PLG as a Category Claimed by OpenView Partners

What Blake Bartlett did after coining "Product-Led Growth"

Most companies try to win by building a better product. A sharper move is naming what the product represents before anyone else gets there first. That's a language act before it's a market act, and it affects who gets to define the category's terms from the outset. Whoever coins the term decides who belongs inside the category, who's an outsider looking in, and who gets final say on what the word actually means.

Compete inside a category somebody else named, and every pitch becomes translation work into their vocabulary. Naming the category yourself makes you the dictionary. Everyone else has to cite you, argue with you, or quietly borrow your words without credit, which is the highest compliment a term can get.

OpenView Partners did this on purpose with "Product-Led Growth." Not as a slogan, but as a firm-wide bet with a budget and a timeline behind it.

Blake Bartlett, a partner at OpenView, coined the term in 2016, though the idea had been walking around unnamed for a few years before that. Back in 2013, OpenView's own bio copy for Bartlett described him as helping identify "product-led businesses driving market dislocation." The concept was there. The label wasn't. In 2014, Bartlett published a blog post called Product-Market Fit Is Not Enough, an early, unbranded shot at the thesis that would eventually get a name.

Then in 2016, the label showed up. Bartlett started using "PLG" explicitly, tested the phrase on a community webinar that June, then took it further out on the SaaStr podcast with Harry Stebbings. A keynote at SaaStr 2017 put the term in front of a much bigger room.

OpenView's definition, the one it anchors to its own coinage, stays simple: PLG is a go-to-market strategy where the product itself does the heavy lifting on acquisition, conversion, and expansion. The product sells itself, or at least does most of the convincing before a human ever gets on a call.

Scott Maxwell, the firm's founder, made PLG the number one narrative message across the entire firm. OpenView's stated goal for 2018 read like a mandate: "Put PLG on the map." Every team got a piece of that job. PLG West and PLG East summits ran. The BUILD podcast built entire seasons around the term. Every blog post on the site touched it somehow. The firm even audited its own executive network, tracking what percentage counted as PLG leaders, like a fitness tracker but for vocabulary adoption.

The quote that sums up the intent still holds up: "As a team we decided to commit to category creation. It couldn't be a side project." That's an operating decision.

Bartlett knew the bet had paid off when people he'd never met started using the term like it was public property. Wes Bush, who ran ProductLed (formerly Traffic is Currency), became one of the loudest independent champions of PLG outside of OpenView.

What category ownership looks like when it lands

"PLG" appeared in public company earnings calls and registration filings by 2020 and 2021. CEOs at companies from MongoDB to Toast used the term like it had always existed, the way people say "Google it" without picturing a search engine.

Other venture firms picked it up too, and not quietly. Tomasz Tunguz at Redpoint Ventures predicted in 2021 that product-led growth would become the standard go-to-market model for software and infrastructure companies. A competitor amplifying OpenView's own vocabulary. Bessemer's State of the Cloud report named product-led growth as one of three go-to-market strategies top cloud companies were using in what it called the "New Normal." Another firm's flagship research, built on a frame OpenView built first.

None of that amplification credited OpenView directly, and that's exactly the point. When rival firms, public company executives, and sell-side analysts all use your term without footnoting you, something more durable than brand awareness has happened. Your vocabulary has become the industry's vocabulary. Nobody thanks the dictionary for the word "email."

OpenView backed that position with permanent reference material: framework pages and resource guides laying out what counts and what doesn't. These function as permanent reference points, sitting there indefinitely, available whenever someone needs a baseline definition.

A quieter effect follows from that. Once a category has an author, everyone entering it has to position themselves relative to the original definition, extend it, or push against it explicitly. Call it a tax. Every growth-led startup shaped by that framework, and every competing firm's research report, owes something to the original coinage. There's no neutral entry point left.

The financial case that PLG companies made for the category

Naming a category is one move. Getting the numbers to back it up is a different one entirely, and this is where PLG stopped being a clever phrase and started being a testable claim.

