TL;DR
A phone number is not one product. Mobile, direct dial, office and headquarters numbers have completely different connect economics, and vendors count all four toward a single coverage claim. Ask which type you are buying before you ask how many. Best for: anyone about to sign on a coverage percentage.
ZoomInfo is a candidate for enterprise contact and phone-data sourcing. Evaluate correct-person coverage in the required territories and price the relevant data and export configuration.
Cognism sells phone-verified numbers as a separate product tier and publishes an independent study showing 45% of verified numbers reached the correct person against 18% for standard mobile numbers. The same vendor's overall database tested far weaker in a separate independent test. Best for: European and UK cold calling where connect rate beats volume.
Lusha charges 5 credits for a phone number and 1 for an email, documented in its own developer guide. That single ratio is the entire Lusha budgeting exercise. Best for: browser-first prospecting at small scale.
Datagma and LeadMagic are the two self-serve API options here that charge only on a successful match, price from $39 and $49.99 respectively, and include API access on every plan rather than gating it behind an enterprise tier. Best for: waterfall layers and EMEA or APAC coverage the large vendors miss.
Contents
- The four phone types, and why the distinction decides your connect rate
- What verification actually means
- 1. ZoomInfo
- 2. Cognism
- 3. Lusha
- 4. Datagma
- 5. LeadMagic
- Side by side summary
- Additional tools to consider
- The connect-rate benchmark nobody publishes
- FAQ: Direct-Dial and Mobile Data
The four phone types, and why the distinction decides your connect rate
Every vendor in this category sells a number of numbers. Almost none of them lead with which kind.
A mobile number reaches a person. It survives a job change, which is both its strength and its compliance problem. It is the highest-value record in the category and the hardest to source.
A direct dial reaches a desk. It bypasses a switchboard and lands on an extension assigned to an individual. It dies the moment the person leaves, and its value collapsed for any workforce that stopped sitting at desks.
An office number reaches a location. Somebody answers, and it is not your prospect.
A headquarters number reaches a switchboard. It is a fallback, and a team relying on it is not running phone outbound in any meaningful sense.
One vendor in the category, Lead411, is unusually direct about this distinction, publishing all four types separately and naming over-reliance on headquarters numbers as the most common buyer mistake. The point generalises. When a vendor claims 135 million phone numbers, the useful question is not whether the figure is true. It is how many of them are mobiles, in your geography, for your seniority band.
That last qualifier matters more than most buyers expect. ZoomInfo's own guidance states that accuracy is highest for senior decision-makers in stable roles at established companies. The inverse follows: the fast-moving mid-level operator at a two-year-old company, which is a large share of many technology ICPs, is the hardest record in the database.
What verification actually means
There are three things vendors call verification and they are not equivalent.
Format and carrier validation confirms a number is well-formed and assigned to a carrier. It is nearly free, tells you almost nothing about whether the number reaches your prospect, and is what most "verified" claims mean.
Statistical verification infers that a number is probably current from patterns across a dataset. It is a real signal and it is not evidence.
Human phone verification means somebody dialled it. Cognism sells this as a distinct product and describes a team verifying a number on request in under 48 hours. It is the only one of the three that answers the question you actually care about, and it is priced accordingly.
Evaluate phone-data claims using mutually exclusive outcomes: missing number, wrong person, correct voicemail and correct-person connection. A reported distribution whose categories exceed the full sample cannot be used as a benchmark without an explanation of its denominators.
The honest counterweight sits in a separate independent test, which found 62.5% of Cognism's overall mobile numbers, direct dials and landlines were incomplete, and noted that the 98% accuracy claim applies specifically to Diamond-verified numbers rather than the whole database. Both findings can be true simultaneously, and together they describe the actual product: a small verified subset that performs very well and a larger unverified body that performs like everyone else's.
1. ZoomInfo
Layer: Enterprise B2B intelligence, phone data as part of a platform contract
Best for: US mobile and direct dial coverage where volume is the constraint
ZoomInfo offers a broad contact-data product. Database size, field availability and real connection quality answer different questions. Test the records relevant to your team and keep phone types separate instead of combining several promotional accuracy percentages.
Job title distribution is also published, which is unusual and useful for anyone checking whether the coverage sits where their ICP does: 42 million C-suite and VP, 68 million director, 115 million manager, 290 million individual contributor and 185 million entry level.
Compare contact coverage on a sample from your actual account list. Count correct-person emails and reachable direct numbers separately, and retain unmatched records in the denominator. A global database size or an undocumented benchmark cannot establish accuracy in your territory.
