Customer Experience Audit for B2B SaaS

What Makes This Journey Different

by Braden Kelley and Art Inteligencia

Most customer experience frameworks are written with a single decision-maker in mind — one person, one moment of dissatisfaction, one chance to leave. B2B SaaS almost never works that way, and an audit approach borrowed from consumer retail will miss most of what actually matters in a software buying and renewal relationship.

The journey has more than one customer in it

A single SaaS account often includes a buyer who approved the budget, an admin who configured the product, and a set of end users who never spoke to sales at all and may not even know your company name. Each of these roles experiences a completely different journey, forms a completely different opinion, and has completely different influence over renewal. An audit that only interviews the buyer — the person easiest to reach — misses the end users whose day-to-day frustration is often what actually drives churn, quietly, long before a renewal conversation happens.

Onboarding failures don’t show up until months later

In consumer contexts, a bad first experience usually shows up immediately — a return, a one-star review, a quick churn. In B2B SaaS, a confusing onboarding often doesn’t kill the relationship on day one. It just means the product never gets adopted the way it was sold to be used, usage stays shallow, and the account quietly becomes a non-renewal a year later for reasons that trace directly back to week one. Walking the onboarding journey firsthand — not reviewing the onboarding flowchart, but actually going through it as a new user would — is where this kind of audit consistently finds the most expensive gaps.

Support tickets are a lagging indicator, not a leading one

By the time a SaaS customer files a support ticket, they’ve usually already tried to solve the problem themselves, asked a colleague, checked the help docs, and given up more than once. The ticket is the tip of a much larger iceberg of friction that a support-ticket dashboard alone will never show you. This is exactly why data evaluation in an audit has to be paired with firsthand journey walking — the tickets tell you what people were frustrated enough to report; the journey walk tells you everything they weren’t.

Expansion revenue depends on trust building quietly in the background

Upsell and cross-sell in SaaS rarely happen through a single sales conversation — they happen because a champion inside the account has quietly built confidence in the product over months of ordinary use. Every piece of friction in that ordinary use is a small tax on that trust, invisible individually, but cumulative. An audit that maps the full post-sale journey — not just the support-facing parts — is usually where the connection between “small usability annoyance” and “expansion revenue we didn’t get” becomes visible for the first time.

Competitive benchmarking means something different here

In B2B SaaS, your real competitive benchmark often isn’t your closest direct competitor — it’s the best onboarding flow or support experience your buyer has encountered anywhere in their software stack. B2B buyers import their expectations from whatever consumer-grade product experience they use daily, which means “good enough” is a moving target set well outside your own category.

Where to start

If any of this sounds like it’s describing gaps you suspect exist but haven’t confirmed, the Customer Experience Revenue Leakage Self-Assessment is a good first step to see where your own program stands across the five core audit activities. From there, a Customer Experience Audit scoped specifically to a multi-stakeholder SaaS journey — buyer, admin, and end user — finds what a single-persona review structurally can’t.

Download the Customer Experience Audit Checklist as a PDFImage Credits: Pexels

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

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The Revenue Hiding In Plain Sight

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The Revenue Hiding In Plain Sight

by Braden Kelley and Art Inteligencia

Why your gut already knows something’s wrong, and how to finally prove it.

You’ve seen it before. The numbers look okay on paper, but something just doesn’t feel right. Churn is creeping up. Conversions aren’t where they should be. Your support team is busier than ever. Yet, when you dig into the dashboards, nothing is jumping out and screaming for your attention.

So, like so many leaders do, you wait. You hope it’s a blip. You tell yourself the team will course correct. But deep down, you already know what’s really going on… Your customers are quietly voting with their feet.

Here’s the hard truth: The biggest threats to your revenue aren’t always obvious. They’re hiding in the frustrating onboarding flow your team has grown numb to. They’re buried in the clunky renewal process that only your customers seem to notice. They’re tucked away in the dozen micro-moments of friction you’ve accepted as “just the way things are.”

If You Can’t See It, You Can’t Fix It

For years, we’ve obsessed over measuring sentiment. NPS, CSAT, and star ratings all have their place. But as an experience designer, I can tell you this: sentiment doesn’t always open up a spreadsheet. Revenue does.

The problem is, most organizations don’t have a way to connect those frustrating customer moments to the bottom line. The result? CX initiatives get deprioritized, underfunded, or worse… they become shelfware because leaders can’t see the business case to act.

That’s exactly why I created the CX Revenue Leak Self-Assessment.

Five Minutes To Clarity

This isn’t just another survey. It’s a reality check for growth-minded leaders. In just five minutes, you’ll answer seven pointed questions about churn, conversions, support costs, renewals, customer sentiment, visibility, and your team’s ability to act. What you get in return is immediate clarity.

You’ll walk away with a Leak Score that tells you if you’re in a low, medium, or high-risk category, a laser-focused tip you can act on today, and a clear path forward. No email gate to get your results. No fluff. Just the truth about where your revenue is at risk.

So, if that nagging feeling hasn’t gone away, don’t ignore it. Take the CX Revenue Leak Self-Assessment right now and finally put a number to what your gut has been trying to tell you.

From “How Bad Is It?” To “How Much Can We Recover?”

Once you know where the leak is coming from, the next logical question is always, “how much is this actually costing us?” That’s where our CX ROI Calculator comes in. It’s the perfect companion to your results, helping you model a realistic, defensible range of recoverable revenue in seconds. It’s not the focus, but it’s the tool that will get your CFO nodding their head.