OpenView's own analysis, using Pitchbook data, looked at companies it classified as "PLG leaders": Snowflake, Datadog, HashiCorp, Confluent, DigitalOcean, Zoom, defined as having adopted at least nine of eleven PLG principles. These companies carried a median EV/revenue multiple of 15.7x. They grew 50% year-over-year, with net retention at 128%.

Traditional SaaS companies over the same stretch: 21% year-over-year growth, 114% net retention. Not close, and not a fair fight.

That gap did something content marketing alone never could. It turned "PLG" from a label into a measurable, repeatable phenomenon. Once a performance differential attaches itself to a term, skeptics can't just argue with the framing anymore. They have to argue with the spreadsheet, which is a far less comfortable fight to pick.

This is OpenView measuring its own category, using its own definitions of who counts as a "PLG leader."" Nobody has more granular data on this than the people who coined the term. The numbers deserve some skepticism alongside the credit. Both things are true at once, and neither cancels the other out.

The second-order problem: what a category creator says when its category becomes the default

Winning creates a new problem, and it's the one most category creators don't see coming until it's already arrived.

OpenView has acknowledged, in its own retrospectives, that when it coined PLG in 2016, the firm believed it was describing the future of SaaS. By the time the term moved from novel to normal, from clever insight to a line in every pitch deck, the firm needed a new frame to stand on.

Their answer was something called the "Age of Connected Work," a narrative layer built on top of the original PLG framework rather than a replacement for it. Extension, not abandonment.

That move points at a structural problem every category creator eventually runs into. A category that wins becomes common property. Competitors adopt the vocabulary. Consultants package the playbook into a slide deck and sell it back to the market. The originator's edge, the thing that made them the reference point, erodes just by sitting still. Standing on your own success works like standing on a treadmill: stable right up until it isn't.

The available move is to define what comes after the category before a competitor gets there first. That's a second act of category creation, and it demands the same institutional discipline the first one did, not a lighter version of it. Most companies miss this because they treat their category name like a trophy on a shelf instead of a position that needs upkeep. A trophy doesn't need maintenance. A market position does, constantly.

What OpenView's playbook reveals about language as organizational infrastructure

The PLG push wasn't a campaign with a start date and an end date. It ran closer to plumbing: something threaded through the whole firm, quietly producing that effect regardless of anyone's attention.

The real distinction is narrative as campaign versus narrative as infrastructure. A campaign gets built by the marketing team, has a shelf life, and gets measured in impressions. Infrastructure governs how decisions get explained internally, how a firm identifies which portfolio companies fit its thesis, how network penetration gets measured, and how the whole frame gets updated once the category matures.

Firms with strong narrative infrastructure build something like muscle memory: the ability to make consistent strategic calls across the whole organization without re-arguing the core idea every time someone new joins. Most enterprise B2B organizations run the opposite setup, with bits of a narrative scattered across old pitch decks, current website copy, and whatever the sales team happens to be saying on calls that week. No single source of truth, and nobody governing any of it.

OpenView's tracked metric, the share of its executive network counted as PLG leaders, is a small but telling example of narrative governance. OpenView tracks that metric as part of its broader effort to monitor category adoption.

A financial angle backs this up too. Research on brand experience has found that brands leading in narrative coherence see meaningfully higher customer preference and greater willingness to pay a premium than those with fragmented messaging. Treating language as infrastructure isn't a nice-to-have. It pays rent.

The silent cost of language drift for category creators

Without documented rules for how a term gets used, language drifts. Every new writer, every agency, every contractor, every fresh hire brings a personal interpretation to the table. The category name survives. Its meaning doesn't, and nobody notices until the gap is wide enough to trip over.

Software has a useful word for this kind of decay: technical debt. The term was coined to describe what happens when a team ships a quick fix instead of a proper solution. The cost of that shortcut compounds over time instead of appearing once and going away. A report from Oliver Wyman put a number on that compounding: technical debt has grown by roughly $6 trillion globally, nearly doubling in scale.