The API behaviour matters for phone workflows specifically. ZoomInfo's enterprise API documentation states that the Search endpoint does not consume credits and that a credit is only charged when you Enrich a record, which means the correct pattern is to search broadly, filter locally and enrich only the records you will actually dial.
For ZoomInfo phone data, require the relevant territories and phone types in the evaluation. Judge the quote against accepted correct-person numbers, rather than every returned phone field.
Where it falls short: coverage can vary by territory, seniority and phone type. Test these separately; a premium database or a broad waterfall can still return the wrong person.
Verdict: The volume answer for US mobile and direct dial, and an expensive one. If phones are the only reason you are considering it, price the phone-specific alternatives first, because a $15,000 floor buys a lot of pay-per-match credits.
2. Cognism
Layer: GDPR-focused B2B data with human phone verification as a separate tier
Best for: UK and European cold calling where connect rate matters more than list size
Cognism's product architecture is built around one idea: that a phone-verified number is a different product from a scraped one, and should be sold as such. Verified mobile numbers are positioned as phone-verified contact numbers designed to improve connect rates, with on-demand mobile verification as a premium feature letting users submit high-priority prospects for advanced verification through the company's verification engine, described as completing in under 48 hours.
The tier names changed and most third-party writing has not caught up. Grow is the former Platinum tier and Elevate is the former Diamond tier, and Elevate is where verified mobiles, intent data and AI features sit. Bombora intent is included at up to 12 topics from a library of 11,000 or more. Standard and Pro packages include 5 seats, 1 credit is consumed per contact, the API requires a prospecting seat, and do-not-call screening is available in several European markets. That last capability is not a footnote for anyone calling into the EU or UK.
Customer-reported outcomes on the verified tier are strong and they are vendor-published. One enterprise account reports 2.4 times more mobile numbers found, connect rates moving from 6% to 30% on a pilot and five times fewer invalid numbers. Treat those as a case study rather than a benchmark.
Where it falls short: The headline accuracy claim applies to the verified subset and not the database, and an independent test found 62.5% of overall mobile numbers, direct dials and landlines incomplete. Third-party review aggregates put Cognism at 3.6 out of 5 while noting email accuracy above 90% and mobile connect rates two to three times competitors on the verified tier, with the weakness concentrated in US mid-market and APAC coverage. The platform-fee-plus-seats structure also means the entry price is not the entry price: a small team pays the platform fee regardless.
Verdict: The best answer in this list if you are dialling UK and Western Europe and you can articulate why connect rate beats list size. Buy Elevate or do not buy at all, because the verified tier is the product.
3. Lusha
Layer: Browser extension and API contact reveal, credit-metered per data point
Best for: Small teams working from professional-network profiles one record at a time
Lusha is the fastest path from a profile to a phone call and the easiest budget in the category to get wrong. The reason is a single documented ratio: in Lusha's own developer guide, revealing an email costs 1 credit and revealing a phone number costs 5 credits.
That means the credit allowance on a Lusha plan is a phone allowance divided by five. A plan advertising 4,800 credits per year is 4,800 emails or 960 phone numbers or some blend. Every published per-credit calculation for Lusha that does not account for this is describing the email price.
Two billing mechanics catch people out. Annual plans deliver all credits upfront but unused credits reset at year end with no rollover. Monthly plans cost 25% to 35% more but allow rollover up to twice the monthly cap. Credits are also consumed across four documented value categories rather than one: essential prospecting, workflow automations, sales intelligence and client engagement.
The API is not available on every tier. Multiple third-party comparisons state that Lusha API access requires the enterprise-level Scale plan, and place the practical entry for API access in that structure at several thousand dollars a year. Confirm this against your own quote, because it is the difference between Lusha being a browser tool and Lusha being infrastructure.
Where it falls short: The five-credit phone charge makes Lusha expensive per phone number relative to every pay-per-match vendor in this list. API gating to the top tier removes it from consideration for most automated workflows. And third-party analysis is consistent that the headline price covers roughly half a real multichannel stack cost, because there is no dialer, no social automation and no inbox placement testing, so those arrive as separate line items.
Verdict: Genuinely good at the thing it is: a rep on a profile who needs a number now. A poor foundation for a programmatic phone pipeline, and the five-credit ratio is the reason.
4. Datagma
Layer: Self-serve phone and email enrichment API, pay per successful match
Best for: European, UK, India and APAC mobile coverage that the large vendors miss
Datagma is built around the case the enterprise vendors are weakest at: verified direct mobiles outside North America, found from a professional profile URL or from a full name plus company with no profile URL required. The vendor positions itself explicitly as an upgrade layer on an existing stack rather than a replacement, and names Clay, FullEnrich, BetterContact, Cargo, Zapier, Make and a REST API as integration paths, which is an unusually honest positioning statement for this category.
