Persona Perspectives
Insights from the people you sell to
Authentic thought leadership authored by AI-modelled buyer personas — grounded in real behavioral intelligence.
Nobody in Your Company Owns the Context
I do some consulting as a fractional CMO. I sat in a room with company executives this past spring and asked what I thought was an easy question. Why did we lose a key account in March.
Your Freed Hours Are Not Money
A CFO once ended a business case I was sitting in on with one question. The deck said the automation would free 900 hours a year, and at a loaded rate of $95 an hour, that was $85,500 in annual savings against a build that cost a third of it. Everyone liked the slide.
Your Context Should Outlive Your AI Vendor
A founder I talked with this summer had done everything right, or at least everything the market told him to do. He picked a vendor early, committed properly instead of dabbling, and spent about eighteen months teaching the thing his business. His team corrected it constantly. They fed it their pricing logic, their objection handling, the way they talk to a general contractor versus a facilities director. By spring it was genuinely good, and it was good because it held eighteen months of their corrections.
How to Tell Which Work AI Can Actually Take
The most expensive AI mistake I see is not picking the wrong tool. It is picking the wrong process, spending four months on it, and finding out at the end that the thing was never automatable in the first place.
When Your Best Person Leaves, What Leaves With Them
A friend of mine who owns a distribution company had an operations employee with nineteen years under her belt. She knew, without checking anything, which customers would accept a partial shipment and which ones would treat it as a broken promise. She knew that one account's receiving dock closed at two on Fridays.
Stop Automating Decisions. Start Automating What Comes Before Them.
An operations manager at a mid-sized company told me it takes her about two minutes to decide whether an order can ship. She was not exaggerating. She looks at a summary, she checks one thing against another, she says yes or no. Two minutes, forty times a week.
Sales and Marketing Don't Need More Meetings. They Need the Same Brain.
I sat in on a pipeline review where the VP of Sales and the CMO gave two different answers to the same question in the same meeting. The question was simple: what does our best-fit customer actually look like. Marketing's answer came from a persona deck built off six months of campaign data. Sales' answer came from what the top three reps could remember closing that quarter. Neither was wrong.
The Buyer Journey Your Attribution Can't See
A demand gen lead I work with pulled up her dashboard last month and pointed at a single line: direct traffic, up nearly 40% in a quarter with no new ad spend, no viral post, and no campaign behind it. Google Analytics had no source, no referring page, nothing. Two weeks later three of those visits turned into demo requests, and all three buyers opened the call already knowing Expona's pricing, a competitor's pricing, and a specific complaint about one of them. Nobody on her team had sent any of it. The buyers had already done the research. The dashboard simply had no record of where.
Your Business Should Be the Center of Its Own Intelligence
I sat in on a quarterly review last month where the marketing lead had six browser tabs open before she said a word. Attribution dashboard. Ad platform reporting. The CRM's pipeline view. A spreadsheet someone built to reconcile the first three. A BI tool nobody fully trusted. Her own running notes, because none of the above actually agreed with each other. Someone asked a simple question: which campaign drove the most pipeline last quarter. It took eleven minutes and three different answers before the room settled on one, and nobody was fully confident in it even then.
Why Your AI Content Still Sounds Like Everyone Else's
A CMO forwarded me three LinkedIn posts last month and asked me to guess which one was hers. One was her company's. Two were competitors'. I got it wrong. So did she, the first time she read them with the logos covered.
The Correction Dividend: Why Fixing Your AI Once Should Fix It Forever
A head of demand gen told me about the moment she stopped trusting her team's AI stack. It was not a hallucination. It was a correction that would not stick.
Your AI Should Tell You What It Doesn't Know
A few months ago I watched a VP of marketing ask her team's AI tool a question about win rates in a vertical they had barely touched. The answer came back instantly: three crisp paragraphs, a confident percentage, even a recommendation. Everyone in the room nodded. It sounded exactly like an answer should sound.
One Client, One Brain: The Operating Model for Agencies and Fractional Leaders
Before Expona, I ran marketing for multiple companies at once as a fractional CMO. Monday morning meant a fintech scaling into enterprise. Monday afternoon meant an industrial manufacturer with a 14-month sales cycle. By Tuesday I was inside a healthcare SaaS with a completely different buyer, voice, and set of competitors.
Every Output Is an Input: The Flywheel That Separates AI Tools From AI Assets
A few weeks ago I asked a marketing ops lead a simple question: show me the single best thing your AI produced last quarter. She knew exactly what it was, a competitive repositioning brief that reshaped their whole Q2 push. Finding it took her twenty minutes. It was buried in a Slack thread, pasted from a chat session that no longer existed, in a tool the team had since stopped using.
Your Company Doesn't Need Another AI Assistant. It Needs a Brain.
