What a free data count actually tells you
A data count is a pre-purchase query. You give the supplier your targeting brief, they run it against their database, and they send back numbers. No money changes hands. Done properly, a count gives you four distinct signals before you decide whether to proceed.
Universe size
The headline figure tells you how many records in the supplier's database match your criteria. If you are looking for Finance Directors in UK manufacturing businesses with 50 to 499 employees, you might get a count of 4,200 or 18,000 depending entirely on which supplier you ask. That variance is information. A very high count from one supplier deserves scrutiny. A very low count from another might mean their file under-indexes that sector, or that their job-function taxonomy is granular enough to have excluded Operations-side finance contacts you actually want.
Universe size also tells you how much headroom you have for re-prospecting. A file of 4,200 records used for a quarterly mailer gives you roughly four touches before you have exhausted it and need to re-buy or refresh.
Channel availability
Raw record count is meaningless without channel breakdowns. A B2B file might have 10,000 records matching your sector and seniority brief, but only 6,400 with a verified direct email, 3,100 with a direct-dial telephone number, and 9,800 with a confirmed postal address. Those three figures are what you are actually buying. Always ask for the count to be broken down by channel.
For B2C consumer data the same principle applies. A count of 250,000 consumers matching your age, income, and lifestyle profile might have 180,000 with a contactable email address, 140,000 with a telephone number, and 248,000 with a postal address. If your campaign is email-led, you are working with 180,000 records, not 250,000. Price accordingly.
Freshness distribution
B2B contact data decays at roughly 25 to 30% per year. People change jobs, companies restructure, telephone numbers are reassigned. A count that shows 12,000 matching records is much less valuable if 5,000 of those were last verified three years ago. Ask the supplier to break the count by last-verification date in quarterly or annual bands. Any responsible supplier running a live-verified database can provide this.
If a supplier cannot give you a freshness breakdown, treat the count with caution. It likely means they are not refreshing records on a rolling basis, which means you are buying a static snapshot of an ever-degrading file.
Per-record pricing check
Divide the quoted total licence fee by the count volume to get a per-record cost. If a supplier quotes £800 for 4,000 email-contactable records, the per-record cost is 20p. Run the same calculation for every supplier quoting on the same specification and you have a real comparison. A large gap between suppliers usually signals either a genuine quality difference or a universe that has been artificially inflated with unverified contacts to make the per-record price look low.
In our experience, buyers who skip the per-record calculation and buy on total price alone end up paying for volume they cannot use, because the records without working contact details are deadweight. Count by channel, then price by channel.
What to include in your count request
A vague brief produces a vague count. The more precisely you specify your criteria, the more useful the returned figure will be. Below is a count-request checklist covering both B2B and B2C scenarios.
| Field | B2B example | B2C example | Why it matters |
|---|---|---|---|
| Geography | East Midlands and Yorkshire regions | Postcodes LE, NG, DE | Defines the physical universe; postcode-level is more precise than regional |
| Sector / interest | UK SIC 2007 codes 4941–4942 (freight transport), 5210 (warehousing) | Homeowner, interest in home improvement | SIC codes are unambiguous; plain-English descriptions risk supplier interpretation |
| Company size | 10–249 employees | N/A | Filters out micro-businesses or enterprise accounts outside your sweet spot |
| Job function / seniority | Operations Director, Supply Chain Manager, Logistics Director | N/A | Prevents dilution with junior contacts who lack purchasing authority |
| Age range | N/A | 35–65 | Aligns with product suitability and media response benchmarks |
| Income / financial profile | N/A | Household income £40k+, homeowner | Avoids high-response, low-conversion records where spend capacity is low |
| Required channels | Verified direct email AND direct-dial telephone | Email and postal address | Forces the supplier to count only records usable for your campaign type |
| Suppression files | Existing customer list (500 records), known TPS-registered numbers | MPS wash required, existing customer suppression | Net count after suppression is the number you are actually paying for |
| Freshness requirement | Last verified within 12 months | Last verified within 18 months | Sets a quality floor so the count excludes ageing records you would reject anyway |
Send this specification in writing, ideally as a structured brief rather than a conversational email. A written brief makes it straightforward to compare counts across multiple suppliers on the same terms, and it forms the basis of the data licence agreement if you proceed. If you are regularly approaching suppliers for counts, a standardised brief template makes the whole process faster.
How to read the count response
A count response is not just a number. Know what to look for when it lands.
Does the breakdown match your brief?
Check that the supplier has applied every filter you specified, not just the headline ones. A common issue is a supplier returning a count on sector and geography but ignoring the seniority filter, producing an inflated figure. Ask them to confirm in writing which criteria were applied to generate the count.
Are the channel figures realistic?
