The GTM Slop Problem, Part 1: The Real Reasons B2B Tech Launches Fail
- 7 days ago
- 11 min read
Note to readers: This is the first article in a six-part series on why so many B2B software and AI product launches fail. In the articles ahead, I’ll cover the six areas that matter most to a successful go-to-market effort: narrative, ICP and targeting, competitive readiness, offer and proof, field enablement, and activation + measurement.
Each piece will use real-world examples to cut through the hype, call out what gets glossed over, and get back to the fundamentals that actually determine whether a launch works or quietly dies.
Most B2B software launches fail not because the product lacks value, rather because the company never fully translates that value into a story, offer, and field motion people can understand. It is rarely one big dramatic mistake that causes the fizzle, rather several smaller gaps that build on each other.
I’ve spent a career commercializing technical B2B software products across AdTech, MarTech, data, and measurement. These were not easy products to explain, package, or sell. They were complex offerings in competitive markets, where buyers needed more than a feature list to understand the value.
More often than not, product teams are consumed by sprint targets and roadmap pressure. They don’t always have the time, or the commercial lens, to turn product capability into a clear market story.
So what reached the field was often incomplete. Instead of a client-value-centered play that sales and account teams could use with confidence, they got a loose set of features, claims, and assumptions.
That is what I mean by weak commercialization, or what I call “GTM slop.” It has nothing to do with product quality. I’m talking about the commercial system around the product that determines whether the market understands it, values it, and buys it.
This has been a persistent problem in software and technical markets for years, and it has always had real business consequences, whether we admit it or not. In today’s buying environment, those consequences compound faster.
When companies feel this gap, executives and investors usually respond the same way: hire a branding agency, add a PR firm, or build out more product marketing and general marketing support. But that rarely fixes the real issue.
Agencies and marketers can help shape the message, but they usually don't have the depth of product understanding that lives with PMs or the voice-of-customer and use-case knowledge that sits with sales, account, and support teams.
So the work gets pushed to people who are, at a minimum, one step removed from the product and the buyer. The result often feels exactly that way: polished on the surface, but thin on substance and disconnected from how the product actually creates value.
The result is GTM slop. The underlying problem is not new, but AI has made it easier to mass-produce. GTM slop is what happens when a company goes to market without the launch intelligence needed to translate product value into clear market distinction. Too many B2B SaaS companies and AI point solutions are generating more outreach, more messaging, but definitely not more differentiation.
Just because you build something does not mean buyers will come. And just because AI makes it easier to create go-to-market content at scale does not mean that content is worth anything to the buyer.
In fact, it often makes the problem worse. Slop, the word of the year according to the Merriam-Webster dictionary, is the flattening of real differentiation. “AI Slop is Everywhere,” warned The Wall Street Journal, and for B2B SaaS and AI products, it means more volume, claims, and activity with less of anything that actually helps a buyer understand why you matter. One company starts to sound like every other company. Buyers are left with a sea of sameness, and that quickly becomes noise.
Most people do not have the time, or the patience, to dig through all of it in search of the one company that actually has something clear and meaningful to say. I see it in my own day-to-day life. I get hundreds of pitches weekly, and maybe one in a thousand (0.1%) breaks through as remotely distinct. That is about as effective as the dismal click-through rates of programmatic display advertising (0.05-0.1%). Think about that.
The simple fact is that half of all product launches fail. That sounds harsh, but the data backs it up. McKinsey has found that more than 25% of total revenue and profit across industries comes from launching new products and services, yet 50% of launches do not meet their targets.
In other words, launches are one of the clearest growth levers a company has, and one of the easiest to get wrong. I’ve seen the same pattern in private equity portfolio analyses over the last few years. The companies that innovate and launch well tend to outperform on ARR growth, often by a wide margin.
This gets even more painful in software and AI, where early traction is not the same thing as a scalable business. McKinsey’s 2025 scale-up research found that 78% of companies that successfully build a product and find product-market fit still fail to scale. So even when the product is real, something in the commercial system still breaks.
Odds of start-ups with successfully built product to achieve scale-up
The B2B tech buying process is harder than it has ever been to manage. Forrester says the average B2B purchase now involves 13 people, and 89% of purchases involve two or more departments. 6sense says 69% of the purchase process happens before buyers engage sellers, and 84% of buyers choose a preferred vendor before speaking with sales.
This means a launch or GTM initiative is not starting from zero. Buyers are already researching, comparing, filtering, and forming opinions before your sales team is even remotely involved.
