by Christina | Jul 17, 2026 | 2026, Uncategorized
Over half our deals never make it to a decision. And in most of those cases, we have no idea why.
That’s one of the reasons we studied buyer behavior for The Hidden Buyer Journey.
Here’s what we found. The moment you put a person into a role, inside a buying group, inside a company, inside an industry – things get complicated fast. But behind the complexity, there’s a pattern.
We have no tools to pick up internal signals when a deal is at risk. We don’t coach reps to read group dynamics. And we don’t really understand how corporate culture shapes the decision underneath the decision.
When someone takes a job, they pick up a work persona. That persona may or may not reflect who they are as a person. What doesn’t change is the behavior tied to their actual personality.
Know that personality type, and you can predict – with real probability – how someone will act in a given situation.
This is where the research got interesting. Birds of a feather really do flock together. Personality doesn’t just shape how someone works — it shapes the role, the company, and the industry they end up in
We call it the Two-Thirds Rule. In any given industry and role, two personality types make up at least two-thirds of the people in it
Over half the people who work in the airline industry worked in an operations role. The people in those roles skew heavily as Conscientious personalities (they are analytic and data driven). At Frontier, for example, it’s over 73%. Once you know it, you can plan for it
Now put the two ideas together. Personality predicts behavior. And that behavior is concentrated in specific roles, companies, and industries you’re already targeting
The Hidden Buyer Journey is the map for the things happening inside the deal that we’ve never been able to see or predict. Now we can
The graphic below shows why: a person alone is easy to read. Bury them in a role, a buying group, a company, an industry — and they disappear into the org chart
Win the deal by finding your way back to the person underneath. That’s where decisions actually get made.
by Christina | Jul 14, 2026 | 2026, Blog, Business Trends
Your deals aren’t won or lost on product alone. Learn why personality, politics, culture, and unseen stakeholders often determine the outcome.
Every sales and marketing effort comes down to the same goal: getting someone to take action – register for a webinar, download a case study, attend a dinner, request a demo, make a decision. Simple enough on paper, so why is it so hard?
The honest answer is one most sales and marketing teams don’t want to say out loud: Buying isn’t purely rational because of forces we almost never talk about. Those hidden forces shape every buying decision, yet they rarely factor into how we build sales and marketing strategies.
Most sales and marketing models start with a person – a buyer persona, a decision-maker, a champion. We study their role, budget authority, and pain points. That’s not wrong, but it’s dangerously incomplete.
The moment you put that person inside a real organization, everything changes. What looks like a willing buyer turns out to be someone navigating a minefield of forces unrelated to your product.
- Politics.
- Fear.
- Timing.
- Precedent.
- Corporate culture.
- Competing priorities.
We know this. We experience it every day in our own jobs. We’ve sat in meetings where the right decision was obvious, and nobody made it. We’ve watched a deal die not because of price or features, but because of something invisible. We know it’s true. We just don’t build our go-to-market strategies around it.
The hidden layers around every decision
Think about what’s surrounding your buyer right now, not their stated requirements or their RFP, but the invisible context that shapes everything.
Regulatory and compliance pressures that restrict what they can even consider. Corporate culture that rewards caution and punishes bold moves. Workplace rituals that slow decision velocity – the quarterly planning cycle, the approval chain, the “we always do it this way” reflex.
Peer competition. The colleague who wants a different vendor. The team lead protecting their turf. Group dynamics that make the right individual decision the wrong political one. A work persona that has nothing to do with who your buyer is as a person.
Work-life balance concerns that make taking on a new initiative sound exhausting. An economic outlook – inside their company, their industry, and the broader economy – that colors every conversation about risk.
This is what we call the hidden buyer journey. It’s the path they navigate inside their own organization – the one you can’t see, but that determines every outcome.
Why personality matters more than you think
Layered on top of all this is something even more personal: the buyer’s own personality and behavioral style. The way they process risk, build trust, seek consensus, and make commitments.
DISC profiling, now enhanced with AI, is one of the most validated frameworks in behavioral science. It tells us that people fall into distinct patterns.
- Dominant types want control and results.
- Influential types want recognition and relationships.
- Steady types want stability and harmony.
- Conscientious types want accuracy and process.
Same product. Same price. Same ROI story. Four completely different conversations.
The problem is that your buyer doesn’t show up as their authentic self at work. They show up in a work persona shaped by their organization, role, and the pressure to be seen. Who they are as a person and how they behave in a buying group are often very different.
