough for an innovator to crawl through and create something new.

We might be living in the ultimate seam.

Google CEO Sundar Pinchai calls AI the most significant innovation in human history — more important than fire, medicine, or the internet. The power of AI seems absolute and threatening. For many, it’s terrifying.

Through my new book, I’m trying to get people to view disruption through a different lens: not fear, but immense possibility.

3. Given that AI has access to all of our accumulated wisdom, does it actually create unique insights and ideas, or will innovation always be left to the humans?

AI is extraordinary at remixing existing content. It can scan millions of data points, connect patterns we might miss, and surface possibilities at lightning speed. That feels like insight, and sometimes it is. However, there is a crucial distinction: AI doesn’t truly care. It lacks context, longing, and lived experience.

Innovation often begins with a problem that aches to be solved or a vision that comes from deep within human culture. AI can suggest ten thousand options, but only a person can say, “This one matters because it touches our values, our customers, our future.”

So the real power is in the partnership. AI accelerates discovery, clears away routine work, and even provokes us with new connections. Humans bring the spark of meaning, the intuition, and the courage to act on something that has never been tried before. Innovation is not being replaced. It is being supercharged. In my earlier book “Audacious: How Humans Win in an AI Marketing World,” I note that the bots are here, but we still own crazy!

This is a time for humans to transcend “competent.” Bots can be competent and ignorable.

4. Do you have any tips for us mere mortals on how to productively use AI without developing creative and intellectual atrophy?

Yes, and it starts with how you frame the role of AI in your life. If you treat it as a replacement, you risk letting your creative muscles go slack. If you treat it as a partner, you can actually get stronger.

Here are a few practical approaches. First, use AI to stretch your perspective, not to finish your work for you. Ask it to give you ten angles on a problem, then choose one and make it your own. Second, set boundaries. Write your first draft by hand or sketch ideas before you ever touch a prompt. Let AI react to your thinking, not define it. Third, use the tool to challenge yourself. Feed it your work and ask, “What am I missing? Where are my blind spots?”

Most importantly, keep doing hard things. Struggle is where growth happens. AI can smooth the path, but sometimes you need the climb. Treat the technology as a coach, not a crutch, and you will come out sharper, faster, and even more creative on the other side.

5. I’ve heard a little bit about AI literacy. What are some of the critical aspects that we should all be aware of or try to learn more about?

How AI Changes Your Customers' MarketingThere are a few critical aspects everyone should know. First, bias. AI models are trained on human data, which means they inherit our blind spots and prejudices. If you don’t recognize this, you may mistake bias for truth. Second, limits. AI is confident even when it is wrong. Knowing how to fact-check and verify is essential. Third, prompting. The quality of your input shapes the quality of the output, so learning how to ask better questions is a new core skill.

Finally, ethics. Just because AI can do something does not mean it should. We all need to be asking: How does this affect privacy, autonomy, and trust?

AI literacy isn’t about becoming a coder. It is about being a thoughtful user, a skeptic when needed, and a leader who understands both the promise and the peril of these tools.

6. What do companies and sole proprietors worried about falling below the fold of the new AI-powered search results need to change online to stay relevant and successful?

I have many practical ideas about this in the book. In short, the old game of chasing clicks and keywords is fading. AI-powered search doesn’t just list links, it delivers answers. That means the winners will be those whose content and presence are woven deeply enough into the digital fabric that the algorithms can’t ignore them.

This requires a shift in focus. Instead of creating content that only ranks, create content that is referenced, cited, and trusted across the web. Build authority by being the source others turn to. Make your ideas so distinct and valuable that they become part of the training data itself. We are entering a golden age for PR!

It also means doubling down on brand signals that AI can’t manufacture. Human stories, original research, strong communities, and unique perspectives will travel farther than generic blog posts. And remember, AI models reward freshness and relevance, so showing up consistently matters.