When You Need More Than a Quick Fix

Sometimes, a tip and a number are enough to get the ball rolling. Other times, you need to go deeper. You need to uncover the root cause of that leak, prioritize what to do first, and build a roadmap your team will actually adopt. Not one that collects dust.

That’s the heart of our independent Customer Experience Audit. It’s built on a simple belief: human-centered change only works when it’s paired with a business case that’s undeniable. That’s why we don’t just hand you a report, we deliver a 3-week action plan with effort vs. impact and estimated revenue lift for each of your top priorities.

The Cost of Waiting Is Greater Than You Think

Every day you wait to address that friction is another day of lost revenue you won’t get back. The good news? You don’t have to boil the ocean to make progress. You just need to start by shining a light on your biggest leak.

So, do what great leaders do. Get curious. Get clarity. Then, get moving.

Start Your 5-Minute Assessment Now

Your customers are already telling you something. It’s time to hear what their actions are saying about your revenue.

Image Credits: Microsoft AI

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

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Never Trust a Guru

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Never Trust a Guru

GUEST POST from Greg Satell

In 2005 W. Chan Kim and Renée published Blue Ocean Strategy, which found that “blue ocean” launches, those in new categories without competition, far outperformed the shark-infested “red ocean” line extensions that are the norm in the corporate world. It was an immediate hit, selling over 3.5 million copies.

Bain consultants Chris Zook and James Allen’ published, Profit from the Core, around the same time. They found that firms that focused on their ”core” far outperformed those who strayed. For example, they warned that Amazon was putting itself from peril for expanding its business beyond books and predicted dire results.

Clearly, none of this makes sense. How can you both “focus on your core” and seek out “blue oceans?” It betrays logic that both strategies could outperform one another. Today, Amazon makes most of its money outside of books. Yes, new markets lack competitors, but they also lack customers. The truth is that most business research is surprisingly shoddy.

Cargo Cult Science

When Richard Feynman took the podium to give the commencement speech at CalTech in 1974, he told the strange story of cargo cults. In certain islands in the South Pacific, he explained, tribal societies had seen troops build airfields during World War and were impressed with the valuable cargo that arrived at the bases.

After the troops left, the island societies built their own airfields, complete with mock radios, aircraft and mimicked military drills in the hopes of attracting cargo themselves. It seems more than a little silly, and of course, no cargo ever came. Yet these tribal societies persisted in their strange behaviors.

Feynman’s point was that we can’t merely mimic behaviors and expect to get results. To illustrate what he meant, he told a story about going to a new-age resort where people were learning reflexology. A man was sitting in a hot tub rubbing a woman’s big toe and asking the instructor, “Is this the pituitary?” Unable to contain himself, the great physicist blurted out, “You’re a hell of a long way from the pituitary, man.”

What makes science real is not fancy sounding words or slick charts with numbers on them. Business gurus often boast of their “research” that consists of hundreds of case study interviews and large databases containing data on thousands of firms, but without the proper methods and controls, those things are meaningless.

The Problem With Case Studies

Organizations are often inscrutable and hard to research. That’s why the preferred mode of analysis is case studies in which insiders are interviewed and a particular situation is interpreted by investigators. These can be helpful, but they also have severe limitations.

First, with shareholders and customers to please, managers are rarely eager to talk about failures. So we usually only hear about successes. Those, of course, are important but also subject to survivorship bias. For example, if a risky strategy results in 1% of the firms being wildly successful and 99% going out of business, then we’ll tend to hear glowing accounts of that lucky 1% and we’ll miss the vast majority that flamed out.

Another issue with the case study method is that it is necessarily limited. When researchers did a case study on a company I used to run, to take just one example, they interviewed insiders (including me) and did their best to interpret what they heard and what they could glean from background information regarding the market.

While I don’t think anything was inaccurate, it wasn’t exactly the truth either. Only a handful of people were interviewed, almost all of them were concentrated in a single part of the business and none of them, besides me, were involved in making decisions. The issues presented in the case study simply weren’t the ones we were actually wrestling with.

The problem with case studies is that they offer little to no documentation. In more rigorous fields like, say, sociology or psychology, researchers are expected to share their data so that others can interpret it. Unfortunately, that’s rarely true in business research.

Working Around The Glitches In Our Brains’ Machinery

We tend to imagine that our minds are some sort of machines, recording what we see and hear, then storing those experiences away to be retrieved at a later time, but that’s not how our brains work at all. Humans have a need to build narratives. We like things to fit into neat patterns and fill in the gaps in our knowledge so that everything makes sense.

Psychologists often point to a halo effect, the tendency for an impression created in one area to influence opinion in another. For example, when someone is physically attractive, we tend to infer other good qualities and when a company is successful, we tend to think other good things about it.

The truth is that our thinking is riddled with subtle yet predictable biases. We are apt to be influenced not by the most rigorous information, but what we can most readily access. We make confounding errors that confuse correlation with causality and then look for information that confirms our judgments while discounting evidence to the contrary.

Unfortunately, so many of the popular management ideas today come from people who never actually operated a business, such as business school professors and consultants. These are often people who’ve never failed. They’ve been told that they’re smart all their lives and expect others to be impressed by their ideas, not to examine them thoroughly.

That’s why it’s so important to not to believe everything you think, there are simply too many ways to get things wrong and so few ways to get things right.

It’s More Important To Be Careful Than Smart

When I lived in Poland, a common aphorism advised that “life is cruel, and full of traps.” From an American perspective, the aphorism can be a bit of a culture shock. We tend to believe in the power of positivity, the American dream and the can-do spirit. Negativity can be seen as something worse than a weakness, both an indulgence and a privation at the same time.