So here’s the core problem. Most companies still treat launch like a campaign tied to a date and a set of deliverables. Maybe it’s a webinar, a product announcement, or a burst of LinkedIn posts followed by heavy pipeline pressure. If the company is especially organized, there may also be a cross-functional checklist. But a launch (or GTM initiative) is not a campaign. That is the fatal flaw.
It is a test of whether the company is commercially coherent.
If your story is vague, your ICP broad, and the feet on the ground are saying different things, your prospects and clients will feel it instantly. Buyers may not describe it that way, but that is what they are reacting to. They are reacting to a company that is not actually ready.
This is the part people miss. Launches usually break not because teams are lazy or because nobody cared. They break because each function is built for something different. Product is trying to deliver solutions that work. Marketing is trying to generate attention. Sales is trying to create pipeline. Customer Success is trying to grow client accounts and protect renewals. Finance is trying to keep the forecast grounded.
Those are all reasonable goals. But no one, by default, owns the integrity of the whole commercial system.
That is how you end up with familiar problems. Product promises flexibility but sales sells certainty. Marketing pushes a category story that the product may not support. The website sounds bold, but legal has quietly stripped proof out of the claims. Customer Success inherits deals that were closed with language the product team would never have approved. Pipeline looks healthy on paper, but conversion tells a different story. Everyone is working, but the system still breaks.
McKinsey found the same pattern in broader growth efforts. In a review of 60 growth transformations, more than half failed to meet their targets, and the recurring issues were not mysterious: weak alignment, unclear goals, and poor monitoring. That should feel familiar to anyone who has watched a launch move forward while leadership still disagrees on the story, the buyer, or what good looks like in the first 90 days.
Slack vs. Quibi One launch taught the market, the other misread it
Slack entered the market with a clear problem to solve and a product teams could adopt naturally. Quibi entered with plenty of hype, but a shakier link between the offer, the audience, and the real behavior needed to sustain it.
Slack is still one of the cleanest examples of a strong product launch. What Slack understood early was that it was not just selling a product. It was helping buyers recognize a problem. Stewart Butterfield, Slack’s founder, said only 20% to 30% of early users came from existing team messaging products. The other 70% to 80% said they were using “nothing,” which really meant a jumble of email, text, Skype, Hangouts, and random workarounds.
Slack had to explain the category before it could win the category. When its preview launched in 2013, 8,000 people requested invitations on day one, and 15,000 had done so within two weeks. But the real win was not the waitlist. It was the clarity of the use case and the discipline of iterating in waves before scale.
Quibi is the opposite lesson. Reuters reported that Quibi moved to wind down operations just six months after launch. Some called it the “$2B dumpster fire that was supposed to revolutionize Hollywood.” On paper, it had everything people usually point to as signs of success: major funding, top-tier talent, big-name founders, and plenty of attention. But those strengths masked a weaker reality.
Quibi was asking consumers to pay for premium short-form mobile video in a market already full of free content, established streaming platforms, and deeply ingrained viewing habits. The launch did not fail because people had never heard of it. It failed because the offer, the behavior it depended on, and the value it promised never lined up tightly enough.
People can still debate how much COVID changed the timing, whether mobile-only premium short-form video was always the wrong bet, or whether the category itself never had enough pull. But none of those points really changes the lesson.
The product idea, buyer behavior, offer logic, and commercial system did not come together in a way that could hold. That is what launch failure looks like in the real world. Not “we needed more awareness,” and not “the campaign underperformed.” The system was weak.
GitHub Copilot vs. Microsoft Recall One entered the market ready, the other got exposed fast
The GitHub CoPilot launch entered the market with a clear use case, easy adoption, and proof buyers could understand. Microsoft's Recall entered with unresolved trust questions the market picked up on immediately.
GitHub Copilot is a more recent example of a capability launch that worked because the value was concrete and the proof showed up fast. GitHub said more than 50,000 organizations had adopted Copilot, and in its enterprise research with Accenture, 81.4% of developers installed the IDE extension the same day they received a license. Of those who installed it, 96% started receiving and accepting suggestions that same day.
Accenture developers also saw an 8.69% increase in pull requests and a 15% increase in pull request merge rate. That is a much stronger launch pattern than broad AI hype. The use case was clear, the workflow fit was obvious, and the proof was specific enough for buyers to believe.
Microsoft Recall, in contrast, is a reminder that a compelling idea can still fail the readiness test. Reuters reported that Microsoft pulled back the broad rollout of Recall and limited it to a smaller preview after privacy concerns surfaced. Recall was presented as an AI feature that tracks activity across web browsing, voice chats, and other on-device behavior so users can search their history later. But that same promise quickly triggered the harder questions buyers and users were always going to ask about privacy, trust, and misuse.
