# Matching Product Strategy to Innovation Stage

- Link: https://www.andreidraganescu.info/2025/09/17/matching-product-strategy-to-innovation-stage/
- Published: 2025-09-17T14:20:16+03:00
- Author: Andrei Draganescu

Product theory is full of competing commandments. “Build an MVP.” “Cross the chasm.”“
Disrupt yourself.” “Bundle or unbundle.” Product managers, founders, and leadership
in general, juggle them, quoting whichever one fits the current deck. The theories
are great: most are drawn from empirical evidence.

A problem I noticed in time is that we treat them as stand-alone. I believe, in 
reality, they’re just milestones on one curve: Everett Rogers’ _Diffusion of Innovation_.

![](https://www.andreidraganescu.info/wp-content/uploads/2025/09/image.png)

Innovators, early adopters, early majority, late majority, laggards — the shape 
is familiar, a Bell curve.

“Diffusion is the process by which an innovation is communicated over time among
the participants in a social system” says the observer of this phenomenon, Everett
Rogers. An old thing hailing from 1962! Still holds. That diffusion curve isn’t 
just sociology; it’s a product compass. Each stage of the curve makes a different
product strategy valid. Misapplying them out of place can doom great products, despite
good execution.

⸻

### Experiments and R&D → Innovators

At the very left, there is no “market.” Here there be only innovators — the few 
who adopt for curiosity’s sake. This is where experiments and **academic** R&D belong.
Throwing products at this zone is malpractice. Paraphrasing someone famous, the 
purpose of invention is learning. You don’t need MVPs here. You need experiments,
often ugly, often useless in market terms, but generative.

Google X embodies this. Projects like Loon or self-driving cars weren’t products;
they were hypothesis engines. Innovators engaged because they wanted to explore.
The congruence worked.

Juicero didn’t see it like that. It took what was effectively a food-supply experiment
and launched it as if the early majority were waiting. The mismatch: _users were
still innovators of cold-pressed juice supply chains, but Juicero used a product
strategy fit for optimisation and scale_. The result was ridicule and collapse.

At this stage, launches are dangerous. Each one ratchets expectations. Too many “
launches” of half-science and the market stops taking you seriously. There may be
such a thing as **launch debt**: the erosion of trust capital with every premature
reveal.

⸻

### MVP → Early Adopters

Once an idea turns into a possibility, it enters the **product** R&D and MVP stages.
In the lean startup it’s called “that version of a new product which allows a team
to collect the maximum amount of validated learning with the least effort”. MVPs
are for early adopters — people willing to tolerate roughness in exchange for vision.
At this stage of innovation diffusion it’s about testing hypotheses with customers,
not satisfying demand.

Tesla’s Roadster was exactly that. An overpriced, jury-rigged sports car, it wasn’t
meant for scale. It was meant for believers. Those early adopters gave Tesla data,
legitimacy, and patience. The alignment, perfect: MVP strategy with early adopter
audience.

Fisker Karma? The exact opposite. It launched as though the early majority were 
ready for electric luxury sedans. But reliability was catastrophic. The mismatch:
_users were early adopters of EV tech, but Fisker treated them as a late-majority
market expecting optimisation_. Trust imploded.

Tesla framed its Roadster as a stepping stone but Fisker sold the Karma as a revolution
already past.

⸻

### Fast Iteration → Early Majority

When a product tries to leap into the early majority, it goes through the famous
dangerous place, coined by someone named Geoffrey Moore: The Chasm. Pragmatists 
don’t care about your vision. They want a safe bet. The only way across is visible,
relentless iteration. Fast iteration is as essential for success as a YouTube thumbnail’s
weird facial expressions and pointing fingers.

Amazon Web Services nailed this. EC2 launched with bare-bones compute, but the drumbeat
of new instance types, storage, and networking every quarter reassured customers.
The strategy was congruent: _fast iteration for an early-majority audience_. The
pace itself created confidence.

HP Cloud stumbled. It entered the same market but rolled out features at a glacial
pace. Worse, it packaged itself as a mature bundle. The mismatch: _users were early
majority of cloud compute, but HP approached them with bundling and optimisation_.
Customers defected to AWS before HP could close the gap.

Iteration here isn’t just product. It’s messaging, onboarding and support. For this
to work, commitment is key. Commitment of people, cash, risk, loss. But the chasm
IS a dangerous place after all.

⸻

### Optimisation → Late Majority

Once adoption tips, the late majority arrives. Their demand is stability, price,
reliability. In a book from the previous century it says “Disruptive technologies
bring to a market a very different value proposition than had been available previously”.
But at this stage of diffusion the opposite is needed, sustaining technologies. 
The optimisations, are what the late majority values. You’re no longer trying to
prove the product works. You’re trying to prove it scales.

AWS again provides the yes. By the 2010s, it turned its energy to cost reduction,
enterprise compliance, and reliability. Optimisation strategy for late-majority 
users.

Webvan shows the no. It invested billions into optimised logistics — warehouses,
fleets, automated systems — but grocery delivery itself was still in MVP territory.
The mismatch: _users were early adopters of online grocery, but Webvan acted as 
if they were late majority demanding optimisation_. The infrastructure collapsed
under lack of demand.

Optimisation also means operational trust. The late majority wants compatibility
and enterprise support.

⸻

### Bundling → Maturity

At saturation, innovation slows. Commodities emerge. A supple and nice line from
the COO of a long sunset company says: “There are only two ways to make money in
business: one is to bundle; the other is unbundle.”. Maturity is bundling time.

Adobe got this right. Photoshop, Illustrator, Premiere — individually powerful, 
but together irresistible as Creative Cloud. Users were late-majority creatives;
bundling gave them convenience and predictability.

Google+ got it wrong. It tried to bundle messaging, social graph, photos, and video
before it had won any one product. The mismatch: _users were early adopters of online
identity, but Google+ deployed a bundling strategy fit for maturity_. Nobody wanted
the bundle.

⸻

### Unbundling → Renewal

When bundles calcify, resentment brews. That’s when unbundling strikes. We host 
a famous blog with a whole concept dedicated to Bundling and Unbundling. It shows
the history of the technology industry has been one of bundling and unbundling in
turn. Unbundling is often how disruption sneaks in.

Slack is the yes. It unbundled team communication from the bloated email bundle.
Users were maturity-stage email sufferers; unbundling gave them relief.

Yahoo is the no. It resisted unbundling, stuffing news, chat, search, groups into
a portal that tried to be everything. The mismatch: _users were maturity-stage web
users hungry for unbundled excellence, but Yahoo doubled down on bundling_. The 
portal rotted.

Unbundling works because mature bundles calcify. Customers resent paying for bloat
they don’t use. New entrants exploit that resentment by stripping to essentials.
Like say … make a blog out of markdown files only, and a whole website out of souped
up JavaScript. Or host static sites like it’s my childhood.
⸻

### A Tool to Check Against

So what’s left is not theory, but alignment. The innovation stage tells us which
playbook to run. Fail to match them, and the market will fail us.

Here’s a simple self-test:

 * Am I calling this an experiment when users expect a product?
 * Am I shipping an MVP to pragmatists who expect reliability?
 * Am I iterating when users want optimisation?
 * Am I optimising before adoption proves demand?
 * Am I bundling without a single market win?
 * Am I clinging to bundles while customers are peeling away?

⠀
If we answer “yes” to any, we out of sync with the curve. Each of the product 
strategies are valid, but only if the core innovation of the product is in a diffusion
stage that matches correctly. The diffusion is slow and patient. There is time even
for mistakes, but wait enough and it punishes mismatches quite badly.
