Part of Lusha’s ongoing measurement of B2B data decay. Every finding in one place: How fast B2B contact data decays.
We tested Lusha’s own data across metros and company sizes.
We enriched 125 real US contacts, split across two metros and two company size bands, and checked what came back.
Work email resolved every time, in every segment. Mobile phone resolved 96 to 100 percent of the time, with no meaningful difference between San Francisco and Boston, or between small companies and large ones.
The thing that went stale was not the contact details. It was the job title and the current employer, which is the opposite of what teams usually verify.
What we tested
We pulled real contacts through Lusha’s own prospecting and enrichment tools. No simulated data, no preview flags.
Two metros: San Francisco Bay Area and Boston. Two company size bands: name brand companies with 500 or more employees, and small companies with 1 to 50 employees. For each of the four segments we searched for contacts at manager, senior or director level, ran a real enrichment call, and counted a hit only when a usable work email or mobile phone number actually came back, not when the system listed one as available.
Total sample: 125 contacts, every reveal run in real time on July 28, 2026. A second test run the same day covered 197 contacts across four industries; that report is here. Across both tests, 322 contacts, work email resolved for 322 and mobile phone for 314, a 97.5 percent hit rate.
Work email resolved in every segment
Every contact in all four segments resolved to a usable work email. Fifteen for fifteen in SF Bay name brand companies, thirteen for thirteen in Boston name brand companies, fifty for fifty in SF Bay small companies, forty seven for forty seven in Boston small companies.
Company size and location did not move this number at all.
Mobile phone held in a tight band, 96 to 100 percent
Phone is where variation should show up, and it mostly did not.
Small companies ran two to four points behind name brand companies on phone, in both cities, and Boston and San Francisco landed within two points of each other in every band. Neither company size nor geography produced a gap large enough to change how a GTM team should plan around this data.
Read the two small bands with more caution than the two large ones
The name brand segments are 15 and 13 contacts. A perfect score on 13 contacts is consistent with a true rate anywhere from about 77 percent upward, so the 100 percent in those two cells is a clean result on a thin sample rather than a firmly established number.
The SMB segments are 50 and 47, and the 96 and 97.9 percent figures there sit on much firmer ground.
We are stating this because the next section is about exactly this problem, and it would be odd to make that argument and then leave our own small cells unmarked.
What we expected to find, and did not
The early read looked different. A first pass pilot of 15 Boston small company contacts came back with a phone hit rate of 86.7 percent, a real gap against San Francisco’s early numbers. We almost stopped there.
Expanding that same segment to 47 contacts moved the number to 97.9 percent, back in line with every other segment in this test.
The 15 contact pilot was not wrong. It was small enough that two missed contacts swung the result by twelve points.
We are including this because it is a better way to show our work than quietly swapping in the corrected number. If a data claim can move that much on a small sample, the sample size is part of the claim.
What actually goes stale: title and employer, not contact info
Contact details held up. Something else did not.
Across the name brand sample, a handful of contacts showed a real gap between what the initial search returned and what the enrichment call confirmed. Not on email or phone. On job title and current company.
In every one of these cases the work email and mobile phone Lusha returned were accurate. What lagged was the snapshot of where someone currently sits and what they are currently called.
That is a different failure mode from a wrong phone number, and it points to a different fix: cross check title and current employer before treating either as settled, the way you would already check any fast moving executive’s status.
It also lines up with our separate decay measurement, which found that about 1 percent of senior contacts change roles every month. Contact details survive a job change. Titles do not. The measurement is here.
What this means for a GTM team
If the question is whether a contact record will resolve to something you can use, the answer holds steady regardless of which major US metro or what size company you are prospecting into. Work email is close to a sure thing in the ranges we tested. Mobile phone lands in the high 90s outside the smallest companies, and even there it does not drop far.
The place to spend caution is not verifying contact details. It is verifying that the person is still in the role and at the company the record shows.
Build that check into any workflow that fires personalized outreach referencing someone’s current title. A stale title in the first line of an email is a worse failure than a bounced message, because the message arrives and announces itself.
Methodology notes
Sample composition. 125 total contacts, manager through director seniority, across Sales, Marketing, Engineering, Operations, Finance, HR and General Management. Not a department specific sample.
