All figures in this report are drawn from Lusha’s live signal database tracking professional job changes and promotions across B2B contacts, January to June 2026, as published in the B2B Contact Change Report. Figures are aggregate, company-level counts — no individual data is included or derivable.
Sales teams already learned this lesson the hard way: contact data decays because people move, constantly. HR and talent teams sit on the exact same problem from the other side — every candidate record, org map, and competitor talent pool is decaying at the same rate — but talent planning still mostly runs on annual cycles and static market reports. Here’s what the live movement actually looks like.
The numbers at a glance
Part One: The market you’re hiring in reshuffles daily, not quarterly
Around 13,600 company changes per working day means the talent market a plan was built on in January is not the market the team is recruiting in by March. Concretely, for a talent team, every one of those daily moves is one of four things: a candidate who just became reachable (new joiners rarely move again immediately, but the people they left behind reconsider), a sourced candidate whose record just went stale, a competitor losing coverage in a function you compete with them for, or your own backfill problem arriving.
Annual salary surveys and quarterly labor reports can’t see any of this — they aggregate after the fact. The practical shift is treating talent-market data the way sales teams learned to treat account data: as a live feed you check before acting, not a reference document you consult at planning time.
Part Two: Where the market moves fastest
Mobility is not evenly distributed across functions. Sales is by far the most mobile function in the dataset — 121,238 company changes in six months, roughly double IT’s 60,384 in second place. For talent teams this cuts two ways:
If you hire salespeople: the pool refreshes constantly — sourcing lists for sales roles decay faster than for any other function, and a list built last quarter materially understates who’s actually available now. It also means time-to-fill pressure is partially self-inflicted: the candidates exist, the list is just old.
If you retain salespeople: the same number is your churn benchmark. The market’s baseline appetite for your sales talent is structurally higher than for any other function you employ — retention programs sized on company-wide averages under-protect exactly the function most likely to be poached.
Part Three: 23,301 C-suite moves, and the cascades they start
Executive moves are the highest-leverage mobility events in the dataset, because they rarely happen alone. A new executive re-evaluates the team they inherit; the departing executive’s loyalists reconsider their own positions; and within a few quarters, one C-suite move commonly becomes a cluster of mid-level departures — each one either your retention risk or your sourcing window, depending on which side of the move you’re on.
194,165 promotions tell the quieter half of the same story. Every promotion creates a vacated role (an opening that may never hit a job board before it’s backfilled internally) and, statistically, at least one person who was passed over — historically the single most receptive moment for a competitor’s recruiter to call. Talent teams that track promotions at competitor accounts aren’t doing anything sales teams haven’t done with buying signals for years; the signal is identical, only the use changes.
Part Four: Your ATS decays exactly like a CRM
Our Data Decay Report ran a simple test on 25 fast-moving companies: snapshot what a CRM knew in January, measure what was still true by June. 23 of 25 accounts had materially changed. The same test applies, unchanged, to a talent database — the sourced-but-not-hired candidates from last year’s requisitions, the silver-medalist pool, the alumni list. The records hold titles, employers, and locations from the day they were captured, and roughly 13,600 of the people behind records like those move every working day.
The consequence isn’t just wasted outreach to dead records. It’s the opposite miss: the silver medalist from eighteen months ago who just got promoted into exactly the seniority you’re now hiring for — invisible if the record still shows their old title. Sales teams call this a buying signal. For a talent team it’s a sourcing signal, and it’s the same data.
What talent teams can do with this
1. Put a decay assumption in the sourcing workflow.
Any candidate record older than a quarter gets re-verified before outreach — the same rule sales ops teams now apply to CRM contacts, for the same reason.
2. Track promotions and exec moves at the companies you hire from.
A C-suite change at a competitor is a 2-3 quarter sourcing window at that company. A promotion round is a passed-over-candidate window. Both are visible in live signal data before they’re visible anywhere else.
3. Size retention programs by function-level mobility, not company averages.
Sales talent faces roughly double the market pull of the next function. Flat retention budgets systematically under-protect it.
4. Treat the talent plan like a forecast, not a map.
A plan built in January describes a market that has since absorbed hundreds of thousands of moves. The teams that re-check against live data mid-cycle are working with the market as it is.
Methodology and data notes
Source: Lusha live signal database, job change and promotion signals, January-June 2026, as published in the B2B Contact Change Report. This report re-frames the published figures for a talent-audience context; no new data cuts were produced for it.
Scope note: figures count detected professional job changes among tracked B2B contacts. Detection windows vary by role visibility; the published counts are floors, not ceilings.
What this report does not claim: no figures on HR-function mobility, recruiter turnover, or function-level breakdowns beyond Sales and IT are included, because those cuts were not part of the published dataset. If there is demand for a talent-function-specific cut, it can be produced as a follow-up from the same signal layer.
Privacy and compliance: all figures are aggregate. No individual contact details are included or derivable. Full privacy documentation at lusha.com/trust-center.
Corrections and right of reply: this report describes what Lusha’s tracking detected, using the stated methodology. If you believe a figure is inaccurate or want to add context, contact us via lusha.com/contact and we will review and correct where warranted, noting material corrections on this page.