The book also covers what I call “overrides.” If you create a meaningful, loyal relationship with customers and word of mouth recommendations, that will override the AI recommendations. We consider AI recommendations. We ACT on human recommendations.

7. ‘Weaponizing kindness’ was a terrifying headline I stumbled across in your book. What do organizations need to consider when using AI to interact with customers and what traps are out in front of them?

That phrase is unsettling for a reason. AI can mimic empathy so well that it risks crossing into manipulation. Imagine a chatbot that remembers your child’s name, mirrors your mood, or expresses concern in just the right tone. Done responsibly, that feels like service. Done carelessly, it feels like exploitation.

Organizations need to recognize that kindness delivered at scale is powerful, but if it is hollow or purely transactional, customers will sense it. The first trap is confusing simulation with sincerity. Just because an AI can sound caring does not mean it actually cares. The second trap is overreach. Using personal data to create hyper-tailored interactions can quickly slip from helpful to creepy.

The safeguard is transparency and choice. Be clear about when a customer is interacting with AI. Use technology to enhance human care, not replace it. Always provide people with a way to connect with a real person.

Kindness is a sacred trust in business. Weaponize it, and you erode the very loyalty and love you are trying to build. Use it authentically, and you create relationships no machine can ever replicate.

8. What changing customer expectations (thanks to AI) might companies easily overlook and pay a heavy price for?

One of the biggest shifts is speed. Customers already expect instant answers, but AI raises the bar even higher. If your competitor offers a seamless, AI-powered interaction that solves a problem in seconds, your slower, clunkier process will feel intolerable.

Another overlooked expectation is personalization. People are starting to experience products, services, and recommendations that feel almost eerily tailored to them. That sets a new standard. Companies still delivering one-size-fits-all communication will look outdated. Don’t confuse “personalization” with “personal.”

Perhaps the most subtle change is trust. As customers realize machines can fake warmth and empathy, they will value genuine human touch even more. If every interaction feels synthetic, you risk losing trust, especially if you’re not transparent about it.

The price of ignoring these shifts is steep: irrelevance. Customers rarely complain about unmet expectations anymore; they simply leave. The opportunity is to stay alert, listen closely, and respond quickly as AI reshapes what “good enough” looks like. The companies that thrive will be those that not only keep pace with AI, but also double down on the irreplaceable humanity customers still crave.

9. What unintended consequences of AI do you think companies might face and may not be preparing for? (overcoming AI slander and falsehoods might be one – agree or disagree? Others?)

I agree. In fact, I predict in the book that we cannot foresee AI’s biggest impact yet, as it will likely be an unintended consequence of the technology’s use in an unexpected way.

Where could that occur? Maybe reputational risk at scale. AI systems will generate falsehoods with the same confidence they generate facts, and those errors can stick. A single hallucination about your company, repeated enough times, becomes “truth” in the digital bloodstream. Most companies are not prepared for the speed and reach of misinformation of this kind.

Another consequence is customer dependency. If people hand over more of their decisions to AI, they may lose patience for complexity or nuance in your offerings. That can push companies toward oversimplification, even when a richer human experience would build deeper loyalty.

There is also the cultural risk. Employees might over-rely on AI, quietly eroding skills, judgment, and creativity. A workforce that outsources too much thinking can become brittle in ways that only show up during a crisis.

The real challenge is that these consequences don’t announce themselves. They creep in. Which means leaders must actively audit how AI is being used, question where it might distort reality or weaken capability, and set up safeguards now. The companies that prepare will navigate disruption. The ones that ignore it will be blindsided.

10. Can companies make TOO MUCH use of AI? If so, what would the impacts look like?

Yes, and we will start seeing this more often. It is a pattern that has repeated through history — over-indexing on tech and then bringing the people back in!

When companies lean too heavily on AI, they risk draining the very humanity that makes them memorable. On the surface, it might seem like efficiency: faster service, lower costs, and greater scale. But underneath, the impacts can be corrosive. You might be messing with your brand!

