Lead Sourcing At Scale

Lead Sourcing at Scale

Compliance is upstream: sales/outbound-compliance defines what may be collected at all. Read it before sourcing, not after. A list you cannot lawfully contact is not an asset, it's a liability you spent time building.

The core claim of this skill: list quality beats list size by an enormous margin. 50 correctly targeted prospects outperform 5,000 scraped rows, because reply rate is driven by relevance and relevance is impossible at low precision. Every rule below serves precision.

Step 1 — ICP definition (do not skip; everything downstream inherits its errors)

Write the ICP as observable, filterable attributes, not aspirations. "Growing companies that value quality" is not an ICP. This is:

The trigger event is what turns a list into a pipeline. A company matching every static attribute but with nothing changing has no reason to act this quarter. Sort the list by trigger recency, always.

Negative ICP is as valuable as positive. Write who we explicitly do not sell to, and why. It prevents a future cycle from re-litigating it.

Step 2 — source selection

Ranked by quality of the resulting list. Prefer the top of this table.

On "scraping"

The word covers two very different acts. Reading public pages a company published for the public, at polite rate, honoring robots.txt, is legitimate research. Logging into a platform to extract its proprietary dataset at volume is a ToS breach that risks the customer-facing account and, in some jurisdictions, worse. This skill does the first and never the second.

Practical politeness rules for the legitimate kind: identify honestly in User-Agent, ≤1 request/sec per host, honor robots.txt and Crawl-delay, cache so you never fetch twice, back off on 429/503, and stop entirely if a site signals it doesn't want automated reads.

Step 3 — enrichment

For each company, aim for this row. Anything you can't fill from a permitted source stays empty — never guess a field, especially email.

company | legal_name | website | category | size_signal | location |
trigger_event | trigger_date | trigger_source_url |
contact_name | contact_role | contact_route | contact_source_url |
lawful_basis | date_collected | score

Two provenance columns (*_source_url) are mandatory: they make the relevance sentence writable later, and they make the lawful basis auditable. A row without provenance is grade-E and doesn't get contacted (thinking/evidence-grading).

Contact route, in preference order: published role address for the right function → published personal business address → contact form → phone → postal. Guessed/permuted addresses are never used — they hit spam traps and kill the domain.

Step 4 — verification

• Company still trading (registry status, site live, recent activity).
• Not already a customer, competitor, or on the suppression list.
• Size band actually matches (a 2-person firm posing as national is common).
• Contact still holds the role (compare page dates).
• Trigger event is recent — a hiring post from 14 months ago is not a trigger.
• Email syntax + MX check where a published address exists. Bounce >3% on a test tranche → stop and clean the whole list before sending more.

Step 5 — scoring and sequencing

Score 0–10; sort descending; work top-down. Weight roughly:

• Trigger recency & strength — 40% (weeks old and specific ≫ months old and vague)
• ICP fit — 25% (how many dimensions match exactly)
• Reachability — 20% (named human + published address ≫ generic contact form)
• Deal size potential — 15%

Then stratify into test tranches of ~50 from one segment. Never send to the whole list at once: a 500-send blast with a bad relevance sentence burns 500 prospects and teaches you one thing. Ten tranches of 50 teach you ten things and keep 450 in reserve.

Anti-patterns

Boundaries

• Public pages, official APIs, licensed data, public registries only. No login-walled extraction, no CAPTCHA/paywall bypass, no volume platform scraping — regardless of what a library makes technically easy.
• No special-category personal data, ever. No personal (non-business) contact details.
• web_fetch retrieves static HTML only — JS-rendered directories will silently return nothing useful. Note that as a gap rather than concluding "no results found"; a headless browser or a licensed API is the fix, and that's an operator-side capability request.
• I build, score, and document the list. I cannot send to it — that's sales/outbound-sequences drafting plus a human pressing send.
• Every list ships with its provenance and lawful-basis columns populated, or it doesn't ship.