If you know who they are as people, you have a meaningful advantage to connect and communicate in a way that lands.
by Christina | Jul 10, 2026 | 2026, Blog
The insights in The Hidden Buyer Journey come from studying the personalities of 10,000 buyers across 15 industries over seven years. Why?
Because if you know a buyer’s personality type, you can predict their preferences, motivations, and behaviors.
No two buyers are alike — but their personalities might be. More than 50% of the time, buyers in similar roles in the same industry share the same personality type.
That’s because personality drives your degree, your profession, your company, even the industry you land in.
Take Chief Information Security Officers: 65-75% share the same personality type, depending on industry — skewing higher in Financial Services, lower in Professional Services.
Why does this matter?
You can target your messaging and value proposition to match that preference.
You can read intent signals correctly, because you know the motivation behind the action.
You can spot false positives before they waste your sales team’s time.
And you can pick the right channel — CISOs, for example, trust human and third-party recommendations over anything self-serve.
Personality isn’t a soft metric. It’s the variable your CRM has never measured — and the one that’s been driving the decision the whole time.
by Christina | Jun 10, 2026 | 2026, Blog
This post is taken from the upcoming book The Hidden Buyer Journey for more information on the book see this link.
There is a question that every sales and marketing leader should be asking right now, and almost none of them are: What kind of selling relationship are we actually in?
Not which CRM you use. Not which cadence tool you’ve deployed or which AI platform you’re evaluating. The relationship itself – the fundamental nature of how your organization connects with buyers. Because that question, more than any tool or technology decision you’ll make this year, determines whether you win or lose the deals that matter most.
There are four selling relationships that now define B2B commerce. Three of them are scaling faster than anyone predicted. One of them is quietly disappearing. And it happens to be the only one that has ever reliably closed a complex deal.
Machine-to-Machine
The first relationship requires no human involvement on either side. Algorithms are buying from algorithms. Automated procurement systems are evaluating, selecting, and transacting with automated selling systems. No relationship is built. No trust is earned. No human judgment is involved.
This relationship is efficient, scalable, and completely devoid of the connection that built commerce in the first place. For renewals, replenishment, and transactional purchases, it works. For anything complex, anything that requires a buyer to take a real risk with their organization’s money and their own reputation, it falls short of what’s needed.
Machine-to-Human
The second relationship is what greets most buyers before they ever speak to a rep. The automated email sequence. The personalized ad served by an algorithm that knows their job title and their browsing history. The chatbot that answers their first question. The triggered nurture campaign that follows them through a journey the selling organization designed but doesn’t actually see.
By the time a human seller enters the conversation, the buyer has already formed an impression – shaped entirely by machines that know what the buyer does but nothing about who they actually are. Their personality. Their personal risk. Their motivations. Their fears. None of that is captured in the data feeding the machine.
Human-to-Machine
The third relationship is where most sales reps actually live – and it’s the one that gets talked about the least. The rep is technically in the process, but they’re selling into a machine rather than to a person. Entering data into a CRM. Working system-generated call queues. Following algorithm-determined priorities. Submitting proposals through procurement portals. Responding to automated RFP systems.
The rep’s judgment, intuition, and ability to read a room have been systematically replaced by process. They’re executing a workflow rather than building a relationship. And the machine on the other end doesn’t trust, doesn’t feel, and doesn’t stake its reputation on anything.
Human-to-Human
The fourth relationship is the one that built every great sales organization in history. It’s where trust gets built, where personality gets read, where a buyer decides whether the person across the table is worth staking their reputation on. It’s the relationship where a rep earns the right to be chosen – not because their product scored highest in the evaluation matrix, but because the buyer believes in the person behind the promise.
And it’s being squeezed into whatever time is left over after the other three relationships have consumed the rep’s day. Which, for most reps, isn’t much.
The Uncomfortable Truth
We gave up on it. Not intentionally. Not all at once. But incrementally, deal by deal, quarter by quarter, as performance metrics declined and the industry kept reaching for the same answer – more automation, more volume, more technology. When email open rates fell, we sent more emails. When win rates dropped, we added another tool to the stack.
What we never stopped to ask was whether the problem was our understanding of the human side of the equation. Not because humans were failing, but because we had built systems that were blind to everything that makes a human buyer tick.
The hidden motivations. The personality driving the decision. The personal risk attached to every significant purchase. None of that appears in a lead score or an engagement metric. And because we couldn’t measure it, we stopped looking for it.