Over the years, however, I came to respect the Poles’ innate suspicion. The truth is that we are far too easily fooled and taken in by those prey on the glitches in our cognitive machinery. Often business gurus have fooled themselves. They believe they have special powers of insight and get taken in by the glitches we all have in our mental machinery.

We get taken in because we want their claims to be true. We’d like to think that there is a secret we’re missing, that there’s a black magic that we’re not privy to and, if we prove our worth and obtain access to a few simple truths, we’ll capture the success that eludes us. Things can seem simple in a PowerPoint deck, but the truth is that the world is a messy place.

That’s why we need to train ourselves to ask the tough questions. What are we not seeing? What data is missing? What are alternative interpretations for the evidence being presented? It’s more important to be careful than smart. We can only make decisions on higher or lower levels of confidence. In the real world, there are no “sure things.”

— Article courtesy of the Digital Tonto blog
— Image credit: Pexels

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How to Lead Cross-Functional Teams Without Cracking

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How to Lead Cross-Functional Teams Without Cracking

GUEST POST from David Burkus

You’ve just been asked to lead a new team. But here’s the catch: it’s not really your team. It’s a group pulled together from different departments – sales, marketing, product, maybe even someone from legal whose job seems to be vetoing everything. These aren’t people you hired. They don’t report to you. And they probably don’t report to each other either.

You’ve been handed what might be called a “project committee” or “task force,” but what you really have is a cross-functional team. And while cross-functional teams should be engines of innovation, agility, and organizational alignment, the truth is most of them don’t work very well.

But they can, if you lead them the right way.

The Promise and Problem of Cross-Functional Teams

In theory, cross-functional teams are supposed to break down silos, accelerate execution, and bring diverse perspectives to complex problems. And sometimes they do.

But more often than not, they stall out. One study found that 75% of cross-functional teams are actually dysfunctional—they miss deadlines, blow budgets, or fail to stay aligned with organizational priorities. And it’s not because the individuals aren’t talented. It’s because collaboration across departments requires a different kind of leadership. One that starts with structure, not just speed.

Too many team leaders, especially those new to cross-functional work, start with the work itself. They jump straight into assigning tasks, setting up meetings, and building timelines. That seems logical, it’s a project after all.

But if you don’t pause to clarify goals, define roles, and build new communication norms, your team will default back to the ways of working they know best—the ways of working from their own silos. And that means your team will function more like a loosely affiliated group than a truly collaborative unit.

Why Most Approaches Fail

Cross-functional dysfunction isn’t about poor communication, it’s about misaligned expectations. Everyone brings different priorities, pressures, and mental models into the room. The marketer thinks about brand. The engineer thinks about feasibility. The legal team thinks about risk. And no one is wrong.

But if you don’t create a shared understanding early, those different viewpoints don’t complement each other—they compete. Left unchecked, people stick to their departmental defaults, and the very diversity that was supposed to spark innovation becomes a source of friction.

How Cross-Functional Teams Win

To lead a cross-functional team effectively, you don’t just manage the project, you design the team.

Here’s how.

1. Clarify Goals and Roles

Before anyone touches a task list, you need to get the team aligned on two foundational questions: What are we trying to achieve? Who is doing what to get us there?

That may sound obvious. But in cross-functional teams, ambiguity reigns. Everyone assumes someone else is handling a task. Or worse, two people assume they’re both in charge.

Start by mapping out the scope of the project together. Identify major deliverables. Then ask the group: “Who here feels best equipped to own this?” Let people step forward. If there’s debate, facilitate it. If someone volunteers for a stretch assignment, support them, perhaps by pairing them with a more experienced teammate.

This approach does more than assign work. It sends a message: this is a team, not a collection of departments. And you’re here not just to execute—but to develop.

2. Set Communication Norms

Every department has its own way of working. Some teams live in Slack. Others still rely on email. Some expect immediate responses. Others have a “48-hour rule.” If you don’t align early, miscommunication is inevitable.

At your kickoff meeting, have the team co-create its communication norms. Ask questions like:

How will we keep each other updated on progress?
What tools should we use, and for what?
How do we request help?
How often should we meet?
How will we make decisions?
How will we give and receive feedback?

Document the answers. Make them visible and accessible. Then refer back to them, especially when things get bumpy.

These shared norms help your team navigate differences in communication style and prevent misunderstandings from becoming major roadblocks.

3. Build Empathy Through Common Understanding

Communication norms help people speak to each other. Empathy helps them listen with each other.

People on a cross-functional team aren’t just bringing different skills—they’re bringing different definitions of success. One team member might be evaluated on speed, another on accuracy, another on cost control. If you don’t understand the pressures your teammates are under, you’ll misunderstand their decisions—and maybe their intentions.

One powerful exercise: ask each team member to explain how their performance is measured back in their “home” department. What does success look like? What’s their boss expecting from them? What’s at stake?

You can even create simple “user manuals” for each team member that explain how they like to work, how they make decisions, and what stresses them out.

The more your team understands each other, the easier it becomes to collaborate, and to resolve conflicts when they arise.

4. Foster Psychological Safety

Here’s something most people miss: a lack of disagreement on a cross-functional team isn’t a sign of alignment. It’s a sign of silence.

In the early days of a new team, people tend to be polite. They nod along. They bite their tongues. They say things like, “That’s interesting,” when they really mean, “That will never work.”

But innovation doesn’t happen through politeness. It happens through candor. And candor requires psychological safety—the belief that you can speak up without fear of rejection or ridicule.

