Build a Business Lead Database: Fields, Cleanup and Examples

A business lead database should help a teammate answer three questions: which account is this, why is it relevant, and what is the appropriate next step? A large spreadsheet that cannot answer those questions creates research work instead of removing it.

This guide takes a small dataset from business records to a reviewable prospect list. The examples are illustrative; they are not customer records or campaign results.

Define what one row represents

A business location, a company, a person and a sales opportunity are different objects. One company can operate several locations. Several locations can share a website, phone number or central inbox. An email address on a location record does not establish who reads it.

Use a business-location row as your starting point when the source provides business listings. Add an account identifier when research confirms which locations belong together. Keep individual contact research separate. Only create an opportunity when an actual sales process begins; possessing a business record does not establish buying intent.

Choose the fields your workflow needs

The current Leadz export offers business name, categories, phone and email fields, website, address, city, state, ZIP code, rating and review count. Optional columns and your selection determine the CSV you receive. See the field-by-field CSV guide for exact headers and an illustrative sample file.

Keep these working fields in your own spreadsheet or CRM alongside the imported data:

• Source and date collected, so another teammate can retrace the record.

• Account identifier and location identifier, so branches are not silently merged.

• Fit decision and supporting evidence, such as a relevant service page.

• Contact role and evidence date, with unknown values left explicit.

• Suppression status, reason and date, checked before any outreach.

• Owner and next action, so the same business is not researched twice.

These are recommended working fields, not a claim that every one is included in a Leadz export.

Work through duplicates before importing

Imagine three illustrative records: Cedar Studio's downtown office, Cedar Studio's north office and a second copy of its downtown listing. All share cedar.example and a general inbox. Different addresses support keeping the two offices as locations. The repeated downtown record is a potential duplicate that requires confirmation.

Merging everything with the same domain would erase a location. Keeping every row as a new company would inflate the account count. Instead, normalize website domains and phone formats for comparison, compare addresses, and label ambiguous matches for review. Preserve the original values so the decision can be reversed.

The deduplication worksheet and workflow separate exact duplicates, possible branches and suppression decisions. Suppression is an independent rule: an opted-out contact must remain excluded even if its source record appears again under a slightly different business name.

Separate availability from usable contact information

A populated email field tells you an address was available in the source record. It does not prove current mailbox acceptance, recipient role, permission or interest. A phone number also needs context: it may reach reception or a central booking team.

Add a research queue for missing or ambiguous contact details. Do not replace unknowns with assumptions such as “owner” or “verified.” The availability versus verification guide explains the questions to ask before using an address.

Decide what to build and what to buy

Build manually when a small, specialized account set needs deep research. Evaluate a business-data source when category and geography can narrow a larger market and consistent fields reduce repetitive collection. Either way, budget for cleanup, role research and maintenance.

Test a sample against your actual criteria before expanding. Measure usable unique accounts after review, not just raw rows. A cheaper row can be expensive if most of the work starts after downloading it.

Give the database a maintenance owner

Assign responsibility for corrections, suppression and duplicate review. Record what changed and why; keep dated exports separate from the current working table. Before a new campaign, recheck the selected cohort and reconcile it with existing customers, open opportunities and prior objections.

Start with the category that matches your buyers, then create a modest segment you can inspect thoroughly. CSV export requires an eligible paid plan; the sample linked here is an illustrative teaching file, not a free production export.