1. Define the market before comparing databases
Write a small test segment that reflects the work your team will perform: target countries, company type, relevant roles, required contact channel and any exclusions. A database can look strong in a broad demo and weak in the narrow geography or vertical that matters to you.
Keep person, company and ecommerce-store needs separate. A person search needs role and employer context. An account list may need domains and industries. An ecommerce agency may care more about commerce platform, store category and installed technology than employee count.
2. Match the source type to the question
General contact databases are useful for net-new people and account discovery. Professional networks add current profile and relationship context. Domain-search tools help when you already know the company. Enrichment systems add fields to records you already possess. Store directories organize merchants by ecommerce-specific attributes.
These categories overlap, but they should not be treated as identical. Buying a strong enrichment product does not automatically create a good target-account list, and a professional profile does not automatically provide a suitable exportable contact route.
| Category | Best starting question | Typical gap |
|---|---|---|
| B2B contact database | Who matches this company and role profile? | Stored roles and contacts still need current verification |
| Professional network | Who works here and what changed recently? | Contact export and mailbox verification may be separate |
| Domain/email finder | Which professional emails are associated with this company? | You usually need the company or person first |
| Waterfall enrichment | Which provider can fill the missing field? | Requires workflow design, source rules and cost control |
| Ecommerce store directory | Which merchants match this platform and technology profile? | Named decision-maker coverage may vary by store |
3. Score a representative sample
Export or review the same small segment in every candidate tool. For each row, record whether the company fits, whether the person still holds the role, whether the contact route is usable, and whether the result can be explained from the selected criteria. Treat unknown fields as unknown rather than incorrect or zero.
A useful scorecard reports precision and coverage separately. Precision is the share of returned records you would accept. Coverage is how much of your known target market the tool can find. A narrow tool can have high precision and low coverage; a huge database can have broad coverage but require more review.
- Company fit and active-domain rate.
- Current employer and role accuracy.
- Email, phone or profile availability by channel.
- Duplicate and ambiguous identity rate.
- Time from search to reviewed list.
- Cost per accepted record after verification.
4. Calculate workflow cost, not headline price
A low per-credit price can be expensive when many rows are irrelevant, duplicated or unusable. A higher-cost tool can still be efficient when it removes manual research or combines several products. Include seats, minimum contracts, enrichment credits, verification, implementation and staff review time.
Also test how the tool handles saved searches, lists, contact reveals, exports and returning to an already reviewed record. The interface matters because repeated small delays become a large cost across hundreds of decisions.
5. Treat freshness and governance as ongoing work
No contact database stays perfectly current. People change employers, domains change, stores close and technologies are replaced. Ask what a date refers to, how corrections are handled and whether you can keep suppression records separate from new discovery.
Before outreach, confirm the company, role and contact route that matter to the message. Keep the source and reason for inclusion, remove duplicates and honor opt-outs across every export destination. A database supplies research inputs; your team remains responsible for how those records are used.
Frequently asked questions
Which B2B lead database has the most accurate data?
Accuracy varies by country, industry, role and field. Test a representative sample in your own market and measure current role, company fit and usable contact coverage separately. Vendor-wide database claims cannot replace that evaluation.
Is a larger lead database always better?
No. A larger database may improve coverage, but it can also increase review work. The useful metric is the number of qualified, current records your team can accept at a reasonable total cost.
Can Feediqo find ecommerce leads as well as B2B contacts?
Yes. Feediqo has separate discovery workflows for B2B people and companies, Shopify stores, and WooCommerce stores. Available fields differ by record type and source, so users should choose criteria supported by the target dataset.