To build that safety, model vulnerability as a leader. Say things like, “What am I missing?” or “This is a rough idea—feel free to poke holes.” When people challenge you, thank them. When disagreements emerge, guide the group to evaluate ideas based on assumptions, not egos. Ask, “What assumptions are we each making?” rather than “Who’s right?”

Psychological safety isn’t about eliminating conflict. It’s about making conflict productive.

5. Celebrate Small Wins

Cross-functional projects often span months or even years. And when the deadline feels distant, motivation can wane, especially when team members are juggling other priorities.

That’s why milestones matter. Break the project into phases. Define what success looks like for each one. Then, when your team hits a milestone, celebrate it. A shout-out in a meeting. A thank-you email. A Slack emoji reaction.

Research shows that even small wins, when recognized, can boost morale and performance. Just make sure your recognition is authentic and specific. People know when you’re faking it.

Final Thought: It’s Never Too Late to Reset

Maybe you’re reading this and thinking, “Great… but I’m already halfway through leading a cross-functional team that’s barely functioning.”

Good news: it’s never too late to pause and reset. Call a meeting. Clarify goals. Align on roles. Set communication norms. Celebrate any progress you’ve made. Then start fresh from there.

Cross-functional teams can be challenging. But when they’re led well, they become more than the sum of their parts. They become engines of innovation and drivers of real change across your organization.

And you? You become the kind of leader who makes collaboration work, even when no one reports to you.

Image credit: Unsplash

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7 Signs Your Company Needs a Customer Experience Audit

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7 Signs Your Company Needs a Customer Experience Audit

by Braden Kelley and Art Inteligencia

Most companies don’t wake up one day and decide they need a customer experience (CX) audit. They notice something’s off — a number that won’t move, a complaint that keeps recurring in slightly different words — and spend months treating the symptom before anyone names the actual problem. If any of the following sound familiar, that’s usually the moment to stop treating symptoms.

1. Your satisfaction scores have plateaued, not declined

A declining NPS is easy to act on — something clearly broke, and you go find it. A plateaued score is harder, because nothing is obviously wrong, and yet nothing is getting better either, no matter what you try. That’s usually a sign the problem isn’t in the parts of the experience your survey is capturing. It’s in the parts nobody’s measuring.

2. Customer complaints keep circling the same theme without ever naming the same issue

Different words, different tickets, different customers — but if you squint, they’re all describing the same friction from slightly different angles. That pattern usually means the actual root cause is a step upstream of where the complaints are landing, and no one’s traced it back far enough to find it.

3. Your team has strong opinions about “what customers want” — and no recent research to back it up

Every organization develops internal folklore about its customers over time, and folklore calcifies fast. If the last time anyone formally validated your personas was more than a year or two ago, there’s a real chance the assumptions steering your roadmap and your customer’s actual expectations have quietly drifted apart.

4. Frontline teams routinely “work around” the same problem instead of escalating it

When support or sales staff have built informal scripts or manual fixes for a recurring issue, that’s a sign the organization has adapted to a problem instead of solving it. It also means leadership likely has no visibility into how often it’s happening, because a workaround is specifically designed not to generate a ticket.

5. You’re investing in acquisition, and retention isn’t keeping pace

New customer growth that isn’t showing up in overall revenue growth is one of the clearest tells that the experience, not the funnel, is where the leak is. It’s a math problem before it’s ever discussed as an experience problem — and by the time it’s obviously an experience problem, it’s usually cost you a lot more than an audit would have.

6. A competitor keeps coming up in customer conversations for reasons that aren’t about price

When customers mention a competitor unprompted, and the comparison isn’t about cost, it’s almost always about experience — how easy something is, how fast a question gets answered, how the relationship feels. That’s a benchmarking gap, and it’s one of the harder ones to see from inside your own organization.

7. Nobody in leadership has personally walked the customer journey in the last year

This is the simplest sign and the one most often overlooked. If the people making decisions about the customer experience are working entirely from dashboards and secondhand reports, rather than having recently gone through the journey themselves, there’s a structural gap between what leadership believes is happening and what’s actually happening.

What to do if two or more of these sound familiar

One of these signs, on its own, might just be normal organizational noise. Two or three together is a pattern worth taking seriously. If you want a more structured way to check where the real gaps are, the Customer Experience Audit Checklist walks through the same five areas a professional audit examines, so you can see for yourself before committing to anything larger.

If you’re already fairly confident there’s a real problem and want to know roughly what it’s costing you, the CX ROI Calculator is the fastest way to put a number on it — and from there, a Customer Experience Audit is how you find out exactly where to fix it first.

Download the Customer Experience Audit Checklist as a PDF

Image Credits: Pexels

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

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Do Your Innovation Words Match Your Actions?

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Do Your Innovation Words Match Your Actions?

GUEST POST from Mike Shipulski

Innovation isn’t a thing in itself. Companies need to meet their growth objectives and innovation is the word experts use to describe the practices and behaviors they think will maximize the likelihood of meeting those growth objectives. Innovation is a catchword phrase that has little to no meaning. Don’t ask about innovation, ask how to meet your business objectives. Don’t ask about best practices, ask how has your company been successful and how to build on that success. Don’t ask how the big companies have done it – you’re not them. And, the behaviors of the successful companies are the same behaviors of the unsuccessful companies. The business books suffer from selection bias. You can’t copy another company’s innovation approach. You’re not them. And your project is different and so is the context.

With innovation, the biggest waste of emotional energy is quest for (and arguments around) best practices. Because innovation is done in domains of high ambiguity, there can be no best practices. Your project has no similarity with your previous projects or the tightest case studies in the literature. There may be good practice or emergent practice, but there can be no best practice. When there is no uncertainty and no ambiguity, a project can use best practices. But, that’s not innovation. If best practices are a strong tenant of your innovation program, run away.