The published claims are narrow and specific, which is what you want in a waterfall layer. Verified direct mobiles rather than switchboards or landlines. WhatsApp detection included on all paid plans, so you know which numbers are reachable on that channel. Coverage named as India, UK, US, APAC and Europe. Email finder with claimed under 2% bounce, verified against professional networks and public code and social sources, with catch-all detection and 100 free emails per month.
The billing mechanics are the reason to shortlist it. You pay only per successful match and never for empty results, stated plainly on the pricing page. Catch-all emails do not count. All plans include 10 seats, API access, WhatsApp integration, Chrome extension and file upload up to 50,000 rows. Credits are per account rather than per seat, so the whole team shares one pool. Unused credits roll over for up to 12 months while subscribed. Billing is month to month with no contract, and annual billing takes 20% off without being required.
Where it falls short: The published plan names and prices are inconsistent across the vendor's own pages and third-party coverage, which makes budgeting a conversation rather than a calculation. Enrichment returning an address is not the same as a verified address, and third-party analysis flags that you pay per lookup whether the data is right or not, which is a different guarantee from paying only on a match. Coverage claims are first-party with no independent benchmark published. And the team ceiling is 10 seats before you need to contact sales.
Verdict: The strongest waterfall layer in this list for non-US mobiles, and the pay-on-match model plus 12-month rollover makes it low-risk to test. Verify the plan and price directly, because the public figures do not agree.
5. LeadMagic
Layer: Pay-per-result enrichment API, one credit pool, no seat fees
Best for: Teams that want mobile enrichment as an API line item rather than a subscription
LeadMagic earns its place here on structure rather than on a phone-specific claim. It is a single credit pool, credits from $0.007, charges only on valid results, and the full API is included on every plan. For a phone workflow that sits inside a larger pipeline rather than in front of a rep, that is the right shape.
The developer surface is more complete than the price suggests: an OpenAPI 3.1 spec with smoke tests, a hosted MCP server with OAuth, official plugins for Claude Code and Cursor, credit-safe hooks, agent skills, a credit-balance endpoint and an analytics API returning rate limits, daily and monthly consumption history, per-product success rates and latency percentiles. Auto top-up fires at a threshold you set. Credits and billing are per workspace.
For data procurement, compare the actual lookup input, accepted output and usage charge. Retain unmatched and wrong-person records in the result set so that apparent coverage does not hide unusable data.
Pricing: Basic $49.99 per month or $490 per year, 2,000 credits, $0.025 per credit. Credits from $0.007 at volume. Full API on every plan. Search unmetered on Professional and Ultimate. Manual and automatic top-ups.
Pricing basis: ZoomInfo. Scope seats, export allowances, API access, enrichment and intent separately. A platform quote does not establish the cost of an API-led workflow.
Verdict: The best-structured API in this list for embedding phone enrichment in a pipeline, with the weakest published evidence on phone quality specifically. That combination makes a match-rate and wrong-number test on your own list mandatory rather than advisable.
Side by side summary
| Tool | Layer | Best for | Entry price |
|---|---|---|---|
| ZoomInfo | Enterprise platform, phone in contract | US mobile and direct dial volume | Quote only, three-seat minimum |
| Cognism | GDPR data with human phone verification | UK and European connect rate | Quote only, platform fee plus seats |
| Lusha | Browser and API reveal, credit-metered | Profile-by-profile prospecting | $37.45 per seat per month annual |
| Datagma | Pay-per-match phone and email API | EMEA, India and APAC mobiles | From $39 to $49 per month |
| LeadMagic | Pay-per-result API, one credit pool | Phone enrichment inside a pipeline | $49.99 per month, Basic |
Additional tools to consider
Phone data is the category where waterfalling is most defensible, because no single vendor covers every geography and seniority band. These four are worth a trial as layers rather than replacements.
FullEnrich aggregates 20 or more providers behind one waterfall call with verified phones and emails, GDPR and CCPA alignment and 50 free leads, which makes it a way to buy the waterfall rather than build it.
Kaspr publishes a free tier with unlimited B2B email credits, 5 phone credits, 5 direct email credits and 10 export credits, plus a professional-network extension, and gates API access to its top tier as Lusha does.
One field caution on the flat-rate cohort that appears in adjacent categories: operators holding several of the low-cost unlimited providers describe phone results specifically as the weakest part of the offer, with one reporting roughly 20 usable numbers per 100 on a vendor whose email data they rated highly. Cheap emails and cheap phones are not the same purchase.
