Tech, ExplainedEnterprise SaaS and software
Product

B2B contact database

Hundreds of millions of business contacts, by the seat.

BEFORE ITAFTER ITB2B contact databaseZoomInfoApollo.ioSprouts.aiPARTTechnographics+PARTLead enrichment and routing+COVERSContact searchCompany profilesSeat licencesData refreshIntent dataflagsaccountsto searchsendsexportedcontactsCustomer relationshipmanagement (CRM)sendscontact listsSales engagement platformsends namesto write toAI SDRCONCEPTS IT USESSaaS pricing modelsBEFORE ITAFTER ITB2B contact databaseZoomInfoApollo.ioSprouts.aiPARTTechnographics+PARTLead enrichmentand routing+COVERSContact searchCompanyprofilesSeat licencesData refreshIntent dataflagsaccountsto searchsendsexportedcontactsCustomerrelationshipmanagement (CRM)sendscontact listsSales engagementplatformsends namesto write toAI SDRCONCEPTS IT USESSaaS pricing modelsBEFORE ITIntent data↓ flags accounts to searchB2B contact databaseZoomInfoApollo.ioSprouts.aiTechnographics+Lead enrichment and routing+Contact searchCompany profilesSeat licencesData refreshAFTER IT↓ sends exported contactsCustomer relationship management (CRM)↓ sends contact listsSales engagement platform↓ sends names to write toAI SDRCONCEPTS IT USESSaaS pricing models
The B2B contact database receives the accounts flagged by intent data, and sends the contacts a salesperson finds to the CRM, the sales engagement platform and the AI SDR.
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A B2B contact database is a large, searchable list of business people and the companies they work at, with each person's job title, work email and phone number. It is also called a sales intelligence database or a prospecting database. Sales teams use it to find out whom to contact at the companies they want to sell to.

The largest databases hold hundreds of millions of profiles. A profile of a person records their name, title, department, company and contact details. A profile of a company records its industry, its location, how many people it employs and its approximate revenue. Machines collect the data, and people check it. The machines read company websites, press releases, job postings and public business registers. Phone teams and researchers then confirm the details. Some databases also collect data from their own users. For example, when a user's email program receives a reply with a new signature, the database may update that contact's title. This is called a contributory network.

People change jobs often, so the data goes out of date quickly. Keeping it current is the main engineering task. Some of this work is done by teams in Bengaluru and Chennai, where researchers check names, titles, emails and phone numbers.

The database is sold by the seat. A seat is one user's licence, so the company pays a yearly fee for each salesperson who uses it. Many plans also limit how many contacts each seat may export in a month. The page on SaaS pricing models explains seat pricing.

Take, for example, a Bengaluru company that sells appointment software to dental clinics in the United States. Its sales team works from India, but its buyers are in America. A sales executive searches the database for clinics in Texas with 5 to 20 staff, and for people with the title "office manager". The search returns 1,240 people. She exports them to the company's CRM. From there, they go to a sales engagement platform, which will send a planned series of emails to each one. The best-known databases cover the United States best, because that is where most of their customers sell.

The database is often combined with intent data, so that the clinics that are already looking for software are contacted first. An AI SDR can also take names from the database and write to them on its own.

Contact data about people is regulated. In India, the DPDP Act limits how personal data may be collected and used. Europe has a similar law, the GDPR. So what a database may hold, and how it may be used, differs from country to country.

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