Editorial
Research Report
Business Leaders CX Report: What’s Working and What’s Not in AI-Driven CX
The Gist
- Most marketing language hides weak thinking. Terms like “awareness,” “alignment” and “insights” often replace evidence, masking unclear goals and lazy analysis.
- Precision in language drives better decisions. Shifting from assumptions to hypotheses, and from activity to outcomes, forces teams to validate, measure and act.
- Credibility must be demonstrated, not declared. Labels like “expert” and “thought leadership” mean nothing without proof, results and repeatable methods.
I am a proud contrarian. Years ago, Bob Hoffman made a rally call for there to be more contrarians out there, calling bluffs and pointing out the ridiculousness of much of what we see and learn. Because he is one of my heroes, I took this to heart. I also felt vindicated.
For much of my career, I have questioned why teams were celebrating what I found to be mediocrity or faux success via vanity metrics. And through these experiences, I began to develop a series of terms that I hate.
At first, I just avoided using them. But over time, I’ve grown to hate these terms. I don’t hate many things in life, I’m proud to say. But these marketing terms? I hate them. Why do I hate them?
Keep reading to find out.
Table of Contents
- Assume
- Awareness
- Expectations
- Seamless
- Insights
- Alignment
- Thought Leadership
- Expert
- Objectivity
- Best Practice
- Confusing an Objective With a Goal
- Conclusion: You Should Hate These Terms, too
Assume
Most people claim they are “assuming,” but that is rarely what is happening. In practice, they are forming a hypothesis based on partial information, past experience or observable patterns. An assumption requires no evidence. A hypothesis requires at least some signal.
If someone is truly assuming something without any supporting signal, the real question becomes: why is a decision being made without evidence or reasoning?
This distinction matters because the language shapes the discipline of the decision process. When teams label a hypothesis as an assumption, they remove the obligation to validate it. The statement becomes a placeholder rather than a claim that must be tested.
This is not a semantic debate. The difference determines whether organizations guess or investigate. Hypotheses invite measurement and refinement. Assumptions invite complacency.
Awareness
People are aware of thousands of things every day. Awareness alone does not change behavior, create preference, or generate revenue. It simply means information reached someone’s senses.
Marketing frequently treats awareness as if it were an outcome. It is not. It is a byproduct of communication or exposure.
If a building explodes, people become aware of it. That does not mean they care, act, donate, purchase or engage. Awareness only signals that a message reached a person, not that it mattered.
This matters because organizations often measure awareness as a success metric even though it does not represent intent, interest or action. When awareness becomes the goal, teams optimize for visibility rather than impact.
This is not a matter of wording. It changes how programs are evaluated. Measuring awareness rewards activity. Measuring engagement rewards outcomes.
Related Article: The Marketing Reality Check CMOs Need: Emojis, Awareness and AI Won't Save You
Expectations
The word “expectations” is often used when people are actually describing norms. Norms form through repeated experiences that establish a baseline for what typically happens.
When someone attends a Blues Traveler concert after seeing the band perform hundreds of times, they do not walk in with a formal expectation. They carry a norm formed through experience. The norm is that the band delivers a strong performance. The audience recognizes the pattern. (Editor's note: The author is talking about himself as the concert-goer. He's Blues Traveler's No. 1 fan, and that number of concerts is not hyperbole).
An expectation implies a specific prediction about what will occur. A norm reflects what usually occurs based on accumulated evidence.
This difference matters because expectations are rigid and personal, while norms are collective and experiential. Expectations create the conditions for disappointment when reality diverges from prediction. Norms create a reference point that helps people evaluate whether something feels aligned with past experience.
Again, this is not semantics. Using the wrong term distorts analysis. If leaders believe customers arrive with fixed expectations, they focus on managing promises. If they recognize that customers rely on norms, they focus on delivering consistent signals that reinforce trust.
Related Article: The New King of Customer Experience? McDonald's. Seriously.
The Evolution of Marketing Buzzword Fatigue
Marketing language didn’t get clearer over time — it got slipperier. What started as overhyped innovation terms has shifted into vague, catch-all language that hides weak thinking and unclear decisions. Here are some marketing terms from 2018 and others from 2020 that annoyed us then to what annoys the author today.
| Era | What Marketers Said | What It Really Meant | Why It Annoyed People |
|---|---|---|---|
| 2018 | Omnichannel, Big Data, Personalization, Growth Hacking | New capabilities powered by emerging tech | Overhyped promises with little real execution |
| 2020 | Pivot, Unprecedented, New Normal, Digital Transformation | Reaction to rapid market disruption | Overused crisis language that lost meaning fast |
| 2026 | Alignment, Awareness, Insights, Thought Leadership, Seamless | Vague placeholders for unclear thinking | Words that replace evidence, ownership and decisions |
Seamless
“Seamless” is often used to describe an experience that supposedly removes friction. In reality, every system contains friction because decisions, authentication, payment and identity verification require effort.
The term usually signals aspiration rather than measurement.
If teams want to improve customer experience quality, they must identify the exact points where effort increases and remove unnecessary steps. Calling an experience seamless provides no diagnostic insight.
It replaces analysis with a slogan.
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Insights
Teams frequently say they want “insights,” but the word is rarely defined. Data produces observations. Analysis produces explanations. Experiments produce evidence.
Insight should mean a discovery that changes a decision. Yet it is often used to describe any interesting statistic.
When the word becomes vague, the analytical process becomes vague as well.