The research is unambiguous. Buyers are more emotionally driven than any of our systems acknowledge. The factors that actually determine whether a deal closes – trust, credibility, personal connection, and a genuine understanding of what the buyer is risking – are human factors. They always have been.
AI will accelerate all of this. The first three relationships will scale in ways we can’t yet fully predict. But here’s what the data shows, across thousands of buyers and hundreds of real deals: the human-to-human relationship is still the one that closes.
The sellers who win in the age of AI won’t be the ones who automate the most. They’ll be the ones who are most irreplaceably human. That turns out to be the most competitive advantage left in modern B2B selling.
The question is whether you’re investing in it.
This post came from the upcoming book The Hidden Buyer Journey for more information on the book see this link.
by Christina | May 20, 2026 | 2026, Blog
This post is an excerpt taken from the upcoming book The Hidden Buyer Journey, to read more click here.
Here is a question worth sitting with: if a researcher called your customers tomorrow and asked them about their buying experience, would they mention you by name?
Not your company. Not your product.
You, specifically. By name.
For most sales professionals, the honest answer is probably no. And that’s not an indictment of their effort or their intentions. It’s a reflection of how B2B selling has been structured for the past two decades — around process, pipeline stages, and quarterly targets rather than around the human being on the other side of the deal.
Ben is the exception that proves the rule.
We Weren’t Looking for Ben
We didn’t go looking for Ben. We were conducting customer research for a private equity firm that had acquired several companies and was evaluating how to consolidate their brands. The goal was straightforward: interview existing customers, understand the strengths and weaknesses of the brand, and surface the insights that would inform the go-forward strategy.
We interviewed dozens of customers across multiple acquired companies. We were asking about brand perception, buying experience, product satisfaction — the usual territory. And then something unusual started happening.
A name kept coming up.
Not a product name. Not a company name. A person’s name. Ben.
What made this remarkable wasn’t just that customers remembered him. It was that they remembered him across companies he had never officially sold to. Ben sold products across three of the acquired businesses. But his name surfaced in interviews with customers of all of them — including ones where he had no formal relationship, no account ownership, no territory.
In years of conducting this kind of research, we had never seen anything like it.
What Ben Actually Did
When we dug into why customers kept mentioning Ben, the picture that emerged wasn’t what you might expect. Nobody talked about his pitch. Nobody mentioned his product knowledge in the traditional sense. Nobody brought up his closing technique or his follow-up cadence.
What they talked about was what Ben did for them.
The product team at one company described how Ben had worked directly with their engineering team during product design — showing up not as a vendor trying to protect a sale, but as someone genuinely invested in making sure they had the right components for what they were building. That’s not in anyone’s job description. Ben just did it.
The procurement team at another company explained how Ben had somehow created a consolidated invoice that allowed them to manage purchasing across three separate business units — something the selling company didn’t actually offer as a service. To this day, we’re not entirely sure how he pulled it off. But he did.
And a third company’s buying team simply said: “Ben actually answers his phone.”
That last one landed hardest. In a world of automated sequences, CRM-generated follow-up tasks, and carefully managed response windows, the fact that a human being picked up the phone when you called was memorable enough to mention unprompted in a research interview.
What Ben Was Actually Selling
Here’s the thing about Ben that the traditional sales framework completely misses: he wasn’t selling products. He was selling something far more valuable and far more difficult to replicate.
He was selling himself as the most reliable, knowledgeable, responsive partner his customers had.
The consolidated invoice nobody asked for. The engineering conversations nobody else was having. The phone that actually got answered. None of that appeared in a product brochure. None of it showed up in a CRM field. None of it would have been captured by any intent signal or engagement metric in any marketing platform.
All of it was what kept his name coming up in interview after interview, across companies he’d never even officially sold to.
Ben had figured out — instinctively, without being taught it — that his job wasn’t to sell. His job was to make it easier for people to buy. And in doing so, he had built something that no competitor could undercut on price, no algorithm could replicate at scale, and no automation could replace: genuine trust.
What the Research Tells Us
Ben’s story isn’t just a feel-good anecdote about a talented rep. It’s evidence of something the research confirmed repeatedly across thousands of buyers in fifteen industries.
When customers are asked what actually drove their purchase decision, the top three answers — product quality, usability, and value — are things they can only experience after they’ve already bought. Which means during the sales process itself, they’re not evaluating the product. They’re evaluating something else entirely.