Hit definition. A hit required an actual revealed, non empty value from a real enrichment call, not a preview flag indicating a field might be available. This distinction is the reason a hit rate measured this way will differ from an availability rate measured from a search result, and from a deliverability or bounce rate measured after a send.
Company size bands. Name brand: 500 or more employees, recognizable companies. SMB: 1 to 50 employees.
Metros. San Francisco Bay Area (San Francisco and San Jose combined) and Boston, Massachusetts.
Confidence ranges. The 95 percent ranges in the table are Wilson score intervals. They show how much room a small sample leaves, which is why the two name brand cells carry wide ranges despite perfect scores.
What this does not cover. Two metros, two company size bands. Not every US metro, not every industry, and not company sizes between 50 and 500 employees. Treat this as directional evidence that geography and company size are not major drivers of hit rate in the ranges we tested, not as a claim covering every segment of the US market.
Privacy. The examples referenced are real contacts surfaced through Lusha’s verified data layer, with identifying details withheld. No individual contact details are included or derivable from the figures presented. Current certifications are on the trust center.
FAQ
How accurate is B2B contact data in the US?
In this test, work email resolved for all 125 contacts across every segment, and mobile phone resolved between 96 and 100 percent depending on segment. Those figures cover two metros and two company size bands, using a hit definition that required an actual revealed value rather than an availability flag. Combined with the 197 contact industry test run the same day, work email resolved for 322 of 322 contacts and mobile phone for 97.5 percent. They are not a claim about every segment of the US market.
What counts as a hit?
An actual revealed, non empty value returned by a real enrichment call. A field listed as available in a search result does not count. This distinction is worth holding onto, because an availability rate and a hit rate measure different things and will produce different numbers on the same contacts.
Does company size affect hit rate?
Slightly, on phone. Small companies of 1 to 50 employees ran two to four points behind companies of 500 or more, in both cities. Work email showed no difference at all. Neither gap is large enough to change how a team should plan around the data in the ranges tested.
Does geography affect hit rate?
Not between the two metros tested. Boston and the San Francisco Bay Area landed within two points of each other in every band. We tested two metros, so this is directional evidence rather than a statement about every US market.
Why do the two name brand segments have wide confidence ranges?
Because they are small. Fifteen and thirteen contacts. A perfect score on thirteen is consistent with a true rate anywhere from about 77 percent upward, so the 100 percent in those cells is a clean result on a thin sample rather than a settled number. The two SMB segments, at 50 and 47 contacts, sit on firmer ground.
What went wrong with the first pilot?
A 15 contact pilot in Boston returned a phone hit rate of 86.7 percent, which looked like a real regional gap. Expanding the same segment to 47 contacts moved it to 97.9 percent. Two missed contacts had swung the small sample by twelve points. We published both numbers rather than replacing one with the other.
If the contact details are accurate, what should I verify?
The job title and the current employer. In every case where search and enrichment disagreed in this test, the email and phone were right and the role was out of date. A separate measurement puts senior contact role changes at about 1 percent a month, which is why a record can carry a correct phone number and a wrong job title at the same time.
What is Lusha’s US data coverage?
Lusha’s database includes 87.8M contacts in the United States and 105.4M across North America, broken out by country on the Lusha data page, last updated September 6, 2026. The US is the largest single market in the database.
How is Lusha’s US coverage counted?
By the contact’s recorded location, not the employer’s headquarters. A further 11.5M contacts in the database are not yet broken out by country and are counted in the global total only. Some markets are excluded from country level reporting for compliance reasons.
Can I run this test on my own list?
Yes, and the method is in the methodology section above. Take a list you already hold, run real enrichment calls rather than checking availability flags, and count only values that came back. The result will reflect your own segments, which is more useful than any vendor average.
Related resources
- How fast B2B contact data decays, and what it costs: every report on this, in one place
- Does B2B contact data quality vary by industry?: the same test across four industries
- How fast does B2B contact data decay?: the rate behind the stale title finding
- Best sales intelligence software for US data accuracy and coverage in 2026: how this test compares with what other vendors publish
- Verify a contact’s title before you reach out: the check this report argues for
- Validate emails before a campaign
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