CEO The Good – Optimization for top brands like Nike, Xerox, Adobe, The Economist & many more | Author & Speaker | 6'7" 🏀 | Jr Olympic 🥇🥋 | jonmacdonald.com | 📘 Latest Book 👉 thegood.com/oito

Every bad digital experience costs you money. My mission is simple: remove them all until conversion becomes inevitable.

I founded The Good 16+ years ago to turn user insights into revenue. We're the trusted Digital Experience Optimization advisory for household names like Adobe, Nike, Xerox, Intel, and The Economist.

Together, we've generated hundreds of millions in additional revenue by optimizing the full digital journey from first touch to retention.

I've written three best-selling books on conversion optimization and am a frequent keynote speaker at Google, Autodesk, and industry events worldwide.

Also building tools for UX researchers and consultants. Currently in beta: Clipses.ai. Turn user interview transcripts into shareable video clips in minutes. Helping teams eliminate hours of rewatching footage.

Folks will tell you I love to compete: I'm a former college basketball player (and still playing on a club travel team) and won the USA Jr Olympic gold medal in Taekwondo when I was 10. But, business is the ultimate sport.

Book a 15-minute optimization strategy call → https://thegood.com/contact/

📨 DM me to start improving the digital journey of your website or app… or to debate LeBron vs Jordan as the GOAT.

Jon MacDonald

I built my first website in 1996. Anyone can do that now in 5 minutes.

But nobody vibe coded Adobe's trust in us.

I've heard the same prediction for 16 years. WordPress will kill agencies. Then Squarespace. Then no-code tools. Now AI coding.

Each time, the pundits focus on the wrong thing. They see the interface and assume that's the product.

It never is.

The interface is maybe 5% of the value. The other 95% took years to build.

Enterprise relationships. Regulatory knowledge. Institutional expertise from hundreds of engagements. SOC 2 compliance. The phone call at 2am when something breaks.

There are five things you can't vibe code: brand trust, distribution, regulatory compliance, proprietary data, and customer relationships.

I'd add a sixth. The judgment that comes from optimizing digital experiences for Adobe, Nike, Xerox, and The Economist over 16 years.

A weekend coder can build a checkout flow. They can't tell you why it's underperforming or what to change. That takes pattern recognition from thousands of tests.

Technology always lowers the barrier to building. It never eliminates the need for expertise.

My business has grown through every "this kills that" cycle. I expect this one will be no different.

Digital Experience Optimization + AI Browser Agent Optimization + Entrepreneurship Lessons | 3x Author | Speaker | Founder @ The Good – helping Adobe, Nike, The Economist & more increase revenue for 16+ years

I've spent 16 years optimizing digital experiences for brands like Nike, Adobe, and Xerox.

But the next wave of "visitors" to their websites won't be human.

AI agents are already browsing sites, researching products, and making purchase decisions on behalf of real buyers. Most enterprise websites aren't ready for them.

Profound just raised $96M to fix that. And I'm fired up about it.

Engineers have Cursor. Lawyers have Harvey. Marketers now have Profound.

Their agents aren't just tools. They're autonomous workers that collaborate across your entire marketing team. AEO, SEO, content, PR, demand gen.

That's a massive unlock. We're talking 10x productivity potential for lean marketing teams who are already stretched thin.

Figma, Walmart, Ramp, U.S. Bank are already investing here. The enterprise demand for AI-powered marketing infrastructure is real and accelerating.

Congrats to the Profound team. Answer Engine Optimization is one of the fastest-moving categories in marketing right now, and the brands that figure this out early will have a massive edge.

More on the raise 👉 https://lnkd.in/gtAGfJ5E

I spent 16 years fixing the same conversion failures for Nike, Adobe, and The Economist. But I never realized I was doing product research.

Every engagement at The Good followed a pattern:

A brand calls. Visitors aren't converting. We dig in, find the friction, and optimize it away. Then the next brand calls with the exact same problems: Broken onboarding. Confusing pricing pages. Checkout flows that leak revenue at every step.

After a few hundred of these, something shifted. I stopped seeing individual client problems and started seeing product opportunities.

That realization built The Good Ventures.

UserInput was born from watching brands waste weeks waiting for user testing results they needed in days.

Clipses came from watching researchers spend entire afternoons hunting through interview footage to find one quote. We had the same problem internally.

PredictiveAX came from an even stranger pattern. We'd optimize a site for human visitors, then watch AI agents completely fail on the same pages. Different user. Same site. Opposite outcomes.

Every product in the portfolio started as a manual fix we repeated too many times. The pattern recognition from client work was the market research.

Most founders build first, then hunt for customers. Consultants have the opposite problem. We already have validated pain. We just need to build.

If you keep solving the same problem across different clients, you already have what most founders spend years searching for: validated demand.

I watched COVID nearly destroy 11 years of building The Good. But that crisis built something better.

In 2020, our services business all but shut down for a quarter. Clients froze budgets overnight. Projects vanished.

One revenue stream. One point of failure.

I'd spent a decade helping brands reduce risk through optimization. Testing small changes. Measuring results. Never betting everything on one idea.

Yet my own company was one giant bet.

