Ethos

We don't sell your data. We use it to make your decisions better.

No surveillance playbook, no lead brokering, and no vendor kickbacks — we earn trust by utility, not by selling your attention.

Most GTM data is built on surveillance. Ours isn't.

Something has gone wrong with how this industry thinks about data.

We do not accept that premise. StackSwap was built on a different one.

The premise is disarmingly simple: if you build something genuinely useful, people will tell you the truth voluntarily. Not because they've been tricked. Not because a pixel fired. Because the tool they're using works better when they give it real information, and they can see the value of that exchange immediately, on their screen, in their results.

The vow

Our binding commitments

Our tools are designed to be immediately useful, without friction, login requirements, or artificial barriers. You should be able to get real value before being asked for anything. That posture is not a stunt — it is how honest signal is earned. Login walls and performance theater train people to lie; we would rather compete on usefulness first and let the rest follow.

Some deeper layers of intelligence — the parts that require the most computation, modeling, and precision — may be paid. Not because access is restricted, but because precision has a cost. Monetization, for us, is not about charging you to walk through the door; it is about sustaining the heaviest parts of the engine so they stay accurate, fast, and worthy of decisions you actually make. The core interaction remains the same: value first, always.

We do not monetize through lead sales. We do not sell your identity. We do not package you into a list. The business model is simple: we build intelligence products on top of aggregated, anonymized patterns. Not people. Patterns. If that sounds quiet compared to the revenue models that dominate our industry, good — quiet is compatible with a long arc. We are not trying to be the loudest company in the room. We are trying to be the one that still makes sense ten years from now.

We will never sell individual leads. Your email, your company, your identity will never be packaged and sold to a sales team. Not to our partners. Not to our investors. Not to anyone. The moment we sell an individual's information to someone who wants to cold-email them, we have broken the contract that makes this entire system work. We will not break it.

We will never share identifiable data with third parties. When we surface insights, they are aggregated, anonymized, and presented as patterns, never as individual records. "37% of mid-market teams are replacing their sequencing tools" is intelligence. "John at Acme Corp is switching from Outreach" is surveillance. We produce the former. We will never produce the latter.

We will never use dark patterns or monetize your data through ads. No gating basic usefulness, no pre-checked consent tricks. If a field exists, it is because it improves your output - not our ad graph. The warehouse exists for intelligence, not retargeting.

We vow to report only at the aggregate level. Every insight we publish, every benchmark we surface, every trend we identify is a statistical pattern drawn from the collective, not a spotlight aimed at the individual. Your data dissolves into the aggregate the moment it enters the warehouse. What emerges is signal, not surveillance.

We will always earn data through utility. Never through coercion. Never through extraction. That line does not flex when the business gets harder. It is the premise the whole architecture was built to serve.

The future of market intelligence is not surveillance. It is service.

StackScan exists to solve a concrete decision problem: what in your GTM stack is redundant, overpriced, or replaceable. Operators enter their tools because doing so produces a better read on overlap and spend. That's the exchange - utility for information, value for signal.

The data we collect is not scraped. It is not inferred from browsing behavior. It is not purchased from third-party brokers or assembled from leaked databases. Every data point in our warehouse was entered by a human being, into a tool they chose to use, because it helped them make a better decision. There is no purer signal than that.

What StackSwap actually is

Strip away the branding and chrome. What remains is voluntary input from people solving real problems, aggregated into patterns that respect privacy.

Today the clearest expression of that is GTM operators running StackScan. They enter tools, spend, and context because the output helps them decide what to cut or keep. Each honest pass sharpens overlap and pricing signal for the next operator. We are not claiming a comprehensive cross-industry dataset yet. We are building in public, in the category where we have depth: go-to-market stacks.

Nobody using our surfaces is filling out a survey for a gift card. They want an answer they can use this quarter. The byproduct is structured data benchmarks can learn from. Better inputs improve the next operator's baseline. Premium layers fund heavy modeling without turning identity into inventory.

This is not seats-for-seats SaaS hiding behind PLG. It is not lead-gen dressed up as product. Useful instruments earn voluntary truth; aggregates become intelligence; the loop stays honest because you see the output in the same session you share the inputs.

The design principle

Everything we ship must pass a single test: if this tool disappeared tomorrow, would people miss it?

If yes, people share real stacks and real spend because the output is useful. If no, you get bots and random fields - and garbage intelligence. The quality of our signal tracks the quality of the instrument. Utility is not charity; it is how honest signal gets made.

