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Replay: AI trust gaps, marketplace mismatches, and data paralysis

Quick hits on when "smart" recommendations backfire, why value propositions can't be forced, and the difference between data and actual decisions

Hey friends 👋

This week brought two solid office hours sessions packed with the kind of founder friction that tells you exactly where the real work lives.

Tuesday’s Substack session and Friday’s LinkedIn stream covered everything from AI-powered pricing tools that make customers nervous to B2B SaaS implementations that drag on for months.

The common thread? Founders assuming their solution is the problem when the actual problem is usually three layers deeper.

Tuesday’s Substack highlights

AI recommendations that feel too aggressive. An AI tool for small online retailers hit the classic trust barrier — users loved the 15-25% conversion boost in testing but wouldn’t implement the “aggressive” pricing and listing changes. The real issue wasn’t the AI being too smart; it was targeting small retailers who don’t have the data volume to trust algorithmic changes with their livelihood. Plus, optimizing for conversion rates instead of net revenue misses the actual metric that matters.

Smart dog collar unit economics. A hardware founder selling $149 collars that cost $95 to manufacture asked about improving margins without pricing out the market. The math is brutal: manufacturing needs to drop below $50 for this to work, or the price needs to double. The real lesson? Run pricing experiments on that 400-person waitlist to see what the market will actually bear before assuming you know the ceiling.

Tax season software with seasonal demand. A B2B SaaS for accounting firms launched right before tax season, saw great traction February through April, then usage dropped to almost zero in the off-season. The founder wanted to explore bookkeeping features to maintain engagement. Wrong move. Get paying customers for your core value first, then worry about expansion. Annual or seasonal pricing makes way more sense than trying to solve a retention problem you haven't validated people will pay to solve.

Watch the replay above.

Friday's LinkedIn rapid fire

Marketplace pricing mismatches. A freelance design platform had 500 designers wanting $50-150/hour while clients expected $15-30/hour rates. This isn't a balancing act — it's a fundamental value proposition problem. You can't convince low-budget clients to pay premium rates or train premium designers to work for Fiverr money. Pick one side of the market and optimize for the customers who actually want what you're offering.

Parents vs. kids on screen time. A gamified math app had 2,000 engaged kid users but only 150 paying parents who worried about screen addiction. Classic buyer-user disconnect, but the solution isn't adding parent dashboards or getting school partnerships to "prove" educational value. Find parents who already use educational technology with their kids instead of trying to educate skeptical buyers.

Small holder farmers and cold calling aversion. An ag tech founder targeting cooperatives and NGOs asked how to validate without cold calling. The channel hacking framework applies here: map every place your customers congregate, rank by difficulty of access, and start with the easiest wins. But more importantly, reframe cold outreach as helping solve urgent problems rather than being a pushy salesperson.

B2B SaaS with 6-month implementations. A pricing optimization tool for mid-market companies had strong product-market fit but brutal implementation timelines. The question wasn't how to shorten time-to-value — it was why they were doing unpaid 6-month pilots instead of collecting commitment upfront. Get contracts signed before implementation starts, not after six months of free consulting.

Gym analytics that don't drive action. A member retention platform showed gym owners exactly why customers canceled, but owners weren't acting on the insights. The problem isn't information overload; it's that information isn't what people pay for. They pay for recommendations and clear next steps. If you're giving them dashboards to analyze instead of specific actions to take, you've created a problem they can't solve.

FinTech compliance overwhelm. Financial advisors loved a client portal in demos but wanted different certifications and audit trails. Instead of debating whether to hire compliance experts or focus on technology, get letters of intent from prospects who'll commit to paying if you meet specific compliance requirements. Don't build without evidence people will actually buy.

Watch the replay →

The patterns worth remembering

Trust is earned in small steps. Whether it's AI recommendations or complex B2B implementations, nobody hands over their business on your word alone. Sandbox environments, pricing experiments, and paid pilots create evidence without betting the farm.

You can't educate your way to a sale. If you're explaining why screen time is actually good or why complex pricing optimization is worth six-month implementations, you're talking to the wrong customers. Find people who already believe what you need them to believe.

Data without decisions is just expensive dashboards. Information feels useful but recommendations drive action. The gap between showing someone their churn patterns and telling them exactly what to do about it is where most analytics companies die.

Marketplaces fail when sides don’t match. Premium designers and budget clients aren’t a balancing problem to solve — they’re separate markets that don’t belong on the same platform. Pick one and optimize ruthlessly.


Got a question burning through your brain? Submit it for next week’s office hours and get some science-based feedback that might actually move the needle. Tuesday mornings on Substack, Friday noon on LinkedIn — or just hit jdm.bio/calendar to submit in advance.

Because the best questions come from founders who’ve tried the obvious stuff and it didn’t work.

See you soon,

—JDM & Cam

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