Microsoft moved the feature into the Windows Insider Program instead of releasing it broadly to Copilot+ PC users on schedule. That is what happens when a capability may sound powerful in a keynote, but the readiness gaps are still obvious the moment the market gets a closer look.
Chalice AI: A clearer commercial story for agentic media buying
After a recent Signal & Noise interview of Adam Heimlich, CEO of a new AI AdTech company Chalice AI, one thing stood out right away: this is not just another company wrapping itself in AI language.
Chalice is tackling a real infrastructure problem Adam knows firsthand from years inside agencies and programmatic media. The core issue is that today’s buying systems still do a poor job of using the full range of signal available, especially contextual and page-level signals, at the moment of ad decisioning. Chalice’s answer is not a vague promise of “smarter automation.” It is a more fundamental rethink of how bidding works, using a containerized RTB model and the broader Agentic RTB Framework (ARTF) to make better use of data, control, and real-time intelligence. That is what makes the company such a strong GTM example. The technology is advanced, but the commercial story is clear.
What Chalice is also doing well is connecting that story to real proof and broader market momentum. Adam pointed to an early Zillow campaign where Chalice improved cost per lead performance by roughly 40% versus a DSP on its own by applying richer context and better signals around whether a lead was actually likely to become a real home shopper.
Just as important, the company is not trying to push this as a closed, proprietary narrative that lives only inside its own marketing. It has taken the idea into the industry through the IAB Tech Lab, built support from major infrastructure players like OpenX, and given agencies a clearer way to think about how AI can drive better media decisions rather than just more automation. That is what strong launch execution looks like: a sharp problem definition, a differentiated point of view, early proof, and real ecosystem pull.
If Slack showed what category creation looked like in an earlier era, and GitHub Copilot showed what a well-framed AI capability launch can look like now, Chalice is a more current example of a company coming to market with a clearly defined problem, a distinct thesis, and enough early evidence to make the value real.
By contrast, examples like Quibi and Microsoft Recall show what happens when the offer, the behavior it depends on, or the trust questions around it are not worked through tightly enough before launch.
The launch intelligence gap
This is the gap I’m trying to name. Companies assume they are launch-ready because the product is moving, the assets are in motion, the messaging deck exists, and a date is on the calendar. But those things are not the same as readiness. Real go-to-market readiness means the launch can survive contact with actual buyers, real competitors, and the messy handoffs between product, marketing, sales, and customer teams.
That is where a lot of launches get exposed. The story sounds good in an internal review, but weakens the moment a buyer asks a hard question. The targeting looks broad and ambitious, but nobody can say where the first real wins should come from. The roadmap gets mixed into the pitch, proof is thinner than it should be, and the field ends up filling in the gaps on its own. By the time the company realizes what is happening, the market is not reacting to the product alone. It is reacting to confusion around the product.
What strong launches share
The product, solution, or company launches that work tend to share a few traits. They start with a sharp story, not a pile of features. The initial buyer is tightly defined rather than broadened to the whole market on day one. What is true now is kept separate from what is still on the roadmap. Proof gets built early instead of being assumed. Product, marketing, sales, and customer teams are aligned before the message is amplified. And the company knows what it is watching in the first 30 days, so it can adjust quickly without debating what success even means.
The GTM readiness test
Before a company goes to market with something, leadership should be able to answer a few simple questions without hedging. Can every executive explain the launch in under a minute? Can sales describe the first 25 conversations they want to have? Can the top three claims survive a skeptical buyer and a competitor response? Do you know what proof exists, what proof is missing, and who owns closing the gap? Can the field handle top objections without improvising? Are the metrics, owners, and first 30-day review cadence locked before launch?
If the answer to several of those is no, the company is not ready. It is just active.
Most launches fail not because the market rejected a well-aligned commercial story, but because the company pushed an unfinished one into the market and tried to hand-wave past the gaps.
It never works.
Over the next six pieces, I’ll break down the six ‘launch intelligence’ layers that sit behind a successful go-to-market initiative: narrative, ICP and targeting, competitive readiness, offer and proof, field enablement, and activation and measurement.
Next article: Why narrative is not messaging fluff, rather the commercial logic that determines whether buyers understand, trust, and buy. Check it out on www.signalandnoise.ai.
About Brett House
Brett House is a go-to-market and commercialization leader with more than two decades of experience helping B2B software and AI companies bring complex products to market. He is the Founder and CEO of HighSignals and Co-Founder of Signal & Noise, where he writes and advises on launch strategy, commercialization, and growth across software, data, and AI.