dig-through-data-brokers

Dig through data brokers

People-search sites resell a blend of public records, marketing data, and self-reported data. They are fast, cheap lead generators and terrible evidence. The one rule that matters: a broker record is a lead, never a fact. Confirm every field you intend to use against the primary source the broker got it from — and if you cannot identify that primary source, do not use the field.

What these services actually are

Three input streams, blended and sold:

• Public records — property deeds, court filings, business registrations, voter files where public, professional licences, bankruptcy, marriage and divorce. Authoritative at origin; the broker's copy is a stale transcription.
• Marketing and commercial data — warranty cards, loyalty programmes, subscriptions, credit-header data, online forms, ad exchanges. Never verified, often inferred, frequently household-level rather than person-level.
• Self-reported and scraped — profiles, résumés, forum posts, and whatever the broker's own users typed in.

They also buy from each other, constantly. That is the most important structural fact about the category: one wrong record propagates across every brand, and cross-checking five brokers gives you five copies of one error wearing five hats. Apparent corroboration across brokers is worth close to nothing.

Why the data is wrong

• Address history is append-only in practice. Brokers add addresses and rarely retire them, so a "current address" is often several moves old.
• Household merging. Two people at one address, or two people with the same name in one metro area, get fused into one profile. Same-name relatives — father and son, cousins named for the same grandparent — merge constantly.
• Relatives are inferred, not recorded. "Relatives" and "associates" lists are usually address-co-occurrence: former roommates, landlords, and the previous occupant show up as family.
• Age is derived. Often from a birth year in a credit header or a voter file, and often off by a year or displayed as a band.
• Phone data ages fastest. Number portability and prepaid churn mean carrier and line-type attributions decay quickly — see whose-number-is-this.
• Corrections do not propagate. Getting one broker to fix a record does not fix the upstream source or the six downstream buyers.

Triage: what to reach for first

What you hold	Better than a broker	Use a broker for
Name + city	Local property and court records, voter file where public	Generating a candidate address list to check against those records
Phone number	Carrier/line-type lookup via whose-number-is-this	Reverse lookup to a candidate name, then confirm elsewhere
Email address	what-an-email-reveals	Reverse lookup to a candidate name
Name + need for relatives	Obituaries — far more accurate and they state the relationship	A first-pass household cluster to test against the obituary
Name + need for employment	Professional networks, licensing boards, corporate registries	Nothing. Broker employment data is the worst field they sell
Name + need for assets	Property registry, court judgments, who-really-owns-it	Nothing usable
Your own name (self-audit)	Nothing — brokers are the target	Enumerating your exposure before opting out

The honest summary: brokers are for turning a name into candidate selectors when you have nothing else, and for auditing your own footprint. For every claim you intend to publish or rely on, go to the primary record.

Method

1. Anchor first. Do not run a bare name. Carry the disambiguating anchor from find-anyone into every search, and treat any result that fails the anchor test as a different person.
2. Search a small number of brokers deliberately, not all of them. Pick ones with different upstream sources rather than different brands.
3. Extract selectors, not conclusions. You want candidate addresses, phones, emails, middle names, age bands, and associated names. Each is a lead to test.
4. Confirm each against a primary source. Address → property or court record. Age → voter file, licensing record, or a document with a date of birth. Employment → the employer or a register. Relatives → an obituary or civil-registration index.
5. Record which fields you confirmed and which you dropped. A broker field that survived confirmation is now cited to the primary source, not to the broker.
6. Pivot the confirmed selectors into the technique skills in the table below.

Primary-source catalogue by jurisdiction and record type, with access and legal notes: reference/source-catalogue.md.

The free-tier bait pattern

The business model is a teaser. Expect: a result page confirming a match exists with characters masked; counts ("8 phone numbers, 12 addresses") designed to imply depth; padding with public data the broker did not pay for; a progress animation implying live searching that is actually a checkout funnel; a "report" that arrives as an auto-renewing subscription with an awkward cancellation path; and results for names that do not exist, because the funnel runs regardless.

Never treat a teaser count as evidence, and assume any paid tier bills until you actively stop it. Some brokers do offer genuine investigator or business tiers with contractual use restrictions — a different product, with obligations you agree to when you sign.

FCRA and the rule that actually binds you (US)

In the US there is a legal line between two things that look identical:

• A consumer reporting agency is regulated under the Fair Credit Reporting Act. It must maintain accuracy procedures, give consumers access and dispute rights, and only furnish reports for permissible purposes.
• A data broker / people-search site is not a CRA, disclaims FCRA compliance in its terms, and has none of those obligations.

The rule: you must not use non-FCRA broker data to make decisions about employment, tenancy, credit, or insurance. That includes screening a job applicant, vetting a tenant, or checking a contractor you are about to hire. If the decision is one FCRA covers, you must go through a regulated CRA and follow its process, including notice and adverse-action requirements. The broker's own terms will say this; it is not decoration, and both the broker and the user have been the subject of enforcement over it. This is the single most common way otherwise-legitimate investigators create real liability.

Related US restrictions worth knowing: motor vehicle and driver records are restricted to enumerated purposes under the Driver's Privacy Protection Act, and some states restrict voter-file use to electoral purposes.

