Use case — corporate development

Whitespace mapping that starts from the whole web, not a database

Your next platform or capability acquisition sits in an adjacency your team has never formally enumerated. We screen 100M+ classified domains against your written thesis and hand back the complete, evidenced map.

100M+classified domains
700+industry categories
1 in 10"perfect" candidates already group-owned
300+ enterprise organisations run on our data
Incl. one of Europe's largest telecom operators
Adtech & cybersecurity platforms
A leading airline metasearch
On this page

Four questions this page answers

1

What whitespace is

A working definition your investment committee can hold you to.

2

How we map it

Two-pass screening of the full web against your written thesis.

3

What you receive

Complete universes with quoted evidence for every inclusion and exclusion.

4

What it costs

Published pricing, from a €4,900 proof project to annual monitoring.

The problem

Corp dev sees the deals that arrive. Whitespace is everything that doesn't.

Banked processes, inbound approaches, and the companies your executives already know cover a thin slice of any adjacency. The rest — usually the majority of it — never surfaces on its own, and never shows up in a database profile either.

Whitespace, as we use the term

The set of operating companies in an adjacency to your core business that your team has not yet enumerated — not a market-size estimate, but a named, evidenced list you can act on.

Leading company databases index the companies they have already found — the funded, the listed, the frequently covered. An adjacency map built from one inherits those blind spots and presents them with confident formatting.

We start from the opposite end: the entire active web, 100M+ classified domains covering 99.99%+ of active internet usage, read against your exact thesis. The map is complete before it is ranked.

The invisible middle

Most private industrial and services companies have never raised capital, never issued a press release, and never met a coverage threshold. They exist only as websites.

The vocabulary gap

A fifth or more of confirmed fits never use the category's obvious keywords on their homepage. They describe outcomes, not taxonomy terms.

The staleness problem

Adjacency maps built as one-off projects decay quietly. Companies get acquired, pivot, or close — and the deck nobody re-checks keeps circulating.

The starting universe

Coverage is a property of where you start

One industrial category alone resolves to 367,478 domains globally once you begin from the full web. No profile-based database holds that; no keyword search returns it.

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Classified domains
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Business & finance sites
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Industry categories
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Domains in one mapped category
The method

From the full web to a defensible adjacency map

Three stages, each auditable. Your thesis stays in plain language throughout — no taxonomy translation, no black box.

1
Universe

Fix the boundary before anyone ranks anything

We resolve your adjacency to its full global footprint across our 700+ category classification. That number is usually uncomfortable — and it should be, because it is the honest denominator.

Every operating company

Job shops, service firms, integrators — including thousands with no press, no funding history, no directory profile anywhere.

Geography & scope cuts

A 25,000-domain US-focused triage of one category resolved to roughly 17,300 live operating companies — the rest were parked, dormant, or duplicates.

2
Screening

Two passes: broad triage, then deep extraction

The first pass reads every candidate site and answers one question — could this plausibly fit the thesis? The second pass reads the survivors thoroughly and extracts structured fields.

Pass one — triage

Broad and deliberately forgiving, so companies that describe themselves in unexpected language survive long enough to be read properly.

Pass two — extraction

Fifteen signals per company: ownership language, certifications, service mix, footprint, recurring-offering indicators — each tied to quoted site text.

Insufficient evidence, flagged as such

Where a site is too thin to support extraction, the company is retained in the universe but flagged — never scored on guesswork. The specimen format reserves two of its twenty rows for exactly these cases.

3
Evidence

Scores you can challenge, line by line

Every company carries three scores — Mandate Fit weighted 70%, Outreach Suitability 20%, Transition Context 10% — and group ownership zeroes a candidate out entirely.

Verbatim snippets

Each inclusion and each exclusion quotes the site text that justified it, with the source page. Disagree with a call? The evidence is one click away.

Exclusions shown, not hidden

Roughly one in ten keyword-perfect candidates turns out to be group-owned already. We document those exits instead of quietly dropping them.

A worked miniature

What one adjacency looked like, three companies deep

From a real mapped category — industrial automation and controls integration, 534 eligible independent US companies — three anonymized rows that show why evidence discipline matters more than list length. Every claim below quotes the company's own site.

Target A-02 — top fit

Controls integrator, five Indiana locations, recurring service offerings, UL508 compliance. Scored 92.7 with every extraction field populated.

