RocketReach alternative: U.S. emails and mobiles as one free file, not lookups by the month

A lookup that finds no verified email or phone is refunded, so these are prices per contact found. Billed yearly, lookups in its app are unlimited and exports are capped, and an export is what its API spends: “1 Export = 1 API Credit”. A year of Ultimate, $1,699, exports 20,000 people at most. The free file holds 5,182,067 people with a mobile or an email.

On RocketReach's pricing page, a customer finds “a list of product managers who live in Seattle, work in tech” within a few clicks. The same list from the file: unzip it into us_10m/, pip install duckdb, then

import duckdb

duckdb.sql("create view people as select * from 'us_10m/us_smb_mid_market_persons.parquet'")

# A website as its domain: lowercase, without http(s)://, www. or a path, so "https://www.Acme.com/about" is acme.com
duckdb.sql(r"create macro domain(url) as regexp_extract(lower(trim(url)), '^(?:https?://)?(?:www[.])?([^/:?#]+)', 1)")
duckdb.sql("create view companies as select *, domain(URL) as DOMAIN from 'us_10m/us_smb_mid_market_companies.parquet'")

# Product managers in the Seattle area at tech companies, with a mobile phone or an email, to a CSV
duckdb.sql(r"""
  copy (
    select p.FULL_NAME, p.CURRENT_JOB_TITLE, c.NAME as COMPANY, c.LINKEDIN_INDUSTRY, c.EMPLOYEE_COUNT_RANGE, p.CITY,
           p.MOBILE_PHONE, p.EMAIL, p.LINKEDIN_URL
    from people p
    join companies c on c.LINKEDIN_ID = p.CURRENT_JOB_COMPANY_LINKEDIN_ID
    where regexp_matches(p.CURRENT_JOB_TITLE, '\bproduct (manager|management)\b', 'i')
      and c.LINKEDIN_INDUSTRY in ('Software Development', 'Technology; Information and Internet', 'IT Services and IT Consulting',
                                  'Information Technology and Services', 'Computer and Network Security')
      and p.STATE_CODE = 'WA' and p.CITY in ('Seattle', 'Bellevue', 'Redmond', 'Kirkland')
      and (p.MOBILE_PHONE is not null or p.EMAIL is not null)
  ) to 'seattle_product_managers.csv'
""")

The titles and industries are as written on LinkedIn: change the pattern, the cities or the industries for another list, or add c.EMPLOYEE_COUNT_RANGE to the where. The customer also wanted Notre Dame alumni: the file has no schools, and that part stays RocketReach's.

A list of target accounts is a list of websites. With the same setup, one join gives the people at the top of each, with their mobile or email:

# accounts.csv: your target accounts, one domain or website a line under a "domain" header.
# Who runs each one (chiefs, founders, owners, presidents, VPs, heads, directors), with a mobile phone or an email
duckdb.sql(r"""
  copy (
    select a.domain, c.NAME as COMPANY, c.EMPLOYEE_COUNT_RANGE, p.FULL_NAME, p.CURRENT_JOB_TITLE, p.MOBILE_PHONE, p.EMAIL, p.LINKEDIN_URL
    from read_csv('accounts.csv', header = true) a
    join companies c on c.DOMAIN = domain(a.domain)
    join people p on p.CURRENT_JOB_COMPANY_LINKEDIN_ID = c.LINKEDIN_ID
    where regexp_matches(p.CURRENT_JOB_TITLE, '\b(chief|ceo|cfo|coo|cto|cmo|cro|founder|owner|president|vp|vice president|head of|director)\b', 'i')
      and (p.MOBILE_PHONE is not null or p.EMAIL is not null)
  ) to 'accounts_people.csv'
""")

We ran it on a laptop on 550 websites: 500 company domains of the October 2026 file drawn at random, each written one of the ways people paste them (https, http, www., a trailing slash, a path such as /about, in capitals), and 50 made-up ones. It took 0.5 s.

Of the 500 found, 329 have someone of theirs in the file, 171 someone at the top, and 142 someone at the top with a mobile or an email. An account the file doesn't hold isn't in the CSV: a company outside the U.S., of fewer than 11 or more than 500 employees, or not in the October release. That's where RocketReach's lookup comes in. One person you have a name and a company for, as it takes them:

# One person by name and company, as a RocketReach lookup takes them
duckdb.sql("""
  select p.FULL_NAME, p.CURRENT_JOB_TITLE, c.NAME as COMPANY, p.EMAIL, p.MOBILE_PHONE, p.LINKEDIN_URL
  from people p
  join companies c on c.LINKEDIN_ID = p.CURRENT_JOB_COMPANY_LINKEDIN_ID
  where p.FULL_NAME ilike 'jane doe' and c.DOMAIN = domain('acme.com')
""").show()

• Personal emails: the file's are work emails, none at Gmail, Yahoo, Hotmail, Outlook, AOL or iCloud.
• The world: 700 million professionals, where the free file is 9,521,154 people at U.S. companies of 11 to 500 employees.
• Verification at the lookup: RocketReach verifies on demand and grades each email (A, A-, B, F). The file is the October 2026 snapshot; a profile as it is today is the LinkedIn profile API, at $0.00125 a profile found.
• The tool: a search app, a Chrome extension, sequences, Autopilot, Salesforce and HubSpot sync, intent and healthcare data.

• A list of LinkedIn URLs matched to their mobiles and emails in one query: ContactOut alternative. The same file next to other tools' contacts: Seamless.AI alternative, Lusha alternative, ZoomInfo alternative.
• What each tool's free plan gives, RocketReach's included: free B2B database. Their APIs' prices per 1,000 people: B2B data API pricing compared.

The free file is on your dashboard once you sign up with your work email, with the $5 credit and your API key.