Data Sources

TL;DR

Pick 1-2 primary data sources and 1 backup/enrichment source. Define your ICP first (industry, size, geo, tech, roles, triggers). Use GPT to convert your ICP into precise filters/Boolean strings for tools like Apollo and Sales Navigator. Build your TAM list (all possible accounts), then apply lead scoring to prioritize (we will give you a tool for this in the next section). No source is perfect -combine, enrich, and verify.

Where to get data

Company-level (firmographic / technographic)

-LinkedIn / Sales Navigator -most current company universe, org charts, growth; no emails. -Apollo -strong filters, basic technographics, solid email coverage, enrichment API. -ZoomInfo -deep coverage, direct dials/org maps; great but pricier. -Clearbit / Clearbit Reveal -enrichment + website/company matching; good for technographics. -BuiltWith / Datanyze / Wappalyzer -tech stack (e.g., "uses HubSpot/Shopify/Snowflake"). -Crunchbase / Owler -funding, acquisitions, company news signals. -Dealfront (ex-Leadfeeder), Lead Forensics, Albacross, 6sense -reverse-IP account intent.

Person-level (contacts)

-Apollo -large contact database + sequencer; good starter. -ZoomInfo -higher direct-dial accuracy; expensive. -Seamless.ai / Lusha / RocketReach / LeadIQ -fast contact discovery; quality varies -verify. -Sales Navigator -gold standard for title discovery & org mapping; export/enrichment needed.

Intent & triggers (great for timing)

-G2 / TrustRadius intent -researching category or competitors. -Bombora / Demandbase -account-level research topics surging. -Hiring feeds (LinkedIn Jobs), press/funding (Crunchbase), tech changes (BuiltWith) -strong "why now" signals.

ICP first (before you buy)

You will save budget and time if you lock this down up front:

-Industry: NAICS/SIC or practical segments (e.g., "B2B SaaS, 50-500 employees"). -Size: employees and/or revenue bands. -Geo: countries, states, time zones you support. -Tech stack: "must use" or "must not use" (HubSpot, Shopify, Snowflake, SAP, etc.). -Compliance/Needs: e.g., "healthcare with HIPAA concern," "manufacturers with service depots." -Personas: titles + synonyms ("RevOps," "Revenue Operations," "Sales Systems," "Go-To-Market Ops"). -Triggers: hiring for X, new funding, opened second location, migrating CRMs.

Shortcut: paste your ICP into GPT and ask: "Turn this ICP into Apollo filters + Sales Navigator Boolean searches. Include title synonyms and negative keywords."

Turning ICP into lists

-TAM (Total Addressable Market): the full company list that matches your ICP. Build in segments (by industry, size, or tech) so you can run targeted plays. -Contacts: for each segment, pull the right personas (primary + influencers). -Enrich & verify: add domains, tech, HQ, social; verify emails before sending.

Important: Being on your TAM list != being a good near-term target. You will prioritize with lead scoring (fit + intent). Our Lead Scoring Tool in the next section does this automatically.

Strengths & trade-offs (real talk)

No single source is perfect.

-Sales Nav = most current titles/orgs; weak on emails. -Apollo = great filters + decent emails; some gaps at the edges. -ZoomInfo = strong phones/orgs; $$$. -Seamless/Lusha/etc. = fast/cheap contacts; quality varies -verify every send. -Clearbit/BuiltWith = excellent for enrichment/tech; may miss long-tail firms.

Best practice: choose a primary (e.g., Sales Nav for discovery + Apollo for enrichment) and keep a backup source for fills.

Simple process that works

1. Define ICP (use the checklist above).
2. Ask GPT for Apollo filters and Sales Nav Boolean strings based on your ICP.
3. Build TAM lists by segment; pull initial contacts (primary persona + 1-2 stakeholders).
4. Enrich (tech, HQ, LinkedIn, website) and verify emails.
5. Tag source (e.g., source=Apollo) so you can measure quality later.
6. Score & prioritize with our upcoming Lead Scoring Tool (fit + intent + recency).
7. Run plays -> capture intent -> follow with microsites for your best prospects.

Quick examples of ICP filters

Example A (SaaS): United States • 50-500 employees • "B2B SaaS" • uses HubSpot • titles: "Revenue Operations," "Sales Operations," "Head of RevOps."

Example B (E-commerce): North America • 10-100M GMV • Shopify Plus or BigCommerce • titles: "VP Ecommerce," "Head of Growth," "Operations Director."

Example C (Manufacturing): Midwest • 200-2,000 employees • "Industrial Equipment" • has multiple plants • titles: "Plant Manager," "Maintenance/Facilities," "Ops Director."

What happens next

You will have a clean, segmented company + contact universe. Next, we will show you how to score it so your team focuses on the highest-fit, highest-intent targets first -and how to plug that into microsites to lift meetings with less noise.