In 2021, I launched The Good Ventures. A portfolio of small, focused products. Each born from patterns we kept seeing across client work.

No massive funding rounds. No 18-month builds. Small bets with clear metrics and fast feedback.

Jeff Bezos built Amazon's dominance through thousands of small experiments, not moonshots. I applied that same principle to venture building.

Some of our bets took off. Others taught expensive lessons. The portfolio absorbs both.

My EO forum helped me see this clearly. Several founders ran diversified businesses. They weathered downturns that nearly broke mine.

One revenue stream feels like focus.

It's actually fragility.

Diversify like you'd optimize: small bets, real data, and the willingness to kill what isn't working.

I laughed at this LinkedIn reply. But Okta data shows 350 SaaS apps per enterprise.

The reply: "I can now create the same tool in about a day. SaaS is over."

This take is everywhere right now. B2B SaaS stocks lost $1 trillion in value this year. The narrative feels convincing.

The data tells a different story.

Bureau of Economic Analysis numbers show corporate spending on self-built software dropped from 50% to just 15%.

Companies don't want to build tools. Even when they can.

Because building is the easy part. Maintaining, securing, updating, supporting, and scaling is where the real work lives.

That "one day" to build becomes one year to get SOC 2 certified. Two years to earn enterprise procurement approval. Five years to build the integration ecosystem customers depend on.

The average large company runs 350-400 SaaS apps because each one solved a problem they didn't want to own.

It's all been said before... WordPress was going to replace agencies. No-code was going to replace developers. AI is going to replace SaaS.

Each prediction confuses the ability to build with the ability to operate.

SaaS isn't dying. The bar for earning enterprise trust is just getting higher.

I got to be one of five returning guests who interviewed Sani for the No Hacks 5-year anniversary episode.

Five years. 218 episodes. Zero hacks.

That didn't happen by accident. It happened because Sani has spent five years doing the work, sharing what he learns, and earning trust the hard way.

Slobodan is one of the smartest people I know when it comes to the agentic web. He's also one of the most generous with his time and knowledge.

We're building PredictiveAX together on the side, helping companies prepare their websites for AI browser agents. Working alongside him has been one of the highlights of my career. 

Listen to this episode. It's packed with insights on where the agentic web is headed and what you need to do about it now.

Congrats on 5 years, Sani 🎉

We haven’t quite figured out how AI understand and uses the web we built for ourselves. I’m trying to do that. | Keynote speaker | Host of the No Hacks podcast (200+ eps)

After five years and 218 episodes I couldn't think of a better way celebrate than letting other people ask the questions for once.

I invited five previous guests to interview me for the anniversary episode. Kelly Wortham, Iqbal Ali, Talia Wolf, Jon MacDonald, Shiva Manjunath. Five different people, five different angles on the agentic web. One of them tried to convince me the whole thing is overhyped. (It didn't work)

Here's what kept coming up across all five conversations:

The basics are the strategy. A fully functional website built for humans gets you 80-90% ready for AI agents. Accessibility, semantic HTML, schema, page speed. The stuff you've been putting off? That's optimization now.

AI agents are already between users and websites. Chrome has 3 billion users and started shipping Gemini. Apple is putting AI into every device. There will be an AI layer in front of every interaction. Your website needs to be discovered, cited, and usable by that layer.

WebMCP is one of those things that could change everything. Right now it takes an AI agent 3-5 minutes to fill a basic web form. WebMCP gives agents a clean interface to your front end. It's still early, but if it lands as a standard, every website can become an agentic website.

The rankings model is dead. Prompting ChatGPT a hundred times and averaging your position to 4.7 is not measurement. Real tracking is just arriving. Bing launched AI analytics in beta last week. Google will have to follow.

Five years of this podcast and the message hasn't changed. No hacks. Just do it well. The difference is that now the cost to not doing it is higher.

Link in comments.

Every SaaS growth guide tells you to run A/B tests, offer free trials, and iterate quickly.

But what if your users are patients whose data you can't touch? Or bank customers protected by strict compliance rules?

I've watched too many regulated SaaS leaders give up on optimization entirely, believing their constraints make growth impossible. They see Canva and Spotify's success stories and think, "That could never be us."

They're half right.

Traditional product-led growth won't work when system failures mean massive fines or when your HR platform needs enterprise-wide rollout to function.

But here's what we discovered: You can validate hypotheses and optimize experiences before they ever touch your production environment.

Our research shows AI-powered heatmaps can predict user behavior with 92% accuracy, without requiring any actual user data. Lookalike user testing reveals friction points without exposing sensitive information. Rapid experimentation validates ideas before a single line of code changes.

It's off-site, experiment-led growth. Same insights, different methods.

Healthcare software. Fintech platforms. Government contractors. They're all growing within their constraints.

Your compliance requirements don't have to be growth blockers. For the full breakdown of tactics and implementation steps, check out the article below.

View newsletter: Digital Journey Insights

The traditional growth playbook falls short when compliance, privacy, and regulations limit your ability to experiment or follow product-led growth pr

Open article: Regulated SaaS Companies Need a Different Approach to Growth. What Actually Works? by Jon MacDonald • 8 min read

Regulated SaaS Companies Need a Different Approach to Growth. What Actually Works?

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