"the founder established the company in 1981" — About page

12 of 12 evidence snippets verified against site text.

Target A-03 — keyword-missed

Robotic palletizing systems, Washington state, recurring service offerings across various industries. Its homepage never says "automation integrator" — a keyword screen would never have surfaced it.

"co-owned by two fourth-generation families" — About page

Surfaced by thesis reading, not by matching category vocabulary.

Excluded — group-owned

Textbook category language, strong certifications — and one sentence that removed it from the map with the score zeroed.

"a wholly owned subsidiary" — footer, every page

Logged as a documented exclusion, with the quote, not silently dropped.

Why this format

Built to survive the questions your board actually asks

A whitespace exercise fails in the room, not in the spreadsheet. The deliverable is designed backwards from the four questions that kill adjacency proposals.

The board asks

"Is this the whole market, or the companies you happened to find?"
"Why is this target on the list — and who decided?"
"How many of these are already owned by a competitor or sponsor?"
"Will this map still be true in a year?"
"What did we pay for, if half of these never respond to outreach?"

The map answers

A defined denominator: the full category count, then every cut we made to reach the shortlist.
Quoted site evidence per company — the reasoning is on the page, not in an analyst's head.
Group-ownership screening with documented exclusions, not silent deletions.
Optional monitoring: the same thesis re-run on schedule, deltas reported.
An Outreach Suitability score per company, so effort goes where a conversation is plausible.
Where it points

Four kinds of whitespace corp dev teams map with this

The mechanics are identical; only the thesis changes. These are the four we are asked for most.

Capability gaps

Every independent company holding a certification or service capability your roadmap needs but your footprint lacks.

Vertical adjacencies

The full population one step up or down your value chain — sized with real counts, not analyst estimates.

Geographic extension

Your existing thesis re-run against a region you do not yet operate in, before committing corp dev travel to it.

Aftermarket & service entry

Service and aftermarket operators around your installed base — often invisible to databases, always visible to the web.

Into your process

A map is only useful once it is inside your pipeline

Deliverables arrive as structured files your CRM imports directly — one row per company, signals as columns, evidence quotes attached.

  • CRM-ready CSV: dedupe keys, category tags, and all fifteen signal fields per company
  • IC-memo appendix: methodology note plus the evidence trail behind the shortlist
  • Custom ICP re-runs included — tighten the thesis, we re-screen the universe
  • Named-analyst handover call to walk through the exclusion log

One map, three internal uses

Pipeline seeding: the shortlist lands in your CRM with owners assigned inside a week, each row carrying its evidence quote for the first call.
IC support: the denominator and exclusion log answer completeness questions before they are asked.
Strategy reviews: per-subvertical counts — 702 precision machining, 534 automation integration in one mapped category — size adjacencies with real numbers.

The uncomfortable arithmetic: a fifth or more of confirmed fits in our specimen runs never use the category's obvious keywords on their homepage. A keyword-built whitespace map starts a fifth short — before anyone evaluates a single company.

Working with us

Four steps from thesis to living map

Published pricing, no discovery-call theatre. Each step stands alone; none obligates the next, and the specimen report is free to request before any of them.

Thesis intake

Your adjacency thesis in plain language — one page is enough. We agree the boundary, the geography, and the cuts before anything runs.

Proof project

One subvertical mapped end-to-end so you can audit the evidence discipline on real output before committing further.

from €4,900

Full universe

The complete adjacency: universe, deep shortlist, exclusion log, CRM-ready files.

from €9,900

Annual monitoring

The thesis re-run on schedule; new entrants, ownership changes and exits reported as deltas your team reviews in minutes.

from €18,000/thesis
What this is not

Honest limits, stated up front

A corp dev team that discovers a vendor's limits mid-engagement stops trusting the parts that work. Ours are these.

We do not detect intent to transact

No website signal reveals whether an owner would entertain an approach. Vendors who claim otherwise are guessing; we decline to, and our standards say so in writing.

We do not estimate financials

Revenue, EBITDA and valuation are not visible on company websites, and vendors who derive them from page text are guessing. The map tells you who exists and what they evidence — your diligence prices them.

Evidence is website-visible by design

A company with a two-page site yields thin extraction, and we say so per company via an insufficient-evidence flag rather than padding the record.

