What is data decay?

What causes data decay?

Data decay starts outside the record: nothing in it changes, but the world it describes does. In a B2B database, the usual causes are:

• Job changes: a contact leaves for another company, and the employer, title, email and phone in your CRM now describe someone who is gone.
• Promotions and new titles: same company, different role, sometimes a different budget.
• Company changes: moves, rebrands, mergers, acquisitions and closures change names, domains and headquarters.
• Closed mailboxes: when someone leaves, their work email usually stops working, and messages to it start to bounce.

Problems that were there from the start are not decay. A typo, a duplicate or an empty field is a data hygiene problem, and two records for the same company is a matter of entity resolution.

How fast does B2B data decay?

B2B data has no single decay speed: it depends on who and what you store. The measurement above takes one population, every profile titled exactly VP of Sales in three US cities, and asks when each person started the job they hold today.

Of the 304 profiles with a start date, 94 began their current job in 2025 or 2026. Read it as a list. Had you saved these same 304 people at the end of 2024, the job on file would now be wrong for 94 of them, about one in three, after less than two years, without anyone touching the list. And 30 of them started in 2026 alone, so a list saved on January 1, 2026 is already out of date on 30 records.

What this measurement does not say matters as much:

• It is one title in three cities. SDRs, CFOs and engineers change jobs at other speeds, and so do other regions. These counts are not a rate for your database.
• It only sees changes already on file. A job change reaches a database when the person updates their profile, so the newest months are undercounted.
• It follows the people who hold the title today. VPs of Sales who left the role since 2024 are not counted, although a list saved back then would include them.

Treat any decay rate quoted without its population, its field and its date with care, this one included.

How do you measure data decay?

To measure data decay, choose a population you care about, a field that carries a date or can be checked, and a window. Then count what changed. Two methods work:

1. Read a dated field, as above. The start date of each person’s current job tells you how many changed jobs since any date you pick.
2. Re-check a random sample of your own records. Take a few hundred contacts, enrich them again from a fresh source, and count how many changed employer, title or email since they were last checked. That share, over that time, is your decay rate for that population.

For email, bounces are the visible part: a bounce rate that climbs on an old list is decay showing up in your sending tool. Whatever the method, publish the population, the field, the dates and the sample size with the result. Without them, a decay rate cannot be compared with anything.

Data decay, data hygiene and data enrichment: what is the difference?

Data decay is the reason data hygiene and data enrichment are never finished. Data enrichment and hygiene run on a schedule because the people and companies in your records keep moving.

	What it is	What it deals with
Data decay	Records going out of date as the world changes	Nothing: it is the problem
Data hygiene	The routine that keeps records clean: merge duplicates, fix formats, flag stale records	Duplicates, formats, records known to be stale
Data enrichment	Adding or refreshing fields from an outside source	Missing values, and values that decayed

Check yourselfFour problems found in the same CRM. Which one is data decay?

• A contact was saved with a typo in her last name
• A VP of Sales who changed companies in March still shows his former employer
• The same company appears twice, as acme.com and as Acme Inc.
• Many contacts have no phone number

Show the answer key

1. ✕A contact was saved with a typo in her last nameThe record was wrong from the day it was entered, and nothing changed in the world: that is a hygiene problem.
2. ✓A VP of Sales who changed companies in March still shows his former employerThe record was right when it was saved; the person moved and the record did not. That is decay.
3. ✕The same company appears twice, as acme.com and as Acme Inc.Two records for one entity is a matching problem, solved by entity resolution, not decay.
4. ✕Many contacts have no phone numberA field that was never filled is incomplete data: enrichment fills it, but nothing decayed.

How do you keep CRM data from decaying?

You cannot stop CRM data from decaying; you can shorten the time a wrong record stays wrong. Refresh on a schedule that follows the value of the records, with the accounts in active deals and your target accounts first and the rest of the database on a slower cycle. Refresh on events too: a bounce, a reply from someone new, a company that changes its domain.

With BlitzAPI, Profile Enrichment returns a person’s current role and employer from their profile URL, and the CRM hygiene use case shows how to run that refresh on events from a CRM or a workflow tool such as n8n, Make or Zapier.