Email addresses follow patterns. Phone numbers do not, which is why every trick that works for finding an email fails here.
You cannot guess a mobile number from a naming convention, verify it with an SMTP handshake or infer it from a domain. Phone data is either sourced and verified or it is a guess, and the difference shows up immediately in your connect rate.
Three kinds of number, and only one worth much
| Type | Connects to | Realistic value |
|---|---|---|
| Switchboard | A receptionist or an IVR | Low. Free to find, gatekept, and usually a transfer you will not survive |
| Direct dial | A desk line, no gatekeeper | Moderate, and falling. A desk line in a hybrid company rings in an empty room |
| Mobile | The person | High. The only number with a serious answer rate, and the only one worth 10 credits |
The hierarchy has shifted in the last few years. Direct dials used to be the prize; hybrid work turned them into voicemail. If you are buying phone data in 2026 and the coverage number quoted includes direct dials and switchboards, you are being sold a bigger number than you can use.
Where the numbers actually come from
1. A B2B database with phone data. The default and the fastest. Coverage is the whole question, and coverage varies enormously by role and region rather than being one flat percentage. Phone Finder reveals mobile and direct-dial numbers on the same lead record you prospect from, which matters less for the data and more for the workflow: no export, no re-matching, no CSV that ages while you clean it.
2. Your own CRM. Genuinely under-used. Old opportunities, churned accounts and past champions carry numbers you already paid for. If someone has changed job, the mobile usually still works, and a champion at a new company is the highest-converting call you can make. This is also the argument for job-change monitoring: watching people rather than searching for them tells you when the number you already own became valuable again.
3. Inbound and content. A phone field on a demo form is self-reported and verified by intent. Small volume, best quality.
4. Manual sourcing. Company filings, conference speaker lists, email signatures, personal websites. Slow, occasionally the only route into a founder-led business, and not a programme.
What no longer works: guessing extensions, buying a bulk list of unverified numbers, or scraping aggregator sites whose data was stale two years ago. All three cost rep hours and corrupt your connect-rate metric, which is worse than the wasted dials.
Why a mobile costs ten times an email
On a credit model the prices are explicit: 1 credit for a lead with a verified email, 0.5 for LinkedIn data without an email, 10 for a mobile number. That ratio is not arbitrary and it is worth understanding rather than resenting.
Sourcing a mobile is harder, verification is harder, and decay is faster. But the deciding factor is value: at a 31% connect rate, ten mobiles is roughly three conversations with a decision-maker. Ten emails is ten sends with an open rate. Priced per outcome, the mobile is cheap.
The ratio also imposes useful discipline. At 10 credits each, nobody reveals mobiles across a 5,000-lead list, which is exactly the behaviour that wastes money. The pattern that works:
- Build and filter the list. Filters and company records cost nothing, so refine until the segment is tight.
- Reveal verified emails across the whole list at 1 credit each.
- Run email and LinkedIn first. Let engagement and ICP scoring sort the list for you.
- Reveal mobiles only on accounts that engaged or that clear a deal-value threshold.
On a 3,000-lead campaign that is 3,000 credits of email data and 1,500 credits of mobiles on the top 150 accounts, rather than 30,000 credits of mobiles on a list you had not qualified.
Coverage, honestly
Nobody has complete mobile coverage and anyone claiming it is counting something else. Rough expectations on a typical B2B list:
| Segment | Mobile coverage to expect |
|---|---|
| Sales, revenue, founder and agency roles | High. These people publish their numbers |
| Mid-market operations, marketing, HR | Moderate |
| Engineering and technical ICs | Low |
| Regulated industries, public sector, enterprise legal | Low, and often deliberately unlisted |
| US and UK | Best coverage overall |
| EU (post-GDPR sourcing constraints) | Thinner, and varies sharply by country |
| India, LATAM, MENA, APAC | Often good, and frequently a WhatsApp number rather than a call number |
That last row matters more than it looks. In several regions the useful thing about a mobile is not that you can ring it: it is that you can message it on WhatsApp, where reply rates run far above email.
Before you dial anything
Phone data carries obligations email does not: do-not-call registries, TCPA in the US, GDPR-based rules in the EU and UK, and recording consent that varies by state and country. Buying the data is the easy part; the twenty minutes on what you can legally dial is the part that protects the programme.
Next: what a meeting on the phone actually costs, or why some numbers get flagged as spam before they ring.
Frequently asked questions
What is the difference between a direct dial and a mobile number?
A direct dial reaches a desk line without going through a switchboard. A mobile reaches the person wherever they are. Since hybrid work, mobiles connect far more reliably, and desk lines increasingly ring in an empty office.
What is a realistic phone match rate?
Expect 30% to 60% mobile coverage on a typical B2B list, higher in sales, revenue and founder roles, lower in regulated industries, engineering and public sector. Any vendor claiming 90%+ mobile coverage is either inferring numbers or counting switchboards.
Why does a mobile number cost more than an email?
Sourcing and verification are harder, and the data decays faster. On the Outboundry credit model a mobile is 10 credits against 1 for a verified email, which is also a useful brake: it stops teams revealing mobiles across a whole list before qualifying it.
Is it legal to call a business mobile you found in a database?
In most B2B contexts yes, subject to do-not-call registries, TCPA rules in the US and GDPR-based legitimate-interest requirements in the EU and UK. The obligations vary by country and by whether the number is personal or corporate, so it is worth reading the compliance detail before scaling.
Should I verify phone numbers before calling?
Yes. Dialing dead numbers wastes rep time and pollutes your connect-rate data, which then hides real problems in your scripts and targeting.