How Fast Does B2B Contact Data Decay?

Why do the studies give different numbers?

Because they measure different things on different people. Here are the three side by side.

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Read them as three different questions. Lusha counts one kind of change (a new employer) in one senior segment. ZeroBounce counts addresses that stop working, across every role. The MarketingSherpa figure claims to cover whole records, but we could not trace its study, so we use it only as the older, rougher estimate. The three don't conflict: job moves are one cause of decay, bad addresses are another, and a full record can go stale for both reasons plus new titles and phone numbers.

Lusha also searched for the source of the widely repeated "30% a year" figure and found none. It concluded the number is roughly right but attached to the wrong period: closer to a two-year number than an annual one. We couldn't trace a primary source either.

What does the Lusha study say, in detail?

From Lusha's September 12, 2026 re-run of its measurement:

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Lusha is open about the limits. It only counts moves it has spotted, and recent ones show up late: its three-month window came out at about half the usual monthly pace, which Lusha puts down to late detection, not fewer moves. It tracks employer changes only, so a new title at the same company, a changed phone number or a new email format is not in the count. Lusha calls its figures a floor, not a ceiling. Its first run, on August 15, 2026, put the 12-month figure at 12.6%, so the number moves a little between runs. This is vendor data on one segment, not a market-wide measure.

What goes stale first?

Per Lusha, the person's role and company, more than the email or phone. In two small enrichment tests (125 US contacts, then 197 more), it reports that every contact's work email still worked and that where its sources disagreed, the role was what had gone out of date. That is the vendor's claim about its own data on small samples, so check it on yours. If it holds, an address can still accept mail after the person behind it has changed jobs, and a verifier that only checks whether the mailbox exists won't flag that. See the best email verification tool for what each tool checks.

Company facts (industry, headcount, location) move slowly. Job titles move with every promotion and job change.

How does decay compound if you never refresh?

It stacks every year. Starting from 1,000 clean contacts at 22.5% annual decay, the older MarketingSherpa rate (our math):

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Ignore a list for three years and most of it is wrong, while your CRM still counts every record. On the lower, job-change-only Lusha rate, a list ages more slowly, but still loses about 123 of every 1,000 senior contacts in a year and about 257 in two.

How many contacts is that on a list this month?

Our math for 3 and 6 months, spreading the 12.25% evenly through the year (real moves won't be that even). The 12- and 24-month rows are Lusha's measured figures:

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Our house plan has one rep starting 504 new prospects a month (4 inboxes x 30 sends a day x 21 sending days = 2,520 emails, spread over 5 touches each). If those 504 prospects come from a list that is six months old, expect about 32 of them, roughly 6%, to have changed jobs since the list was pulled (our math, job moves only). Each is a sequence written for someone who no longer holds the role.

What are the signs your prospect list is decaying?

Four signals, all in data you already have:

1. Same data source, but bounces climb every quarter.
2. Fewer pickups even though nothing changed about how or when you call.
3. More replies saying "no longer here" or "wrong person."
4. A growing share of contacts whose LinkedIn title doesn't match your CRM.

Track them monthly and you have your own decay rate, which is more useful than any benchmark. When replies fall, fix the list before you raise volume: sending more to a decaying list is how teams fall into the outbound activity trap. A verification tool is the quickest way to check the email side.

How often should you refresh B2B contact data?

One rule for people data: any contact record older than 60 days gets checked again before you use it. That is our guideline, not a tested rule. Fields expire at different speeds, so each gets its own schedule:

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Three habits go with the rule:

1. Check on the day you send for top accounts. Because recent moves show up late in databases, confirm the person's current role on the day you write, rather than trusting the date of the last refresh.
2. Treat changes as triggers. A new job is a reason to write. See sales trigger events.
3. Remove bounces and moved-on contacts fast. Bounces hurt your sender reputation, and someone who no longer fits is more likely to mark you as spam. Google's sender guidelines say to keep the spam rate shown in Postmaster Tools under 0.10% and never let it reach 0.30%.

Our contact enrichment workflow shows how to run these refreshes without doing them by hand. For where to get fresh data, see the best B2B contact data provider.

When can you skip a refresh?

• A list under 60 days old: skip it. Little has changed.
• Fast-moving segments: don't wait for the 60 days. Lusha measured a UK job-change rate 1.75 times the US one.
• Low-priority accounts: skip the manual role check. Verify the address and send a segment message; see how much time to spend researching a prospect.
• Contacts you spoke with this month: skip the role check. A live conversation is fresher than any database.
• A full re-purchase: skip it when only a slice is old. Refresh that slice.

What should you do when a contact changes jobs?

Keep the record. Someone who switched companies knows you, has a new budget, and may have the same problem. Send a short re-engagement note that references their old problem and asks whether it exists at the new company.

Example: "Saw you moved to [new company], congrats. At [old company] you were working on [problem]. Is that on the list at [new company] too?" (Illustrative template.)

Stale contacts shrink your real list. See how many sends you actually need in the Pipe Playbook calculator.