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Even if you don’t know Everett Rogers by name, you know his work. For decades, his theory on the Diffusion of Innovation has been taught as THE model for how new ideas (and products and startups and…) spread. If you’ve ever used the term “early adopter” then you know exactly what I’m talking about. But what if he was…wrong?
This week, we dig into how Rogers’ ideas can guide your GTM efforts — and where you should be careful not to put too much reliance on them as well.
Here’s what you’ll find:
This Week’s Article: Go to Market Is a Diffusion Problem,
Not a Sales Problem
Case Study: Quibi: Built to Spread, Failed to Stick
Share This: What if he was wrong?
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Go to Market Is a Diffusion Problem,
Not a Sales Problem
Most people overestimate how much their idea matters.
They underestimate how much its shape determines its survival.
If your product isn’t getting traction, the problem isn’t your pitch deck.
It’s that you’ve built something people can’t absorb, explain, or test.
You Can’t Sell Your Way to Adoption
Everett Rogers studied how humans accept change. His research wasn’t about startups or products. It was about how societies absorb new ideas. And yet we rely on Rogers' work to explain product and startup adoption every day.
Even if you don’t know Rogers by name, you certainly remember this diagram (Yeah, that guy ☝️ created this idea 👇):
Through his work, Rogers also identified five characteristics that determine whether, and how quickly something spreads. These five levers shape the way innovations reach people. They’re useful because they explain the structural friction in any go-to-market motion. And they still apply today, especially when you treat them as strategic design constraints, not academic theory.
Rogers’ five factors are:
Relative Advantage
Complexity
Trialability
Observability
Compatibility
Here’s what they mean in a go-to-market setting…
1. Relative Advantage → Make the win obvious
People only switch when the new thing is clearly better than what they already have.
How it shows up in GTM:
If a customer needs a meeting or demo to understand what makes your product better, it’s not better enough. Or your messaging is broken.
How to tune it:
Lead with outcomes, not features.
Benchmark against the real alternative (usually not your direct competitor, but inertia).
Make the win measurable, not aspirational. “20% faster workflow” beats “revolutionize your process.”
Ask yourself:
Can a customer explain your edge after reading your homepage for 15 seconds?
2. Complexity → Remove friction before you add features
The more complex something feels, the slower it spreads. Even if it works better.
How it shows up in GTM:
Lengthy onboarding, unfamiliar jargon, setups that feel like a commitment.
How to tune it:
Strip down your core offering to the minimum people need to experience value.
Speak in language your user already knows.
Hide complexity until it’s necessary. Default settings exist for a reason.
Ask yourself:
Can someone understand how this works without a sales call or training session?
3. Trialability → Let people test before they commit
People adopt things faster when they can try them in a low-risk way.
How it shows up in GTM:
Free trials, pilots, MVPs, and previews. But also: whether those are actually useful or just marketing.
How to tune it:
Give a real taste of value in the trial, not a bait-and-switch.
Let users keep what they build, even if they don’t convert.
Shorten time to first win.
Ask yourself:
Can someone experience a meaningful benefit in under an hour?
Minimize the time-to-value.
4. Observability → Make success visible
People copy what they see working for others.
How it shows up in GTM:
Lack of visible use cases, silent users, no public proof of success.
How to tune it:
Design for show-off moments.
Highlight real use. Not testimonials, but screenshots, behavior, network effects.
Make wins public, whether through case studies, social proof, or integrations.
Ask yourself:
What does the world see when someone wins with your product?
5. Compatibility → Fit the behavior, not the fantasy
People adopt new things faster when the new things feel like extensions of existing actions and habits, not replacements.
How it shows up in GTM:
Ideas that demand the user think or act differently from day one. Innovations that ignore current tools, workflows, incentives.
How to tune it:
Meet users where they are, even if you plan to move them later.
Integrate with their stack instead of asking them to switch.
Map your onboarding to existing rhythms, not ideal ones.
Ask yourself:
How does this fit into what they already do today?
The Innovation Might Win. You Might Not.
Jason Voiovich has spent years dissecting how innovation plays out historically. (And he’s incredibly knowledgable about the history of innovation. Keep an eye out for our upcoming podcast episode!) Not in theory, but in practice. His take on Rogers is clear: understanding diffusion is helpful, but it won’t save a bad product.
Innovation only seems inevitable in retrospect. Many innovations never achieve 100 percent of their potential market. But more to the point, technologists are not paying attention to a simple point of language: Innovation is not the same as a single idea, product, or service. The innovation may succeed. You may not.
Rogers explained why some ideas spread. Voiovich explains why yours might not.
Even if you check all five boxes. Even if your product is better, simpler, testable, visible, and familiar… It still might not work.
Because diffusion is a pattern. Success is a case study.
External forces matter: timing, incumbents, market conditioning, and path dependence all shape outcomes. You’re not just battling product-market fit. You’re battling innovation entropy.
Visualizing the Innovation vs. the Case Study
Voiovich’s breakdown of the gap between diffusion theory and actual outcomes is visible in two charts:
The first is the textbook model as outlined by Rogers.
What it shows: A smooth, idealized S-curve.
What it assumes: That innovations naturally progress through adoption stages (innovators, early adopters, early majority, etc.) if they meet the five criteria.
The story it tells: Innovation adoption is predictable and progressive, assuming the right traits are in place.
The second shows the messier reality most products face.
What it shows: Disruption, dropoffs, fragmentation, non-linear chaos.
What it reflects: What actually happens when new ideas hit market noise, user resistance, timing issues, and unpredictable external factors.
The story it tells: Even well-designed ideas often fail to cross the gap. Adoption isn’t just a matter of traits, it’s conditional and volatile.
The difference is sobering. One is a model. The other is a graveyard.
Final Note: Adoptability is Design, Not Luck
Rogers gave us the framework. Voiovich reminds us not to become beholden to it.
You can’t pitch your way out of poor design for adoption. If your go-to-market isn’t built on these five factors, no amount of funding or founder charisma will save you.
Still, these five levers are what you can control. If you’re not seeing traction, don’t blame timing. Redesign the idea until people can’t not use it.
Quibi: Built to Spread, Failed to Stick
Quibi checked all five boxes on the diffusion model:
Relative Advantage
It promised mobile-first, professional-quality streaming at a time when TikTok was still mostly dancing teens and YouTube hadn’t cracked short-form monetization. The edge was clear: "Quick Bites. Big Stories."Complexity
It launched with a dead-simple UI. Open app. Pick show. Watch in portrait or landscape. No remote. No setup. Just play.Trialability
Free trial for 90 days. No strings. No credit card tricks. Plenty of content to sample.Observability
Backed by celebrity creators, splashy trailers, and Super Bowl ads. Visibility wasn’t the problem.Compatibility
Designed specifically for mobile commuters and quick consumption. It mapped directly to the “scroll and swipe” habit of the target user.
And yet... Quibi cratered within six months.
The idea was sound.
The execution was fast.
The founders were pedigreed.
The capital was there.
So what went wrong?
Voiovich might say: everything else.
The context shifted.
The pandemic killed commuting, and with it, the core use case.User behavior didn’t adapt.
People already had YouTube, TikTok, and Instagram. Quibi was new, but not better enough.The innovation was real. The adoption was not.
Quibi didn’t fail because it ignored Rogers’ ideas. It failed because Rogers' five factors aren’t a shield from entropy. They describe conditions, not guarantees.
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