Sub-Category

Contact Data Provider

For teams that need accurate, up-to-date contact and company data to find and reach the right people — compare providers on coverage, verification and delivery method.

69 businesses

Frandata

Arlington, Virginia, United States

For more than 30 years, frandata has been an industry leader in the strategic analysis, forecasting, and measuring of franchise…

Unrated

Leading franchise market research firm provides data analytics, lending insights, and business intelligence on 4000+ franchise…

Unrated

Humanlinker

Paris, Île-De-France, France

Humanlinker is the first genai platform built to drive success in prospecting and selling. Our AI copilot is designed to empower…

Unrated Per user

Icypeas

Paris

Icypeas helps GTM teams enrich their prospect files with contact data (emails, profiles, phones).

Unrated

Lumi Loglake is out now, allowing enterprises to search unstructured logs directly in object storage. Learn more here. Decouple…

Unrated

Kindsight

Scottsdale, Arizona, United States

Affinaquest, the leading data management and analytics company in institutional advancement and collegiate athletics, enables…

Unrated Subscription

Origent Data Sciences

Washington, District Of Columbia, United States

Origent data sciences, inc. Is dedicated to managing and reducing drug development risks through better foresight. We are experts…

Unrated

SafeGraph is a geospatial data company that curates high-precision data on millions of places around the globe. Our datasets…

Unrated

Get unbreakable low-latency, high-throughput performance for massive AI workloads — from million-OPS feature stores to…

Unrated

SentiLink’s technology helps you detect and block synthetic identities, where the name, date of birth, and SSN don’t correspond…

Unrated

Strise

Oslo, Oslo County, Norway

With strise, the compliance lifecycle runs autonomously by default. New customers onboard in hours, not days. Risk is surfaced…

Unrated

Syntasa

Mclean, Virginia, United States

Syntasa offers data + AI expertise to empower data and marketing teams to extract meaningful insights from their data, make…

Unrated

These businesses sell access to databases of business contacts and company records: names, job titles, verified emails, direct-dial and mobile numbers, org structure, and often technographic or intent signals layered on top. You use them by searching a platform, pulling data through a browser extension while you're on LinkedIn or a company website, or pushing enrichment straight into your CRM via API or native integration. What changes for a customer is that a target account stops being a company name and becomes a named, reachable person with a title and a working email, without a rep spending an afternoon guessing address formats or scraping LinkedIn by hand.

People end up looking for this when their pipeline has a data problem rather than a demand problem. Lists bought or built two years ago are full of people who've since changed jobs. Email bounce rates are climbing and starting to hurt sender reputation. Reps are manually verifying contacts before every outbound sequence, or worse, sending to guessed addresses. Marketing has a target account list from intent data or ABM tooling but no reliable way to identify or reach the actual buyers inside those accounts. CRM records are stale enough that reporting and territory planning are unreliable.

Providers differ mainly in how they source and verify data, and how they get it into your workflow. Some rely on large-scale web crawling and public-record aggregation, giving broad coverage but variable accuracy; others verify continuously through email pings, phone confirmation or human QA, which costs more but bounces less. Coverage also varies sharply by geography, industry and seniority — a database strong on US SaaS contacts may be thin on European manufacturing. Delivery matters too: a browser plugin for one-off prospecting is a different buying decision from an API-based waterfall enrichment feeding your CRM automatically. Worth comparing directly: refresh frequency, verification method, compliance with GDPR/CCPA on how data was originally sourced and consented, and whether pricing is credit-based (cheap at low volume, expensive at scale) or seat-based.

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