For a well-maintained B2B database, you would typically expect 60 to 75% of records to carry a verified direct email, 40 to 55% to carry a direct-dial or mobile number, and 90%+ to have a valid postal address. If a supplier is claiming 95% email coverage on a B2B file without qualification, probe that figure hard. It usually means they are including generic role-based addresses (info@, sales@) alongside genuine personal contact emails, which are very different things for cold outreach purposes.
For B2C consumer data compiled under genuine opt-in consent, email coverage around 70 to 80% of records is normal for actively maintained files.
What is the suppressed net count?
If you provided a suppression file of existing customers or opted-out contacts, the gross count and the net count (after suppression) should both appear. You are buying the net count. Check that the supplier has applied suppression before quoting rather than after, so the price you are seeing reflects what you will actually receive.
Is the pricing per record reasonable?
B2B data in the UK typically prices between £0.10 and £0.60 per record for a standard licence, depending on seniority, channel, and data quality. C-suite direct-contact data with verified mobile numbers sits at the higher end. Broad sector data with email and postal address tends to sit lower. If a count response implies a per-record price significantly below £0.10, ask why. It may be genuine volume pricing, or it may indicate a file that has not been refreshed recently.
Red flag: no net count after suppression
If a supplier quotes a price based on a gross count and only applies your suppression file after you have paid, you are paying for records you cannot legally use. The suppressed net count should be agreed before any money changes hands.
The count-then-sample-then-purchase sequence
A free count and a free sample are distinct things and you need both. Skipping either step is a false economy.
The count tells you the universe exists at a volume that makes your campaign viable. A campaign that needs 5,000 records to hit its targets cannot function if the count comes back at 800. Better to know that before purchase than after.
The sample (typically 50 to 200 records, also provided free by reputable suppliers) tells you whether the records are what they claim to be. When you review a B2B sample, check for these things specifically:
- Email format validity. A valid-format email ([email protected]) is a better signal than a generic ([email protected]). If the majority of emails in your sample are generic addresses, push back.
- Job title plausibility. Do the titles in the sample actually match the seniority level you specified? "Manager" covers a very wide range of authority levels. Look for whether the titles align with the decision-making level your campaign requires.
- Company data consistency. Does the company name, Companies House number, SIC code, and employee headcount in the sample all hang together? Inconsistencies can indicate records assembled from multiple sources without reconciliation.
- Geographic distribution. If you asked for East Midlands records, are the postcodes actually in the East Midlands? Simple to check, and occasionally reveals that a supplier's regional mapping is imprecise.
For B2C consumer data, review the sample for field completeness, consistency of demographic signals (age, household composition, property tenure), and whether the channel fields (email, telephone, postal) are populated for the records where the count indicated they should be.
After a satisfactory sample review, you are in a position to commit. See our guide to evaluating a B2B data sample for a more detailed checklist.
What no-count suppliers signal
The unwillingness to provide a free count is, in itself, a data point. There are a handful of legitimate reasons a supplier might delay a count (system maintenance, very unusual or complex queries requiring manual work) but "we do not provide free counts" as a policy deserves scrutiny.
The most common reason suppliers avoid counts is that their file cannot support specific queries. They may be reselling stock sourced from a third-party aggregator without direct access to query it themselves, which means their data quality is entirely dependent on someone else's standards and refresh cycle. They may also be reluctant to reveal that the universe for your specific brief is smaller than their marketing implies.
Occasionally you will encounter suppliers who insist on a minimum spend before running a count, presenting it as a qualification step. This is a commercial tactic, not a technical necessity. Any supplier with a properly structured database can run a count query against it in minutes. Do not let a minimum-spend requirement substitute for pre-purchase due diligence.
When choosing between suppliers, how a provider handles the count request tells you a great deal about how they will handle the rest of the relationship. A supplier that is transparent, fast, and detailed at the count stage tends to be the same way on delivery, invoicing, and any post-purchase issues. Consult our guide to choosing a B2B data provider in the UK for a broader supplier evaluation framework.
Counts and GDPR: a brief note
Running a count does not involve transferring personal data to you. The supplier queries their own database and returns aggregate statistics, so there is no data-sharing event at that stage. You do not need a data processing agreement in place before receiving a count, and receiving a count creates no obligations on your part under UK GDPR.
The point at which data protection obligations arise is on purchase and delivery of the actual records. At that point, you will need a data licence agreement from the supplier, and for B2B data compiled under legitimate interests, you should complete a Legitimate Interests Assessment (LIA) before using the records for outreach. Samples are a slight exception: a sample file of 100 records does constitute a transfer of personal data, so the supplier should ask you to sign a sample data agreement covering the limited use and deletion of that sample. Any supplier providing a sample without any paperwork is not running a tight compliance operation.
For guidance on the lawful basis that applies to B2B prospecting, see our article on consent vs legitimate interests for B2B data.