GDPR and the UK/EU position

The US-style people-search market barely exists in Europe, and what does exists on much thinner data. Durable reasons: aggregating and publishing personal data needs a lawful basis, and "we bought it" is not one; transparency obligations require telling the data subject you hold their data, which is fatal to a scraped aggregation business; special-category data is stricter again; and subjects have access, rectification, erasure, and objection rights that are cheap to exercise and expensive to service. Electoral registers, land registries, and court records are correspondingly more restricted than their US equivalents.

If you are in scope of GDPR, your case file is processing too. You need a lawful basis, a retention limit, and a defensible answer if the subject asks what you hold. Legitimate interests is available but requires a documented balancing test.

Self-defense: audit and remove your own exposure

The most valuable use of this skill for most people. Run yourself through the major brokers, record every profile URL, then work each opt-out. What to know:

• Opt-outs are per-broker, deliberately tedious, and usually require finding your own profile URL first. Some require email confirmation; some require identity documents, which is its own risk.
• Removals lapse. Brokers re-ingest from upstream, so a removed profile reappears after a refresh cycle. It is recurring maintenance, not a one-time job.
• Paid removal services automate the tedium across many brokers; they cannot reach brokers with no opt-out, and they do not touch the public records underneath.
• Jurisdiction helps. California created a broker registration requirement and a statutory deletion mechanism intended to let a resident request deletion across registered brokers at once; Vermont maintains a broker registry. Statutory rights are more durable than per-site forms — use them.
• The upstream source is the real fix: address confidentiality programmes for at-risk people, opting out of the UK open electoral register, and holding property through an entity are structural rather than cosmetic.

Searching yourself leaves a trace

Assume every search you run is logged, sold, and potentially visible.

• Broker searches are logged against your account, IP, and payment identity, and the search itself is data the broker can sell.
• Some professional and social platforms notify a subject that you viewed their profile, or surface you via contact-graph inference — uploading a contact list is how investigators most often get made.
• Some paid and investigator tiers notify the subject or generate a record accessible to them; credit-header products can leave an inquiry trail.
• Searching your own name from your own account creates the strongest possible association between you and your identifiers.

Use investigate-without-getting-made before touching any of this on a sensitive matter. Minimum: a separate browser profile, no account reuse, and never the case's real contact details in a signup form.

Where this goes wrong

• Confidence from repetition. Five brokers, one upstream vendor, one error.
• Merged people presented as one. The profile looks coherent because the merge is invisible; two address clusters in unconnected regions is the tell.
• Deceased subjects. Records persist and sometimes merge with a same-name living relative — a specific and damaging failure.
• Recency illusion. "Last updated" reflects when the broker refreshed its copy, not when the underlying fact was true.
• Coverage collapses outside the US. Thin to nonexistent elsewhere; absence of a result for a non-US subject means nothing at all.
• Under-representation of the mobile and the young. People who rent, move often, are recent immigrants, or have never held property or a landline are systematically thin in these datasets. Sparse results are a sampling artefact.
• Suppressed subjects. People who have opted out, or who are enrolled in an address confidentiality programme, produce a clean result that is not evidence of anything.

Confidence grading

• Confirmed — the field is corroborated by a primary record (deed, court filing, licence, registration) that names your subject and matches your anchor. Cite the primary record; the broker drops out of the chain entirely.
• Probable — corroborated by one independent non-broker source, with the anchor matching and no conflicting record.
• Unconfirmed — appears only on brokers, however many. Report as a lead with the anchor basis stated.
• Rejected — fails the anchor test, or conflicts with a primary record. Keep it in the file assigned to a different candidate.

Never grade a claim higher because more brokers agree.

Worked example

Skip trace on a judgment debtor: name plus a last-known city.

1. Two brokers return a profile with four addresses across two states, an age of 47, and six "relatives".
2. Anchor test: the debtor's known employer city matches only two of the four addresses. The other two go to a candidate B file.
3. County recorder for the matching county shows a deed in the subject's name at address 2, sold three years ago. Address 2 is confirmed as historical, not current — the broker showed it as current.
4. Dead end: a "relative" with a distinctive surname turns out, via the obituary of the actual relative, to be a prior occupant of address 2. Dropped.
5. Address 1 has no property record. The utility of the broker here was narrowing four addresses to one with a real document behind it; everything else was noise.
6. Confirmed selectors — one prior address, one middle initial from the deed — go to the court file for the current service address.

Pivots

Selector produced	Feed into
Candidate name from a reverse lookup	find-anyone
Email address	what-an-email-reveals
Phone number	whose-number-is-this
Username or screen name	hunt-a-handle
Employer or business name	x-ray-a-company, who-really-owns-it
Address tied to a company	who-really-owns-it
Removed or changed broker profile	read-deleted-pages
Relatives and associates cluster	graph-the-network
Your own exposure inventory	what-leaked-about-you

Legal and ToS notes

Scraping these sites breaches their terms and most deploy active anti-automation; the business tiers exist precisely to sell you the API instead. Bulk collection of personal data has its own exposure under computer-misuse and data-protection law depending on where you and the data sit. Do not use non-FCRA data for FCRA-covered decisions. Do not use broker data to locate a person who has taken steps to be unlocatable unless you have a documented lawful basis — a court order, a skip-trace mandate, an active investigation — and read ../../ETHICS.md before you start. This category is the raw material of doxxing and stalking, and the same lookup is legitimate or criminal depending entirely on the objective you wrote down at the start.