Nascent categories map imperfectly

Where an adjacency is too new to have a stable web vocabulary, triage recall drops and the honest answer is a narrower claim. We flag this at intake, before you spend anything, and scope the proof project accordingly.

Signals that matter here

Four of the fifteen signals, read through a corp dev lens

Every company in the map carries all fifteen. These four do the most work in adjacency decisions.

Strategic fit to thesis

The principal score, weighted 70% of the composite. Your thesis text — not a category code — is what each site is read against, so "fluid-handling services with aftermarket exposure, no OEM captives" screens exactly as written. When strategy revises the thesis, the universe re-screens against the new wording and the old and new runs stay comparable.

Acquisition-program / roll-up readiness

Often a disqualifier, and the one keyword lists miss most expensively. "A wholly owned subsidiary of" or an acquisitions page of their own means the company is consolidated already — group ownership zeroes the composite score, the exclusion is logged with its quote, and roughly one in ten keyword-perfect candidates exits the map this way.

Recurring-offering indicators

Service contracts, maintenance agreements, scheduled programs, consumables language — visible recurring offerings separate a platform-quality operation from a project shop wearing the same category label. We capture the exact claim text ("multi-year service agreements", "chemical service programs", "rental fleets"), never an inferred revenue split.

Partner & channel ecosystem position

Named OEM authorizations, distributorships and association memberships show where a company sits in your industry's plumbing — and whether buying it strengthens a channel you already have or creates conflict. Certifications (UL 508A, ASME, ISO/IEC 17025, NADCAP) are captured verbatim with source pages so your operators can verify each claim in minutes.

Questions we hear from corp dev teams

Frequently asked, plainly answered

How is this different from the target list our bank produced?
A banked list is curated from relationships and databases — valuable, but its denominator is unknown, and it tends to concentrate on companies already visible to intermediaries. We give you the denominator: the full category footprint, every cut we applied, and evidence per company. The two are complements rather than substitutes; ours tells you what the curated list left out, and why it was left out. In practice, corp dev teams run both and reconcile them in one afternoon.
Our adjacency spans several of your categories. Does that break the model?
No — the thesis, not the category, is the screen. Categories bound the starting universe; your plain-language thesis decides membership. A thesis touching four categories simply starts from a wider universe, and the two-pass architecture keeps that affordable because triage is inexpensive relative to deep extraction. Cross-category adjacencies are common in whitespace work — capability gaps rarely respect taxonomy boundaries, which is precisely why we never ask you to translate your thesis into ours.
Can we change the thesis after seeing the first map?
Yes, and you should expect to. Custom ICP re-runs are included in every engagement: tighten geography, add a certification requirement, exclude a customer type, or raise the bar on recurring offerings, and we re-screen the retained universe against the revised wording. The first map usually teaches a team what its thesis actually meant; most clients converge on a stable version by the second iteration, and the exclusion log shows exactly what each revision cost in coverage.
How do you treat companies that are already owned?
Group ownership zeroes the composite score and moves the company to the documented-exclusion log with its evidence quote — "a wholly owned subsidiary", "part of the group since 2019", an investor page naming the sponsor. Roughly one in ten keyword-perfect candidates exits this way in our specimen runs. Some clients still want these rows because they map competitor consolidation vertical by vertical, so the log ships with the deliverable rather than disappearing into it.
What does the specimen report contain?
A real vertical mapped in full miniature: 8 top fits, 5 keyword-missed fits, 5 documented exclusions and 2 insufficient-evidence cases, each with quoted site text, source pages and all three scores. It is anonymized for the public site, but the format, fields and evidence discipline are exactly what a paid engagement returns. Request it by email and judge the output before you judge the pitch.
Who owns the deliverable?
You do. The files are yours to load, edit and circulate internally without seat licences or per-user fees, and they remain usable after the engagement ends. Monitoring engagements add scheduled re-runs and delta reports on top of the same files rather than locking them behind a portal — the point of annual monitoring is that the map stays true, not that you stay subscribed to read it.
Adjacent reading

Related use cases

Our standards: no seller-intent flags, no financial estimates, no owner profiling — succession context only from what companies state about themselves. Read the full standards →

Map the adjacency before the auction does

Send us the thesis your strategy deck already contains. We will return the denominator, the shortlist, and the evidence — and you can hold every row of it to account in front of your board.