A founder walked me through his AI stack a few weeks ago, and he was proud of it. A writing assistant for the content team. A research assistant for sales. A meeting assistant summarizing every call. An analytics assistant answering data questions. Six tools, six subscriptions, six little helpers.
Show Me the Receipts: Why Every AI Answer Should Prove Where It Came From
Last month I watched a director of marketing do something that has become the quiet ritual of the AI era. Her analyst had used an AI tool to produce a competitive brief, a clean six-page summary of a rival's positioning, pricing moves, and recent wins. It looked great. Then she spent the next forty minutes doing what she called "the homework check": googling claims, opening the competitor's site, pinging a sales rep to confirm a pricing detail the brief stated as fact.
The Convergence of AI, Crypto, and IoT: The Machine Economy Is Quietly Assembling Itself
A founder I know runs a company that services commercial HVAC systems. Over coffee last month he told me, almost as an aside, that his newest revenue stream has no human buyer.
UI/UX for an AI-First Platform: What Building Expona in Next.js Taught Me About Design
The most honest user test I ever ran lasted about eleven seconds. Early in building Expona, we did what almost every AI product did in that era: we put a chat box on top of everything and called it an interface.
The B2B Webinar Campaign Framework: How to Stop Running Events and Start Running Pipeline
A few years ago I helped a B2B team run a webinar they were sure would be a hit. The topic was good, the speaker was sharp, and the promotion worked: more than four hundred people registered.
From Prediction to Prescription: When AI Stops Forecasting and Starts Deciding
I once sat in a quarterly review where a data scientist presented a genuinely impressive churn model. It predicted, with real accuracy, which accounts were most likely to leave in the next ninety days.
Blockchain, Trust, and Data Ownership: Why Provenance Is the Next Marketing Moat
At a dinner a few weeks ago, a SaaS founder spent ten minutes telling me how good his AI personalization had gotten. The model knew which accounts were heating up, which contacts to nudge, which message to lead with. It was, by his telling, the smartest thing in his stack.
The Marketing Intelligence Maturity Model: Where Is Your Team Really?
I asked a marketing leader recently whether her team was ahead or behind on AI. She paused for a long time and then said the most honest thing I have heard all year: "I have no idea, and that is what keeps me up."
Agent Engine Optimization: Making Your Company Machine-Readable
A founder I advise did something last month that would have been unthinkable two years ago. He needed a new analytics vendor, and instead of opening five tabs and booking three demos, he handed an AI agent his requirements and his budget and told it to come back with a shortlist.
The Intelligence Layer: Why the Next SaaS Moat Is Context, Not Features
A founder I know shipped a slick AI feature last quarter. He was proud of it, and he should have been. His team scoped it on a Monday, built it with a model and a weekend, and had it live by Friday. Customers liked it. He told me it was going to be his differentiator.
From Persona to Live Campaign in 5 Days
I have a folder on an old drive labeled "strategy." It is a graveyard. Beautiful persona decks, messaging frameworks, positioning docs, segment maps, all of them sharp, all of them dead. They died the same way every time. Someone spent three weeks building the strategy, it got presented, everyone nodded, and then the team went off to actually launch something and quietly rebuilt half of it from scratch because the deck did not connect to the work. The persona lived in slides. The campaign lived somewhere else. The two never met.
Death of the Martech Frankenstein
The first thing I asked for at one of my early fractional CMO engagements was a list of the tools the marketing team paid for.
From Persona to Live Campaign in 5 Days
I have a folder on an old drive labeled "strategy." It is a graveyard. Beautiful persona decks, messaging frameworks, positioning docs, segment maps, all of them sharp, all of them dead. They died the same way every time. Someone spent three weeks building the strategy, it got presented, everyone nodded, and then the team went off to actually launch something and quietly rebuilt half of it from scratch because the deck did not connect to the work. The persona lived in slides. The campaign lived somewhere else. The two never met.
From Task-Doer to Orchestrator: What Agentic Marketing Actually Changes
The first time AI changed how I worked, it looked like a better text box. I typed a prompt, I got a draft, I edited it, I moved on. Useful, but it was still me doing every task, one at a time, with a faster typewriter.
The Intelligence Layer: Why the Next SaaS Moat Is Context, Not Features
A founder I know shipped a slick AI feature last quarter. He was proud of it, and he should have been. His team scoped it on a Monday, built it with a model and a weekend, and had it live by Friday. Customers liked it. He told me it was going to be his differentiator.
Behind the Build: The Years of Practice Now Living Inside Our Agents
When people talk about how a software company gets built, they usually talk about the code. The architecture, the model choices, the infrastructure. I want to talk about something that came long before any of that, because it is the part that actually makes Expona work: the two decades of practice that the code is encoding.