Language debt works the same way, and it's worse in one specific respect: nobody budgets for it. Loose or undefined terminology doesn't cost you once. It charges interest, in the form of slower decisions, teams talking past each other, sales pitches that don't land because two reps described the product two different ways, and eventually, a loosened grip on the category the company started.

The same research extends into what it calls "skills debt." Organizations still running COBOL, a language over 60 years old with an estimated 220 billion lines of code still powering something like $3 trillion in daily commerce, run into trouble because nobody left inside the building can explain what the system is actually doing anymore. Organizations running on stale narrative frameworks hit the identical wall. Nobody inside has the words to explain the current strategy accurately, because the words drifted out from under them years ago.

The media pitch says one thing, the CEO says something slightly different on a podcast, and the website presents a third version. The market notices the mismatch. Increasingly, so does anything reading that content automatically.

AI's effect on the stakes of narrative ownership for category creators

Businesses have broadly begun adopting large language models somewhere in their workflows, with adoption spreading rapidly across industries. Most companies now generate language at scale through systems that can't tell an official definition apart from someone's sloppy first draft.

LLMs work as narrative amplifiers. They write content, answer customer questions, draft sales one-pagers, produce internal docs, summarize research, all using whatever vocabulary they've been fed. Feeding an LLM a fragmented, inconsistent vocabulary makes it reproduce that fragmentation at a scale no single sloppy employee could ever match alone.

There's an opportunity sitting right next to that risk. A company with a well-governed vocabulary, canonical definitions, consistent framing, a category name with an agreed-upon meaning, gets that vocabulary reproduced accurately, and fast, across every piece of AI-generated output that touches it.

Domain-specific models make this concrete. BloombergGPT, built for finance, Med-PaLM, built for medical question answering, and ChatLAW, built for legal work, all operate inside a tightly defined domain vocabulary instead of trying to speak every language at once. The lesson for category creators follows directly: the company that names a category also gets first crack at defining the vocabulary that AI systems eventually learn to associate with it.

Applied back to PLG, OpenView's decade of blog posts, summits, podcasts, and market maps forms exactly the body of text that shapes how an AI system comes to understand and represent a category. That corpus becomes training signal regardless of how OpenView framed it.

The inverse carries the real danger. A company that lets its own narrative fragment, or never bothered to define its category vocabulary in the first place, risks having AI systems represent it inconsistently, or worse, represent a competitor's framing instead. Narrative precision used to sit under the marketing department's job description. Now it functions closer to a prerequisite for operating an organization that runs on AI. The language a company runs on today is the language its AI tools will scale tomorrow, for better or worse.

What founders and investors can replicate from the PLG playbook

The OpenView model breaks down into steps any founder or investor can actually copy, and none of them require a genius insight, just discipline applied consistently.

Start by finding the gap: some behavior or pattern in the market that existing words don't quite capture. Coin the name, then commit the whole organization to it as a strategic pillar with real, measurable targets attached, unlike a tagline that lives on a slide for one quarter. Build reference material around it (the canonical definition, the framework, the market map, the resource guide) so the organization becomes the place people go to check what the term actually means. Push that material through every channel available until strangers start using the term without crediting anyone.

Then govern it. Audit for drift, track penetration, review the framing on a regular schedule instead of assuming it'll hold its shape forever. And plan the second act early, because the moment a category goes mainstream is the moment it stops belonging to anyone in particular.

For investors, the lesson runs deeper than deal flow or check size. Language, treated as a platform capability rather than a marketing afterthought, produces its own measurable returns, and most firms leave that asset sitting on the table entirely, untouched, like a check nobody bothered to cash.

For founders at the growth stage, the window for naming a category stays narrow. It opens right before the category has a name and slams shut the moment a competitor names it first. If the company misses that window, it spends the rest of its life arguing inside somebody else's frame.

AI just tightens that window further. The company that governs its language today trains the systems that will describe it, accurately or not, for years to come.