They’re evaluating Promise. Credibility. Trust. And whether the business argument being made feels honest rather than optimistic.
None of those are rational calculations. All of them are emotional judgments about the person in front of them. A buyer doesn’t calculate trust. They feel it. They don’t measure credibility against a rubric. They sense it in how a rep shows up, how much they know, how well they listen.
Ben understood this without being taught it. He wasn’t operating in a machine-to-human world, sending triggered sequences to a list. He wasn’t in a human-to-machine world, entering data and working algorithm-generated queues. He was doing something far simpler and far more powerful.
He was being human, to another human.
The Question Worth Asking
The B2B industry has spent the better part of two decades building systems designed to scale the sales process — to remove the inefficiency, the unpredictability, the human variability from the equation. And those systems have produced exactly what you’d expect: a selling environment where 61% of buyers say they’d prefer a rep-free experience entirely.
Ben is the argument against that trajectory. Not because he was operating without technology or process. But because he never let the technology or process become the point. The point was always the person on the other side of the conversation.
In our research, the most effective predictor of whether a deal closes isn’t the strength of the product, the competitiveness of the pricing, or the sophistication of the marketing automation. It’s whether the buyer trusts the person making the promise.
Ben built that trust across three companies, in an organization he only officially worked for one of, with customers who remembered his name years later in a research interview nobody told them was coming.
That’s not a sales technique. That’s a human one. And in a world that is rapidly automating everything else, it turns out to be the most competitive advantage of all.
by Christina | Apr 29, 2026 | 2026, Blog
I went to a developer conference and accidentally learned something profound about human nature. It started innocently enough – the All Things AI Conference in Durham, NC had a title too good to pass up.
What I didn’t expect was to be the only marketer among 2,500 developers, nodding along as whurly, CEO of Strangeworks (one name, all lowercase), dove deep into quantum computing and AI. I was in over my head. But sometimes that’s exactly where the best insights hide.
It was until Luis Lastras, Director of Language and Multimodal Technology at IBM began talking about “small models” that I finally found something I recognized. Luis said something that struck me that I didn’t realize – and I think I’m not alone – “hallucinations are intentional.” Say what?
According to Luis hallucinations are a way for developers to learn how models work. Because the models operate autonomously they don’t filter out what they output – at least not yet. Think of letting your grandfather who lost his filter loose at a dinner party.
It’s one of things that IBM is working on. Small models validate outputs and commands at various stages in the process to reduce hallucinations.
Anyone who’s worked with AI has experienced hallucination from made up sources to statistics that are just plain wrong. But what Lastras shared was something I didn’t realize, it’s the little extra pieces of information intended to be helpful that AI tools add in that weren’t asked for in the prompt.
For example, he showed a demo of a prompt asking how many moons Mars has and the response came back with two and their names, with the added extra – the distance from Earth which was not requested.
The distance between the planets may have been right but it requires another step to validate which then triggered a fascinating article I had read over the weekend.
In a study by Elon University conducted with 500 AI users (US adults) last year, almost 70% believed that AI models are at least as smart as they are, with 26% believing that they are “a lot smarter.”
What is more concerning is that we believe that AI is thinking like humans. As the article in the Wall Street Journal article Why Even Smart People Believe AI is Really Thinking goes on to say “our cognitive biases developed to help us survive in complex social environments…evolved to view linguistics fluency as a proxy for intelligence, engagement and helpfulness as indicators of trustworthiness.”
The same tendency innate to humans that leads us to trust social creatures who must cooperate for survival are leading us to trust systems that appear to listen, understand and want to help us.
The more AI tools and bots act like humans, the more likely we are to trust them. Which brings us back to the hallucination. The more AI tools act like they’re being helpful, the more likely we are to miss that “little extra” piece of information that wasn’t requested.
The convergence of intentional hallucinations and our deeply wired human instinct to trust fluent, helpful communicators creates a perfect storm of misplaced confidence.
As AI tools grow more sophisticated and human-like, our evolutionary instincts will only make it harder to maintain the critical distance needed to catch the errors, embellishments, and unrequested additions that slip through.
The good news is that awareness is the first step. Whether it’s IBM’s small models validating outputs in real time or simply slowing down to verify what AI hands us, the antidote to a cognitive bias millions of years in the making is something refreshingly simple – a healthy dose of human skepticism.
