What is list decay?

List decay, defined
List decay is the steady rate at which a working email list stops working, as people change jobs, abandon mailboxes and close accounts, commonly around 22 to 30 percent of B2B addresses a year.

Job changes drive most of it on the B2B side. Someone leaves, IT disables the mailbox, and an address that was perfect in March returns 550 in July with no warning in between.

Consumer lists decay differently and often more slowly per address, because people keep personal mailboxes for years. What they stop doing is reading them, which produces silence rather than bounces.

The arithmetic gets uncomfortable on old data. An address collected two years ago has roughly a coin flip's chance of still being live, which is why an unmailed archive is rarely worth reviving whole.

Send frequency is the hidden variable. A weekly list surfaces its own decay through bounces as it happens. A list mailed twice a year accumulates the whole year's rot and delivers it in one send.

How ZapBounce reports it

Every result we return carries the timestamp of the probe, because the answer is about that moment. For a list last verified more than three months ago, the honest move is to run it again rather than trust the old file.

Twelve thousand contacts, six months in a drawer

Take a B2B list of 12,000 addresses that was fully valid in January, and assume it decays at 25% a year. Decay compounds, so after six months about 86.6% survive. Roughly 1,600 addresses have died by July, even though nobody touched the file.

Mail the whole list in July without checking and those 1,600 come back as hard bounces in one campaign. That's a 13% bounce rate from a list you'd have called clean. Your sending platform may pause the account, and mailbox providers will have drawn their own conclusions by then.

Now run the same list on a monthly schedule. Decay at that pace is about 2.4% a month, or some 280 addresses. Each send surfaces its own small batch of bounces, the platform suppresses them, and the rate never gets near a threshold. The list and the decay are the same in both cases, and only the second one causes no trouble.

Finding where your own list is aging fastest

An average decay figure hides a lot, so measure yours by cohort. Group addresses by the year you acquired them, then by source, and compare bounce rates across groups on your next send. Event badge scans and purchased data tend to age badly. Customers who log in to your product barely decay at all.

Job titles matter as well. Contacts in high-turnover roles, with sales the usual example, change employers more often than the average, so a list built around those roles needs checking more often.

Set the re-verification schedule by how often you send. A list that's mailed weekly cleans itself through suppression, and a check every six months is plenty. Before any send to a segment that's been quiet for 90 days or more, verify that segment first. At ZapBounce's published price, a 10,000-address check is $25, which is small next to what a 13% bounce rate does to the following quarter.

List decay: common questions

How fast does a B2B list decay?

Commonly 22 to 30 percent a year, driven mostly by job changes. The rate is higher in fast-moving sectors and at smaller companies.

Does verifying stop decay?

No. It removes the addresses that have already died. The remainder keeps aging at the same rate from the day you check.

Is an old list worth verifying or discarding?

Verify a sample first. If more than a third comes back invalid, the survivors are unlikely to remember you either.

See this on your own list

100 free checks a month, and the unknowns come back labeled.