The front end of the innovation process is all about choosing projects. If you want to be more innovative, choose to work on different projects. It’s that simple. But, make no mistake, the principle may be simple the practice is not. Though there’s no acid test for innovation, here are three rules to get you started. (And if you pass these three tests, you’re on your way.)

If you’ve done it before, it’s not innovation.
If you know how it will turn out, it’s not innovation.
If it doesn’t scare the hell out of you, it’s not innovation.

Once a project is selected, the next cataclysmic waste of time is the construction of a detailed project plan. With a well-defined project, a well-defined project plan is a reasonable request. But, for an innovation project with a high degree of ambiguity, a well-defined project plan is impossible. If your innovation leader demands a detailed project plan, it’s usually because they are used running to well-defined continuous improvement projects. If for your innovation projects you’re asked for a detailed project plan, run away.

With innovation projects, you can define step 1. And step 2? It depends. If step 1 works, modify step 2 based on the learning and try step 2. And if step 1 doesn’t work, reformulate step 1 and try again. Repeat this process until the project is complete. One step at a time until you’re done.

Innovation projects are unpredictable. If your innovation projects require hard completion dates, run away.

Innovation projects are all about learning and they are best defined and managed using Learning Objectives (LOs). Instead of step 1 and step 2, think LO1 and LO2. Though there’s little written about LOs, there’s not much to them. Here’s the taxonomy of a LO: We want to learn if [enter what you want to learn]. Innovation projects are nothing more than a series of interconnected LOs. LO2 may require the completion of LO1 or L1 and LO2 could be done in parallel, but that’s your call. Your project plan can be nothing more than a precedence diagram of the Learning Objectives. There’s no need for a detailed Gantt chart. If you’re asked for a detailed Gantt chart, you guessed it – run away.

The Learning Objective defines what you learn, how you want to learn, who will do the learning and when they want to do it. The best way to track LOs is with an Excel spreadsheet with one tab for each LO. For each LO tab, there’s a table that defines the actions, who will do them, what they’ll measure and when they plan to get the actions done. Since the tasks are tightly defined, it’s possible to define reasonable dates. But, since there can be a precedence to the LOs (LO2 depends on the successful completion of LO1), LO2 can be thought of a sequence of events that start when LO1 is completed. In that way, an innovation project can be defined with a single LO spreadsheet that defines the LOs, the tasks to achieve the LOs, who will do the tasks, how success will be determined and when the work will be done. If you want to learn how to do innovation, learn how to use Learning Objectives.

There are more element of innovation to discuss, for example how to define customer segments, how to identify the most important problems, how to create creative solutions, how to estimate financial value of a project and how to go to market. But, those are for another post.

Until then, why not choose a project that scares you, define a small set of Learning Objectives and get going?

Image credits: Pixabay

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AI’s Absurd Response to an Absurd Question

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AI's Absurd Response to an Absurd Question

GUEST POST from Shep Hyken

This article answers the question: Can AI be fully trusted to handle customer service issues, and what are the limitations of relying on AI for customer support?

As I write this article, I’m at the CX Malaysia conference, where I was the opening speaker, watching Dr. Shreekant Vijaykar of COPC Inc., one of the other speakers, talk about AI and how you can’t always trust its responses.

Dr. Vijaykar said that he asked ChatGPT the following question:

“I just bought a pair of shoes from Amazon, and they messed up the order. The shoe for the right foot was for the left foot, and the shoe for the left foot was for my right foot. What should I do about this mistake?”

He then shared that the response was to contact Amazon to let them know about the mistake, and they will refund the purchase price or exchange the shoes. I didn’t believe him, so I asked ChatGPT the same question. To my surprise, here was the answer:

That’s definitely a strange mix-up – and something Amazon should fix quickly. Here’s what to do:

Start the Return/Replacement Process: Go to Your Orders on Amazon. Find the shoe order and click “Return or Replace Items.” Choose the reason: “Wrong item was sent” or “Item defective or not as described.” Amazon will usually offer a free return label and a replacement option.
Describe the Issue Clearly: In the notes, explain exactly what happened–something like: “The right shoe is shaped for the left foot and vice versa. The pair I received cannot be worn properly.” That level of clarity helps Amazon’s quality control team flag the issue for the seller or manufacturer.
Choose the Replacement (if you still want the shoes): If you like the shoes and they’re still available, request a replacement instead of a refund. Amazon will often ship it out before your return even arrives.

Shep Hyken ChatGPT Cartoon
I took this absurd response a step further and wrote: “Maybe there’s a better response. It’s not really a mistake. … Just put the shoes on the opposite feet and they will work just fine. Thoughts?”

ChatGPT’s response was:

“Ha! That’s a funny way to look at it, but unfortunately, that’s not quite how shoes work. Even if you can technically put them on opposite feet, they’ll be uncomfortable and could mess up your posture or cause pain after a while – especially if you wear them for long periods.”

Dr. Vijaykar’s experiment revealed an important truth about AI: It makes mistakes. ChatGPT treated two normal shoes as if they were defective, offering a detailed explanation of Amazon’s return process.

AI is powerful, but just like humans, it can make mistakes. This ridiculous exchange is why some customers fear using AI for customer support. If you use AI tools like ChatGPT, Claude, or others, you must have a way to check answers. Apparently, common sense isn’t something that can be programmed. At least, not yet!

Image Credits: Pixabay

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Is Your AI in the Zone to Win?

