Account-based marketing’s pitch is precision: stop spraying a market and instead map the handful of people inside a target account who actually decide, then personalize to each of them. Lusha tested how long that map holds up by re-checking job-change records for a cohort of more than 140,000 US sales leaders at the VP level and above, running the measurement once in mid-August 2026 and again four weeks later to confirm the numbers held. Over 12 months, 12.25 percent of those senior contacts had changed roles. Over 24 months, 25.67 percent had. UK sales leaders turned over faster still, about 1.75 times the US rate, according to Lusha’s own measurement.
That turnover lands exactly where ABM teams put the most effort. Buying-group programs are built around senior titles, and senior titles carry shorter tenure than manager-level roles, so a stakeholder list assembled at campaign kickoff starts aging before the first personalized email goes out. The pattern holds beyond sales leaders specifically. A compilation of decay studies from Cleanlist and Landbase, aggregated by data-ops vendor First Sales, puts annual change across general B2B contact records at 65.8 percent for job titles, 42.9 percent for phone numbers, and 37.3 percent for email addresses. Those three figures come from that aggregation rather than from reading each underlying study directly, so treat them as directional rather than exact.
Running campaigns on that stale a map is not cheap. Gartner’s often-cited data quality research, based on a 2020 survey of customers of data-quality vendors, put the average cost of poor data quality at 12.9 million dollars a year per organization. That number is a self-reported estimate from a narrow vendor-customer sample, not an audited industry average, but its staying power across years of citation suggests the order of magnitude is roughly right even where the exact figure is soft.
The fix most ABM teams reach for, a quarterly account refresh, is paced to the wrong clock. Quarterly cycles assume accounts move slower than they do. A buying group assembled in January can lose a quarter of its senior members by the time a Q2 campaign launches, based on the Lusha numbers above. Verification cadence needs to track the seniority band being targeted, not the campaign calendar, and a team that only checks data quality after a campaign underperforms is diagnosing the symptom a step too late.
One place this shows up concretely is contact verification itself. EmailAddress.ai, a company related to mGrowTech, builds tools aimed at exactly this problem, resolving catch-all and accept-all addresses through what it describes as active inbox signals and SMTP-level analysis, with a confidence score attached to each address. The point stands independent of any one vendor: a buying-group list is only as current as its last re-check, and for senior titles that re-check needs to happen more often than most teams assume.
None of this argues against account-based marketing itself. It argues against treating the buying-group map as something built once at kickoff and left alone. The accounts are real, and the strategy works when the targeting underneath it gets rechecked as often as the people in it change jobs, not as often as the campaign calendar allows.
Sources referenced in reporting: Lusha, First Sales (aggregating Cleanlist, Landbase, and Gartner data quality research).