A B2B company database is a list of companies with data such as industry, size, location and website that you can filter down to the ones that match your ideal customer. The main sources are LinkedIn, company registries, paid databases and the files your team already keeps. With four filters (industry, headcount, location and keywords), a useful company list takes five steps: define the ideal customer profile, apply the filters, split the search when it is too large, remove duplicates and move from the companies to the people.
What is a B2B company database
A B2B company database is defined as a set of company records, one per company, with attributes that let you filter and sort them: name, industry, number of employees, location, website and, depending on the source, a description or registry data. Its job is to turn a whole market into a list of companies it makes sense to sell to.
A company database answers "which companies do I target"; a contact list answers "who do I write to inside each one". In B2B prospecting, the first question comes first.
Which filters matter in a company database
The filters that matter in a company database are the ones that describe your ideal customer: industry, headcount, location and keywords that appear in the company's description. Every other attribute is for fine-tuning.
- Industry filter: the company's main activity. Each source uses its own classification, so "logistics" can be spread across several industries.
- Headcount filter: almost always in employee ranges, not exact numbers.
- Location filter: country, region or city. Each source decides whether it counts the headquarters or any office.
- Keyword filter: terms in the company's description or activity, useful for niches that no industry classification captures, such as "cold chain".
Some paid databases add filters such as revenue or the technology a company uses.
Where company data comes from: four types of source
The data in a B2B company database comes from four types of source: LinkedIn, company registries, paid databases and your team's own files (the CRM or a CSV). Good company lists usually combine at least two.
LinkedIn as a company database
LinkedIn works as a company database because every company with a LinkedIn Page declares its industry, size and location. In LinkedIn search, after you choose "Companies" on the results page, you can filter by Locations, Industry and Company size, according to LinkedIn Help ("Find a company page URL", checked on 6 November 2026).
On LinkedIn each company maintains its own data, and its Page leads to the people who work there. A company without a LinkedIn Page does not show up.
Company registries and Spain's BORME
Company registries are the official record that a company exists and of its legal filings. In Spain, the Official Gazette of the Commercial Registry (BORME) publishes the legal and financial data of registered companies; it is edited by the state agency BOE and published by the Central Commercial Registry, according to the BORME FAQ on boe.es.
The BORME is published on working days. Its first section lists registered acts in blocks by province, and its second section publishes notices such as mergers, dissolutions and capital increases. The boe.es archive goes back to 2 January 2001. As a company database, the BORME is good for spotting new companies or changes by province, but it cannot be filtered by industry or headcount. If what you need from a registry is who signs for the company, the guide to finding company CEOs covers that part.
Paid company databases
Paid company databases are commercial providers that bring data from several sources into one search tool, with more filters and direct export. Comparisons of named providers are in our guides to ZoomInfo alternatives and Clay alternatives. What to check in any paid company database is which source each field comes from, how often it is updated and how it charges.
Your CRM or your own CSV files
The team's CRM and CSV files are the most overlooked company database: customers, lost deals and trade fair accounts. Cross-check them against any new list before writing to anyone.
Company data sources compared
The four sources of a B2B company database differ in fields, freshness, cost and best use.
| Source type | Fields it provides | How fresh it is | Cost | Best for |
|---|---|---|---|---|
| Name, industry, size, location, website, description | Maintained by each company on its own Page | Included in LinkedIn search | Building the list by industry, size and location and moving on to the people | |
| Company registries (BORME in Spain) | Registered acts by province and notices such as mergers, dissolutions or capital increases | Published daily on working days | Consulted on boe.es | Spotting new companies or changes by province and confirming a company exists |
| Paid databases | Fields from several sources, normalised | Depends on each provider | Paid, by subscription or credits | Extra filters such as revenue or technology |
| Your CRM or CSV | Whatever your team has saved | As current as your team keeps it | Already yours | Removing customers and open accounts, and reviving lost deals |
How to find companies by industry and size, step by step
Finding companies by industry and size takes five steps: define the ideal customer profile, turn it into filters, split the search if it goes over the source's cap, remove duplicates and move from companies to contacts. The example in each step is an SDR selling warehouse management software who is looking for logistics companies with 50 to 200 employees in Amsterdam.
- Define the ideal customer profile. Industry, size, location and a reason to buy; in the example: logistics and transport, 50 to 200 employees, with their own warehouse in the Amsterdam area.
- Turn the profile into filters. Industry goes into the industry filter, size into the closest headcount range (on LinkedIn, 51 to 200 employees) and the own warehouse into a keyword such as "warehouse".
- Split the search if it goes over the cap. When a search returns more companies than the source lets you see, split it by location or by size range and run each part separately.
- Remove the duplicates. Merge the searches, drop repeats and check the result against the CRM to remove customers and other reps' accounts.
- Move from companies to contacts. Find the decision-maker at each company, such as the Head of Operations. This stage is covered in the five stages of prospecting.
Another variation starts from a signal instead of an industry, such as companies that are hiring for the team you sell to.
How to build a filtered company list with HappySales
HappySales builds a filtered company list on top of LinkedIn's company search, requested in plain language from Claude or ChatGPT (where it is added as an MCP connector) or from its web app. Its filters are the four from the profile: single keywords, 20 locations at most, as many industries from LinkedIn's 434 (with sub-industries) and LinkedIn's headcount ranges, from 1-10 to 10001+ employees.
A HappySales search tops out at 1,000 companies, because that is the limit LinkedIn's search sets; a larger market is broken into several searches by location or size. Full mode also reads each company's website, domain, headcount and description, and every search fills a company list. For a location, a company counts if it has an office there.
In Claude, the request for the example can be "find logistics and transport companies with 51 to 200 employees in Amsterdam with the keyword warehouse". If the team already has accounts in a spreadsheet, HappySales imports up to 500 companies per CSV file, marks each company as new, prospected or discarded and keeps each company's history between searches (it is not a real-time alert). Once the list is closed, HappySales finds the people at those companies by job title, function or seniority, with a limit of 100 per company and 10,000 in total per search; companies without a LinkedIn Page are left out.
HappySales does not pull companies from a web search or from company registries: the data comes from LinkedIn and from the CSV files the user imports. It has no revenue or technology filters either, and it is not a CRM: it works before the CRM.