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Whether you are catching up, keeping up, getting ahead, and fending off an existential threat, get in the zone!

Is Your AI in the Zone to Win?

GUEST POST from Geoffrey Moore

We’re already almost three years into the modern AI era, and everyone wants to know — What are we doing with AI? The board wants to know, the sales team wants to know, the customers want to know, the analysts want to know. Heck, you want to know.

So, how do you decide?

Start with a clear-eyed assessment of where your company stands relative to its peers in your industry. Are you behind? Are you on par but need to keep up? Are you out ahead or have a chance to be so? Or, in a darker vein, is AI opening your entire industry up to disruption, putting you and your peers under existential threat? The good news is that there are playbooks for dealing with each of these situations. The caveat is that they are all different. You need to execute them, if not linearly, then at least separately. And that’s where zone management can be a big help.

Catching Up

Industries in catch-up mode with respect to implementing AI might include retail (supply chain management, contact center productivity), higher education (admissions, alumni relations), and public sector (regulatory compliance services). The wolf is not at the door, but with AI moving as fast as it is, time is not your friend, so you need to get cracking. This is a job for the Productivity Zone.

Every organization in this zone — finance, HR, marketing, purchasing, customer success, security, you name it—is a candidate for implementing some kind of AI on a low-risk, get-acquainted basis. None of these applications will be so dramatic as to disrupt normal services, but each will give your AI team hands-on experience with the latest available technology, and most should deliver enough ROI to pay for themselves. Even when they don’t, they will contribute to the “Win or Learn” kitty, and that is what catching up is all about.

The key here is to move fast and on every front. That means every organization in this zone has to participate every quarter. Conduct AI progress reviews to hold each org leader accountable for net new wins or learnings every quarter. The goal is to catch up within a year, and it is important enough to tie performance to discretionary compensation to ensure both prioritization and inspection.

Keeping Up

Industries in a keep-up model with respect to implementing AI might include insurance (underwriting, claims), management consulting (tax, audit), and public sector (tax collection). All these areas represent customer-facing processes that are currently served by humans loaded down with routine work that can be done better, faster, and cheaper by AI applications. This is a job for the Performance Zone.

The goal here is to use AI to increase the competitiveness of your established lines of business, either through materially differentiating your products or dramatically reengineering your processes to lower costs, speed response times, and improve quality. The current generation of AI technology, because it is so remarkably approachable, is ready-made to take on this work. Your job is to make sure you use it to target those opportunities where there is the most trapped value to release. These will likely be a bit more gnarly than the others, but when you are mining for gold, you have to go where the gold is.

Generating such higher returns does not come without taking risk. Good as it is, AI is still a work in progress, so you will likely be taking a human-in-the-loop approach for the foreseeable future. The good news is your workforce is expert in your business, so you have the guard rails you need already in place. The challenge is that we humans are comfortable in our established routines, and you need everyone to break out of the old ways to free your company’s future from the pull of the past. This is more of a change management problem than an AI issue, so you should have no qualms about holding the leaders of this zone accountable.

Getting Ahead

Industries with a lot of built-in trapped value represent opportunities for first-movers to get ahead of their peers by radically reengineering the way business gets done. Examples might include residential real estate (title insurance, buyer agent compensation), health care (value-based care, home care), and public sector (social services). In each case, traditional bureaucracies are at odds with where the industry needs to go next, and implementing AI applications can be highly disruptive. This is a job for the Incubation Zone.

Venture-backed start-ups are normally the fastest movers here, but they take a long time to scale. Established enterprises have the customers, the ecosystems, and the balance sheets to get to the finish line first if they can get out of their own way. That’s what the Incubation Zone is designed to do. As described at length in Zone to Win, it emulates the VC operating model without attempting to replicate its financial model. The goal is to win early market marquee customers and cross the chasm, all without any help (or hindrance) from the core business. You have all the resources you need to do this, but it requires muscles you haven’t used in a long time, so funneling one or more acquisitions into the Incubation Zone is often a good tactic.

The key challenge will come when you reach enough scale to bring the new line of business into the Performance Zone. In the best of circumstances, you can leverage the more forward-thinking elements in your partner ecosystem and customer base to create a soft landing, running both the old and new lines side by side, as Netflix did for some time with its DVD and streaming businesses. Sooner or later, however, you will have to rip off the Band-Aid and make the transition to the new path, again as Netflix did.

Fending Off an Existential Threat

At present, the existential threat posed by Generative AI and its successors is still hard to predict, but two industries that have already sensed it are media entertainment (content creation, acting) and publishing (copyright, fair use). What should their playbook be?

This is a job for the Transformation Zone. The playbook requires all four zones to fly in formation to get through a very rough patch. The Productivity Zone goes into action first, launching legal actions against the invaders and pursuing lobbying efforts to get protective legislation. This is not a long-term solution, but it does buy some much needed time.

Meanwhile, the Incubation Zone is charged with catching up to the new wave as fast as possible. The goal here is not to out-innovate the innovators. That is what Yahoo tried to do to fend off Google, and Nokia to fend off Apple. The attackers are too good at what they do, and you are playing their game. Instead, take a lesson from how Microsoft has played catch-up throughout its storied history, beginning catching WordPerfect with Word, Lotus 123 with Excel, Aldus Persuasion with PowerPoint, and moving on to the Mac GUI with Windows, Novell with Windows NT, and Netscape Navigator with Internet Explorer. Most recently, they executed the catch-up-fast playbook to head off Amazon Web Services with Azure. The key to their success is to get to “good enough, fast enough,” not to out-perform the disruptor but to keep their own existing customer base on their side, again buying time to innovate further once it is clear they are in the game to stay.