The connect-rate benchmark nobody publishes
Coverage is a vendor metric. Connect rate is your metric, and it is the only one that pays.
Field-reported connect rates from operators running real dialing floors cluster tighter than vendor claims suggest. One agency operator running decent data reports averaging roughly 15% connection rate and characterises anything materially below that as a data or caller problem rather than a market problem. A second operator reports 4% to 8% connect while booking 20 to 30 mid-market and enterprise accounts monthly, and is explicit that results are best when the account has already engaged through a webinar or a website visit, while noting 60% of those bookings still come from cold. A third analysis puts realistic direct dial connect rates at 20% to 40%.
Those figures are not contradictory once you separate the denominators. Connect rate on a verified mobile list, on a cold list, and on a list of accounts with prior engagement are three different numbers, and vendors quote the first while buyers experience the second.
The US market also carries a specific and widely reported problem that no data vendor solves: screening. Operators describe US prospects either not answering or answering through an automated vetting layer that asks who is calling, with one reporting that they had never seen anyone break through it, while EU contacts answer and are irritated and Middle East contacts answer and engage. That is a channel condition rather than a data quality condition, and buying better numbers does not fix it.
Run the test this way. Take 200 records in your actual target geography and seniority band. Enrich through each shortlisted vendor. Have a rep dial all of them inside one week. Then record four numbers: fill rate, wrong-number rate, correct-voicemail rate and correct-person-answered rate. Wrong-number rate is the one to optimise against, because it is the one that destroys rep trust in the list and it is the one no vendor publishes.
FAQ: Direct-Dial and Mobile Data
What is the difference between a direct dial and a mobile number?
A direct dial is intended to reach a person or extension rather than a general switchboard. A mobile number may remain with a person after a role change, but that is not guaranteed. Verify the current person and employer association for either type before relying on it.
Does phone verification actually improve connect rate?
The best available evidence says yes, substantially, on the verified subset only. Cognism publishes an independent study of 1,000 dialled contacts in which standard mobile numbers produced 18% correct person picked up and 27% wrong number, while its verified numbers produced 45% correct person and 10% wrong number. That is a vendor-published study with a stated methodology, which is stronger than most claims here. The important qualifier, documented in independent testing, is that the accuracy claim applies to the verified tier and not the whole database, where 62.5% of mobiles, direct dials and landlines tested incomplete.
Should we waterfall phone providers the way we waterfall emails?
Use phone-specific acceptance criteria. Returned numbers should be separated into correct-person, wrong-person and switchboard outcomes; a higher fill rate can conceal a less useful calling list.
Why is European mobile coverage so much weaker than US coverage?
Two reasons, one commercial and one legal. Commercially, the largest datasets were assembled from US-centric sources and the reverification spend follows the revenue. Legally, GDPR changes what may be collected, stored and processed, and vendors serving the market build differently as a result. This is why Cognism sells do-not-call screening in several European markets and leads on GDPR compliance rather than volume, and why Datagma leads specifically on European, UK, India and APAC mobile coverage that it describes as missed by other tools. If you are calling into the EU or UK, treat US-leading coverage claims as irrelevant to your decision.
How should we budget when phones cost more credits than emails?
Build the model on the phone ratio, not the credit total. Lusha's developer documentation is explicit that an email costs 1 credit and a phone number costs 5, so a 7,200-credit plan is 1,440 phone numbers if you use it only for phones. Apollo.io's schedule charges 1 credit for demographics or an email and 9 credits when a mobile number is returned, which is a nine-to-one ratio. The pay-per-match vendors invert the problem: Datagma states no match means no credit used and Coresignal publishes contact enrichment at 20 credits, so your exposure is your hit rate rather than your attempt count. Model expected phone fill rate first and multiply second.
Are mobile numbers a compliance problem for outbound calling?
They carry obligations that desk numbers do not, and the obligations are jurisdictional. Cognism sells do-not-call screening in several European markets as a product feature, which tells you the requirement is real enough to price. In the US, A2P messaging to mobile numbers carries a separate registration regime from voice. The practical guidance is that your data vendor's compliance posture is a procurement requirement rather than a nice-to-have, that GDPR liability generally attaches to you as the controller rather than to the vendor, and that you should get the vendor's screening coverage in writing by market before signing rather than after.
The source is one part of the data workflow. Our guide to b2b data enrichment tools covers the adjacent options.
Work with Forma Nôrden
We build signal based outbound systems for B2B companies selling into the enterprise and upper mid market. Phone data is the layer where vendor coverage claims and rep experience diverge most sharply, and the gap is almost always geography and seniority rather than accuracy. Explore how we work.
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