Lead database comparison and data upkeep

A lead database is a searchable collection of companies and people you could win as customers. You set filters, for example industry, size, region and job title, and receive a list of names and contact details.

It usually holds three kinds of information: company data (industry, size, location), person data (name, role, professional profile) and contact data (email address, phone number). Some databases add signals, such as new job openings or visits to your website.

Clarify your target audience first: create an ideal customer profile

Very different tools go by this name. It helps to sort them by their job. Many providers do more than one job. The examples come from the battlecard further down.

Sales Automation is not a database with data collection of its own. The platform bundles several of the services above, checks the results and merges them into one list. You can see which ones in the battlecard.

Three things cause most of the disappointment in practice: your target audience is not included, the data is outdated, and costs are hard to predict.

1. Availability: is your target audience included at all?

Many providers quote large worldwide totals. What matters is how many matching people exist in Germany, Austria and Switzerland. On the main pages of the providers in the battlecard that we read, only Lusha states its own figures for these countries (as of 30 Sep 2026: Germany over 10 million, Switzerland 2.5 million, Austria 1.2 million contacts). Other providers may state such figures on request or inside their app. Whether your target audience is there is best found out in a test.

2. Freshness: how old is the information?

People change jobs, companies change addresses, mailboxes are closed. A database always reflects an earlier state. We measured this ourselves in a sample in October 2026: 680 target companies in the DACH region with 501 or more employees, four providers, 1,119 people, each checked individually against the company website, legal notice and press.

The results apply to this sample and this point in time, not to individual providers in other markets. Method and detailed results are on our data quality page.

See the study and method

3. Cost: what are you actually paying for?

Some providers, such as ZoomInfo, Cognism and Seamless.AI, state prices only on request, others publish them. That is why the pricing model matters more than a single price. It decides whether you also pay when nothing comes out of it.

With Sales Automation you pay by subscription and credits. Credits for found email addresses and phone numbers are only used on a hit, and importing your own contacts is free. Further functions may be charged separately. Current packages are on the pricing page.

The result of our check is simple: in our sample no single source was complete and current. Accuracy comes from combining sources and checking them.

1. 1

   Define your target audience first

   Industry, size, region and role. The clearer the frame, the less waste.

2. 2

   Combine several sources

   Query one source after another and stop at the first reliable hit.

3. 3

   Check role and company individually

   Compare the person with the website, legal notice or professional profile.

4. 4

   Verify email without sending

   A mail server test shows whether the address exists. “Unclear” never counts as valid.

5. 5

   Check once more right before sending

   A bounce harms your sender reputation. A fresh check helps avoid it.

In Sales Automation this path works as follows: you search the lead database with filters or let the AI assemble a search. For contact details the connected services are queried one after another. Duplicates are detected on import, and email addresses can be verified on import and once more before a campaign. Addresses verified within the last six months are not checked again.

Even a good list goes stale. Plan upkeep as a fixed part of your sales work. This plan applies to every system, including your CRM.

1. 1

   Record origin and date

   Note for each contact where it came from and when it was last verified. Without a date you do not know what is old.

2. 2

   Check before every campaign

   Verify email addresses right before sending, especially for contacts older than a few months.

3. 3

   Evaluate bounces

   Block an address that bounces hard immediately for all further messages.

4. 4

   Detect job changes

   Compare contacts with their professional profile. Do not write to people who have left. Look for a new contact at that company.

5. 5

   Merge duplicates

   On every import, check whether the person already exists, by email address or profile link.

6. 6

   Keep opt-outs consistent

   Anyone who does not want to be contacted goes on a block list. Match that list with your CRM.

7. 7

   Define one leading system

   Decide where changes are maintained first so that CRM and database do not contradict each other.

Existing contacts can be checked in bulk for valid email addresses inside the platform. Make this check a routine before larger campaigns. Upkeep itself remains your task: the platform checks when you trigger or switch it on, not continuously in the background.

The table shows what providers publish about themselves: data coverage, freshness, pricing model and CRM connection. Every row links to the pages we read. All information as of 10 November 2026.

Sales Automation bundles several sources and verifies the results. The overview compares scope of features, not data quality. The seven criteria are our own selection, and the CRM checkmark only says the connection is mentioned, not how deep it goes. Our study covers data quality.

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Good contacts only help if they arrive where your sales team works. Maintaining two systems costs time and creates contradictions. Sales Automation is connected to HubSpot, Salesforce and Pipedrive.

Without a CRM connection you export your contacts as CSV or Excel. Which system you use is your decision. We do not make a recommendation.

Use these questions to test any provider, including us.

1. 1

   How many matching people are there in my country?

   Ask for figures for your region, not for the world.

2. 2

   Where does the data come from?

   Ask for source and date per record.

3. 3

   When was this record last verified?

   Not: last touched.

4. 4

   How do you verify email addresses?

   And what happens with “unclear”?

5. 5

   What do I pay if nothing is found?

   Ask about billing on failure.

6. 6

   What happens on a bounce?

   Is there a credit or a guarantee, and how much?

7. 7

   How does data get into my CRM?

   Direction, duplicates, fields.

8. 8

   Can I test a sample before buying?

   Test with companies you know yourself.

More questions: the lead sourcing guide as a PDF