One thing you do not want to do as an established enterprise is to merge with a successful disruptor. The Time Warner AOL merger provides a cautionary lesson here. The cultures are too different, and the necessary level of mutual trust just isn’t there, so instead of running in parallel, they work at cross purposes, and the result is a tangled mess.

On the Performance Zone side, you have to keep pedaling (and peddling) the legacy line of businesses. Absent private equity, they are your only source of capital, and they are still providing value. But you have to realize that their profit margins are under direct attack and can only be defended through rear-guard actions. That is, your legacy profit pool is the current site of trapped value, and draining it is what is funding the next wave of innovation. You don’t like it, and your investors hate it, but that’s the hand you have to play.

And that brings us to the Transformation Zone proper. You are going through a transition, the intermediate stages of which are ugly, making everyone cranky, and causing rampant second-guessing of every move you make. This is where the CEO must lead with clarity, transparency, and conviction, rallying the troops, reaching out to the customer base, providing an investable narrative to the stakeholders, and reassuring the partner ecosystem. Moreover, every senior executive must unequivocally support the chosen path or else be asked to leave. When you are under existential threat, there can be no fooling around.

Summing Up

The AI tsunami is upon us, and we can expect wave after wave of disruption for the rest of this decade and the next one as well. Clearly, it offers a wealth of opportunity, but as with all waves, catching it depends on getting your timing right and finding the right angle of attack. The four playbooks outlined above have been tested over many decades within the high sector as it dealt with the disruptive impact of the microprocessor, the Internet, cloud computing, SaaS applications, smartphones, and social media. You may not be as familiar with them as you would like, but the risk of waiting on the sidelines exceeds the risk of taking the plunge, so I can only encourage you to grab your nose plugs and jump in.

That’s what I think. What do you think?

— Image credit: Gemini

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How Long Does a Customer Experience Audit Take?

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A Realistic Timeline

How Long Does a Customer Experience Audit Take?

by Braden Kelley and Art Inteligencia

The honest answer to “how long will this take” is almost always more useful than a vague reassurance that it “won’t take too long.” Vagueness here is what makes people hesitate — not the actual time commitment, which is usually more manageable than they expect once they can see it laid out phase by phase.

Why duration varies more than people assume

A Customer Experience Audit runs through five integrated activities, and each one has its own natural pace. The total timeline isn’t one number so much as it’s the sum of how much depth each activity needs for your specific journey — which is why a single-persona, single-channel audit might wrap in a few weeks, while a multi-segment, omnichannel engagement with full competitive benchmarking runs considerably longer. Here’s roughly what each phase involves.

Phase 1: Audience research and persona validation

This phase moves relatively quickly when personas already exist and mostly need validation against current reality, rather than being built from nothing. It slows down considerably when there’s no existing research to validate against — in that case, this phase does double duty as both discovery and validation, which naturally extends it.

Phase 2: Journey mapping and touchpoint analysis

This phase’s pace tracks directly with touchpoint count and channel count. Mapping a single-channel journey with a handful of touchpoints is straightforward. Mapping an omnichannel journey — where a customer might start on a website, continue on a phone call, and finish in person — takes meaningfully longer, because each channel handoff needs its own attention, not just each channel in isolation.

Phase 3: Existing data evaluation

This can run partly in parallel with the phases around it, which is one of the easiest ways to compress a timeline without cutting corners. The pace here depends less on data volume and more on data organization — data spread across disconnected systems that were never designed to talk to each other takes real time to reconcile, even when there isn’t much of it.

Phase 4: Walking the journey firsthand

This is usually the phase people underestimate, because it’s genuine fieldwork rather than analysis — retail visits, live service calls, full sales cycles observed end to end, sometimes across both B2B and B2C contexts in the same engagement. It’s also, consistently, where an audit turns up its most valuable and most surprising findings, which makes it a poor candidate for compressing even when the calendar is tight.

Phase 5: Competitive benchmarking

This phase can run largely independent of the others and is one of the more schedule-flexible components — it’s also the one most commonly trimmed or skipped entirely when timeline pressure is real, since it looks outward at competitors rather than inward at your own journey.

What actually extends a timeline

In practice, three things push a timeline out further than people expect: internal scheduling delays (getting the right stakeholders and frontline staff available for interviews and shadowing), data that’s harder to access or reconcile than anticipated, and scope that expands mid-engagement as new touchpoints or segments turn out to matter more than originally assumed. None of these are about the audit process itself moving slowly — they’re about the realities of coordinating across an organization, and they’re worth planning around rather than being surprised by.

What compresses a timeline

Running the data evaluation phase in parallel with early journey mapping, having stakeholder availability locked in before the engagement starts rather than scheduled reactively, and scoping deliberately — one primary journey and persona rather than every segment at once — are the three most reliable ways to bring a timeline in faster without sacrificing the depth that makes the findings useful.

Getting a real number for your situation

Because the actual timeline depends on your specific journey — how many personas, how many touchpoints, whether benchmarking is in scope — a general range is only ever a starting point for the conversation, not a substitute for it. If you’re building a case internally and need a realistic figure to bring to your own leadership, the audit page has the full detail on how an engagement runs, and I’m glad to talk through a specific timeline for your situation directly — the same way I would the disruption and cost questions that usually come up alongside it.