Alignment
“Alignment” is one of the most frequently used words in corporate communication, yet it rarely describes anything concrete. When someone says a team needs alignment, the statement often masks a simpler reality: people disagree on the objective, the evidence or the decision authority.
Using the word alignment allows organizations to avoid naming the real issue. Instead of identifying the conflict or resolving it, teams schedule more meetings to “align.”
This matters because progress requires clear ownership and explicit decisions. Alignment language often replaces both.
This is not semantics. If the problem is disagreement, the solution is a decision. Calling it alignment delays the decision.
Thought Leadership
“Thought leadership” is a phrase that attempts to declare authority rather than demonstrate it. Real expertise becomes visible through clear analysis, original frameworks or proven results. It emerges from evidence and experience.
Thought leadership language often reverses that process. Instead of proving expertise, the label is used as a shortcut to imply it. The risk is that organizations begin producing content designed to appear insightful rather than content that actually advances understanding or solves problems.
This distinction matters because credibility cannot be claimed. It must be demonstrated through work that withstands scrutiny.
Again, the issue is not semantics. The phrase changes incentives. Teams focus on appearing authoritative instead of producing ideas that hold up under examination.
Related Article: Thought Leadership Is on Trend, but Few Can Pull It Off
Expert
The word expert is often used as a credential rather than a demonstrated capability. In many contexts, no formal standard exists for who qualifies for the title. Organizations, publications and speakers frequently apply the label without any clear vetting process.
Experience and tenure alone do not establish expertise. Someone can spend 20 years repeating the same process without ever improving it, questioning it or measuring whether it works. Time in a role reflects exposure. It does not necessarily reflect mastery.
This distinction matters because the title influences how ideas are evaluated. When someone is introduced as an expert, their conclusions are often accepted without the scrutiny applied to others. The label shifts attention from the quality of the argument to the perceived authority of the speaker.
A more reliable indicator of expertise is demonstrated capability: the ability to explain underlying mechanisms, present evidence, produce measurable results and adapt methods when conditions change. Those signals can be evaluated directly.
This is not simply a wording preference. The language changes how credibility is assigned. If expertise is defined by titles or tenure, authority becomes self-declared. If expertise is defined by evidence and repeatable results, authority must be earned through demonstrated competence.
Objectivity
Objectivity, as a principle, is essential. The problem is the way the word is used. In many discussions, people claim to be objective when they are simply expressing a personal interpretation without supporting evidence.
True objectivity requires verifiable data and a transparent method for evaluating it. Without those elements, a statement remains a perspective or subjective, even if the speaker believes it to be neutral.
When someone announces that they are being “completely objective,” the claim should invite scrutiny rather than trust. Objectivity is not something a person declares. It is something demonstrated through evidence that others can examine and replicate.
This matters because the label often shuts down discussion. Once a viewpoint is framed as objective, disagreement is portrayed as irrational or biased rather than as part of a legitimate evaluation of the evidence.
This is not a matter of word choice. Misusing the term distorts decision-making. When opinions are presented as objective conclusions, organizations risk treating interpretation as fact. Real objectivity comes from data, method and verification, not from a speaker’s confidence in their own neutrality.
Related Article: The Worst Marketing Buzzwords of 2020
Best Practice
The phrase best practice suggests that a universal answer exists for a problem. In reality, most situations are shaped by different constraints, resources, audiences and timing. What worked well in one context may fail completely in another.
Most so-called best practices are simply commonly repeated practices that produced acceptable results under specific conditions. Over time, repetition turns those practices into rules, even when the original conditions no longer apply.
This matters because labeling something a best practice discourages investigation. Teams stop asking whether the approach fits their objective, their data or their operating environment. The phrase becomes a shortcut that replaces diagnosis with imitation.
This is not a matter of wording. It changes how organizations solve problems. When teams rely on best practices, they copy solutions that were designed for someone else’s circumstances. When they focus on evidence and outcomes, they design solutions that fit their own.
Confusing an Objective With a Goal
99% of the time, seriously, 99% of the time, when I’m reading documentation, I see two things that make no sense:
- Several objectives for a single initiative.
- Objectives that are actually goals.
But you’ll have to wait for a future article on this to learn more.
Conclusion: You Should Hate These Terms, too
It is so freeing to stop using these terms. You will find that the air smells sweeter, the sun feels warmer … just kidding. But in all seriousness, it is freeing. You start to focus on what matters.
You stop debating language and start evaluating evidence. Conversations shift from vague agreement to clear decisions. Teams spend less time interpreting what someone meant and more time defining what they will do next. That shift alone removes a significant amount of friction from how work actually gets done.
More importantly, you begin to see where thinking breaks down. When someone says “alignment,” you now ask what decision has not been made. When someone asks for “insights,” you ask what action should change. When someone reports on “awareness,” you ask what behavior moved. The language no longer hides the problem. It exposes it.
This is where the real value shows up. Precision in language creates precision in execution. It forces teams to define metrics that reflect behavior, not activity. It demands that conclusions be supported by evidence, not titles or confidence. It replaces slogans with systems.
And once you see it, you cannot unsee it. You will start to notice how often these terms are used to avoid clarity, not create it. Meetings will sound different. Reports will read differently. You will find yourself translating what people say into what they actually mean, and then pushing for that meaning to be stated directly.
That is the point.
This is not about disliking words. It is about rejecting shortcuts that weaken thinking. When the language improves, the thinking improves. When the thinking improves, the outcomes follow.
Hate the terms if you have to. Just do not use them.
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