Customers may feel manipulated or devalued if a machine drives every interaction. Even perfect personalization can feel hollow if it lacks genuine care. Second, trust erodes when people sense that a brand hides behind automation rather than showing up with real human accountability. Third, within the company, over-reliance on AI can weaken employee judgment and creativity, resulting in a workforce that follows prompts rather than breaking new ground.

The real danger is commoditization. If every company automates everything, then no company stands out. The winners will be those who know when to say, “This moment deserves a person.” AI should be an amplifier, not a replacement. Too much of it and you don’t just lose connection, you lose your soul.

Conclusion

Thank you for the great conversation Mark!

I hope everyone has enjoyed this peek into the mind of the man behind the inspiring new title How AI Changes Your Customers: The Marketing Guide to Humanity’s Next Chapter!

Image credits: BusinessesGrow.com (Mark W Schaefer)

Content Authenticity Statement: If it wasn’t clear above, the short section in italics was written by Google’s Gemini with edits from Braden Kelley, and the rest of this article is from the minds of Mark Schaefer and Braden Kelley.

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You Just Got Starbucked

Layoffs, Store Closures & What It Means for Customer Service

LAST UPDATED: September 25, 2025 at 10:58PM
You Just Got Starbucked - Layoffs, Store Closures & What It Means for Customer Service

Exclusive Interview with Mario Matulich

In a world where corporate decisions often prioritize efficiency, the human element can be the first to suffer. The recent layoffs and restructuring at Starbucks, a brand synonymous with a unique, human-centered “third place” experience, have sent a tremor through the industry. In a wide-ranging interview, we will unpack the strategic and operational implications of these changes. Together, we will explore the difficult balance between trimming corporate fat and maintaining a brand built on emotional connection, diving into how these decisions could affect everything from in-store morale to the long-term loyalty of its customers. Central to the conversation is the following strategic question:

How can a company that has undergone significant corporate restructuring and layoffs maintain and restore a premium, human-centered customer experience?

Mario MatulichToday we will explore this question, along with its various aspects with our special guest Mario Matulich, a practice lead at the Customer Management Practice with a diverse commercial understanding in a variety of industry verticals across the customer management sector. He is well versed in market research, product development, sales, marketing, and operations in addition to cross functional management and leadership development.

Without further ado, here is the Q&A I had with Mario on a range of topics regarding the recent Starbucks’ store closures and layoffs and their implications:

The Strategic Context of the Layoffs

Q: Starbucks’ leadership framed the recent restructuring as a necessary step for efficiency and a return to their core mission. From your perspective in customer management, how do these internal changes directly affect the external customer experience in the short and long term?
A: In the short term, layoffs, especially in corporate roles, can create gaps in innovation, brand narrative, and strategic support for store-level teams. Employees on the front lines may feel increased pressure, which can impact morale and the human connection customers expect. In the long term, if these gaps aren’t addressed, the result can be a more transactional experience that erodes both loyalty and trust.

Q: In many companies, layoffs are a last resort. Do you believe this restructuring reflects a failure of previous strategies, or is it a forward-thinking move to adapt to a changing market? What specific market trends do you think are driving these decisions?
A: I don’t view this restructuring as purely a failure of previous strategies, but rather as an attempt to adapt to a changing market. That said, Starbucks’ bigger challenge is restoring its customer experience. Trends such as rising demand for personalized, convenient, and high-value experiences, along with increased competition in the premium coffee market, make it clear that customers are evaluating Starbucks not just on price, but on the overall experience delivered.

Q: The layoffs primarily targeted corporate roles in marketing, technology, and creative. How does the loss of talent in these specific areas impact the company’s ability to innovate and maintain its brand narrative?
A: These areas are critical for innovation, storytelling, and digital experiences that connect customers to the brand. Losing talent here makes it more challenging to maintain a consistent, differentiated experience and risks further disengagement from customers.