Download the Customer Experience Audit Checklist as a PDFImage Credits: Gemini

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

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Time to Finally Kill the Idea of Leaderless Organizations

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Time to Finally Kill the Idea of Leaderless Organizations

GUEST POST from Greg Satell

About a decade ago, the management guru Gary Hamel wrote a highly cited article in Harvard Business Review entitled ‘First, Let’s Fire All the Managers’. He analyzed the success of Morningstar, a leading manufacturer of tomato products that operates with a flat management structure and called for other corporations to follow its lead.

“A hierarchy of managers exacts a hefty tax on any organization,” he wrote. “This levy comes in several forms. First, managers add overhead and, as an organization grows, the costs of management rise in both absolute and relative terms.” The article created a lot of buzz and helped bolster other flat models, such as Holacracy.

Yet the “flat organization” idea hasn’t caught on. “Since 1983, the size of the bureaucratic class — the number of managers and administrators in the US workforce — has more than doubled, while employment in other categories has grown by only 40%,” Hamil recently wrote. The truth is that we need managers and trying to eliminate them is a waste of time.

Planning A Spontaneous Revolution

In the early 2000s, a series of color revolutions spread across Eastern Europe sweeping away the authoritarian remnants of post-communist governments in Serbia, the Georgian Republic and Ukraine. These would prove to other revolutionary waves such as the Arab Spring. Old-style hierarchies suddenly seemed out of date.

I experienced some of these events first-hand. I was living in Ukraine during the Orange Revolution and managing the leading news organization in the country. I also spent some time in the Georgian Republic and got to see many of the reforms take place. When Hamel’s article came out, I had already begun the research that would lead to my book Cascades and I found his ideas about flat organizations not only persuasive, but inspiring.

I shouldn’t have. Even at the time, it had become clear that the revolutions weren’t as successful and many of us had hoped. In Ukraine, Viktor Yanukovych had already come to power and it would take another revolution to dislodge him. In other countries, such as Egypt, new authoritarians would soon take the place of those who had been overthrown.

Yet even more importantly, I would later get to know one of the chief architects of the color revolutions, my friend Srdja Popović, and would learn that the revolutions weren’t leaderless at all. In fact, much of what I had experienced as spontaneous and organic was actually very much planned, engineered and organized.

As I continued to research supposedly “leaderless” organizations this would be a recurring theme. Either their success was either not genuine or ephemeral, or that there was a less obvious, informal hierarchy at work.

The Truth About The Orpheus Orchestra

One of the most cited examples of successful leaderless organizations is the Orpheus Chamber Orchestra in New York, which has been operating without a conductor since 1972. They not only regularly play at top venues like Carnegie Hall and Lincoln Center, but have won multiple Grammy awards.

An orchestra concert is a highly coordinated event, with many different musicians needing to coordinate their efforts to play music according to a specific vision. If everyone applies their own interpretation, what should be a symphony would end up as a cacophony. So how does Orpheus manage to not only survive, but thrive?

The truth is that Orpheus is not really a purely leaderless organization. It would be more accurate to say that the members trade off leadership, with one member leading one particular collection and then a different member leading another. So while it is true that the Orchestra as a whole is leaderless, each concert is leaderful.

That’s quite a big difference. If you would believe that an entire orchestra could conduct itself, you might go and try to run your organization with no direction at all, which would be a disaster. However, if you would follow the direction of the Orpheus Chamber Orchestra, you would appoint a particular team member to run each project, which would be so utterly conventional that it wouldn’t even seem worth mentioning.

The Open Source Pecking Order

Another favorite that advocates of “leaderless” organizations like to point to are open-source software communities. Yet once again, when you take a closer look, these communities are not some free-for-all, with everybody chiming in and making changes at will. In fact, in successful communities take governance very seriously.

Some projects, like Android and WordPress, are tightly controlled by the companies that originated them, Google and Automattic, respectively. They manage the community fairly tightly, accepting patches, revisions and improvements as they see fit and providing a vision for where they think the technology should go.

Open source foundations, like Linux and Apache provide more intricate governance structures. They don’t have much in the way of formal leadership, but in practice each project has informal leaders who drive the direction of the technology. In fact, competition for clout within those communities can be very stiff.

There’s a reason why some of the world’s most valuable companies pay people well to contribute to open-source software communities and it’s not altruism. They want to shape how crucial technologies will develop to benefit their business. To do that, talented people need to spend time building the trust and reputation that will enable them to lead.

Let’s Not Fire All The Managers

For a while now, management gurus such as Gary Hamel have been advocating for flatter organizations, yet there is little evidence that eliminating leaders is a viable model. In fact, when Wharton Professor Ronnie Lee took a close look at game software developers, he actually found that the number of levels of bureaucracy increased significantly, not decreased, over the last 50 years.

There are several reasons that this is true. The first is that, while having a flatter structure leads to more innovation and creativity, you need good leadership and governance to execute well. As an industry matures and becomes more complex, more levels of hierarchy are needed to manage it effectively.

Another important factor to consider is that even without a formal hierarchy, leaders will tend to emerge. Which is why when you take a closer look at often cited examples of “leaderless organizations,” there is much more hierarchy that it would at first seem. Just because there isn’t an organization chart doesn’t mean there isn’t a pecking order.

We need to stop thinking in terms of how many levels of bureaucracy there are and start working to network our organizations. We don’t need to eliminate managers — or anyone else for that matter — but to widen and deepen connections within and without our enterprise. We need to lead and to do it more effectively.

The role of leadership in organizations has changed. It is no longer merely to plan and direct work, but to inspire meaning and empower belief. As I wrote in Cascades, the key to transformational change is small groups, loosely connected by united by a shared purpose. The job of leaders today is to help those groups connect and forge a common purpose.

— Article courtesy of the Digital Tonto blog
— Image credit: Pexels

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