Why most data feels wrong

Markets swing between reckless harvesting and total refusal to share. GTM operators get stuck in the middle: asked for numbers without a fair story about where they go. Data is still just information; the terms of collection and use are what matter. We bias toward transparency you can verify. The specifics:

What we collect: The tools you use. The prices you pay. Your industry. Your company size. Your goals. Your migration intent. Whether you're evaluating replacements and which ones.

Why we collect it: Because every data point makes the intelligence layer smarter. Your stack analysis isn't just for you. Aggregated and anonymized, it contributes to a dataset that helps every future user benchmark, compare, and decide with greater confidence.

What we do with it: We aggregate it. We anonymize it. We surface patterns. Which tools are rising. Which are declining. What companies of your size and industry actually use. What the real cost benchmarks look like. We turn individual decisions into collective intelligence.

What we will never do with it: Read below.

The contract of consent

We don't sell your data
We don't spam you
You control what you share

Your work email is identity, not inventory. We use it sparingly for updates and writing worth opening - not sequences, partner handoffs, or vendor spam. You will not be sold to a sales org because you typed an address. Nobody buys your inbox access from us.

Your demographics are yours. Industry, company size, role, stack, spend, evaluations - all of it is yours to share or withhold. When you do share, we keep instruments useful before they are clever, and charge only where depth is real, so the deal stays honest if you never pay.

The line we will not cross

We will never become a company that knows who you are and sells that knowledge. Identity is not priced by the row. We model market structure, tool motion, cost pressure, replacement intent - not individuals weaponized for someone else's outbound list. The intelligence is the map, not the traveler; understanding without a surveillance tail is the point.

The case for crowd-sourced truth

We learn from what people actually use — not what they say in surveys.

One operator replacing ZoomInfo with Clay is an anecdote. A thousand unprompted moves, each captured when someone chose to fix their stack, is behavior at decision time - not a paid survey, not a vendor-commissioned brief.

We are not there yet. Let us be honest about that.

StackSwap is early. The architecture is built. The tools are live. The data warehouse is accepting submissions. But the sample sizes are still small, and we would be lying if we claimed our intelligence layer currently rivals the depth of a Zylo report or a Bessemer benchmark built from billions of dollars in observed spend. It does not. Not today.

What we have is the mechanism: each honest stack audit tightens the next operator's baseline. Directional findings are checked against published research (Zylo, Bessemer, Bain, AlixPartners, G2); precision still scales with volume.

Crowd-sourced data, freely given, is as close to consensus reality as we can hope to achieve.

That is the thesis, not a claim of current achievement. We are building toward signal that holds because volume and collection method are both honest. Not there yet; the architecture is sound, the tools are live, and every stack audit moves the needle. We intend to earn the rest one pass at a time.

Traditional research surveys the willing and publishes what justifies the invoice. We are building the alternative: behavior captured at the moment someone tries to fix their stack, at a scale that can eventually outrun panels and annual reports. "Eventually" matters - we have the mechanism; the dataset is still growing.

The future is not outreach

The industry's addiction to cold outreach is a symptom of a deeper failure: the failure to build things people voluntarily engage with. When your only growth strategy is interrupting strangers, you've implicitly admitted that your product is not compelling enough to attract them on its own.

We are building for instruments useful enough that people open them without a cold email nudge - then choose to come back. The flywheel still needs tools that work. That is the bet.

Your data is a gift. We build tools worthy of receiving it.

The flywheel: Useful tools → voluntary input → aggregated data → intelligence → premium insights → better tools → (repeat). Frictionless entry keeps the flywheel honest; paid depth keeps it solvent where computation and rigor demand it.

What this is not: A lead-generation company. A data broker. An advertising platform. A surveillance operation with a friendly UI. A "free forever" stunt that quietly monetizes who you are.

What this is: An intelligence layer built on voluntary, high-signal data - pattern, not people - and a bet that understanding, earned through utility, outlasts models built on extraction.

We believe durable intelligence comes from companies that serve first - that earn signal through usefulness, charge where depth has a real cost, and refuse to sell the humans who generated the signal. StackSwap is early, building in the open, and the promises on this page are load-bearing, not decoration. The data you give is a gift in exchange for utility you can feel the same session; we intend to honor it.

We don't have all the answers yet. We have an architecture, a line we will not cross, and the work ahead: sharper signal as volume grows, funded without auctioning identity.

Nick French

Founder, StackSwap

April 2026

Building in the open - earning trust one stack at a time.

The intelligence layer starts with your stack.

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