Impact on the Human-Centered Experience

Q: Starbucks has long prided itself on the “third place” concept. How does restructuring and potential employee demoralization affect the in-store experience and the emotional connection customers have with the brand?
A: The “third place” experience relies on motivated and supported employees. Restructuring can disrupt this, as uncertainty and low morale may trickle down to in-store interactions. Customers may perceive a decline in warmth, attentiveness, and consistency, which can undermine the emotional connection.

Q: With fewer people in corporate roles, who now owns the responsibility for a seamless customer journey? Does this push more responsibility onto store-level partners, and if so, are they equipped to handle it?
A: While partners remain at the front line, the burden shouldn’t fall solely on them. Leadership must provide tools, guidance, and support to ensure a seamless experience, even as corporate teams shrink.

Q: Customer management is about building long-term loyalty. Do you believe this restructuring risks eroding the trust and loyalty of both employees and customers, and what would your practice recommend to mitigate that risk?
A: Yes, there’s definitely a risk. The key is to go back to the basics and make the experience personal, easy, and fast. Nail those, and customers’ trust and loyalty will .,¬./come back, and the layoffs won’t linger in their minds.

Measuring and Recovering from the Impact

Q: How would you advise Starbucks to measure the real-time impact of these changes on customer satisfaction? Beyond traditional metrics like NPS, what holistic experience measures should they be tracking?
A: Starbucks should look beyond NPS to measure speed of service, personalization, emotional connection, and overall experience consistency. These metrics provide a more comprehensive view of the customer journey and help identify gaps that layoffs may create.

Q: Layoffs can create a perception of instability. What is the most effective way for a company to communicate its recovery plan and rebuild confidence with its customer base after such a significant change?
A: Clear communication focused on restoring the core pillars of customer experience, personalization, ease, and speed, is key. Customers respond when they see tangible improvements in the experience they receive every day.

Q: In your experience, what is the typical timeline for a company to recover from the brand and cultural damage that can follow widespread layoffs? What are the critical milestones they should be focused on achieving?
A: Recovery timelines vary, but visible improvements in customer experience can begin within months if executed strategically. Critical milestones include reestablishing operational consistency, restoring employee morale, and relaunching key brand initiatives that reinforce the premium experience promise.

Future-Proofing for Long-Term Growth

Q: Looking ahead, how can Starbucks utilize this moment of disruption to adopt a more resilient and human-centered organizational model? What key lesson should other companies learn from their experience to avoid similar pitfalls?
A: Starbucks has a chance here to get back to what really made it successful: combining innovative, tech-forward solutions with a human touch, every time. The bigger lesson for any company is clear. Growth and cost-cutting shouldn’t come at the expense of the customer experience. People are willing to pay a premium, but only if the experience feels worth it.

Q: What message does it send that the popular Starbucks Roastery location in Capitol Hill in Seattle is being closed as part of this layoff and restructuring initiative? Why do you think they chose to do it?
A: Closing the Roastery signals a prioritization of efficiency over experiential destinations. While it may make financial sense in the short term, it also serves as a cautionary reminder that iconic, high-touch experiences are critical to maintaining brand differentiation and customer loyalty.

Conclusion

Thank you for the great conversation Mario!

Ultimately, the Starbucks case study is a powerful lesson for every organization. As Matulich’s insights make clear, the pursuit of efficiency and growth cannot come at the expense of the human experience that defines your brand. The true measure of a company’s resilience is not in its stock price, but in the trust it has built with its employees and customers. A single-minded focus on traditional metrics is insufficient; a holistic approach that values emotional connection and employee morale is the only path to sustainable growth. The greatest challenge for Starbucks now is to move beyond reacting to a difficult market and begin proactively shaping its future—not just through cost-cutting, but by recommitting to the core narrative that made it a cultural institution in the first place. The future of any business is not found in a spreadsheet; it’s built on a foundation of human connection, one interaction at a time.

Image credits: Pexels, Mario Matulich

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