CUFinder’s detection graph logged 224,684,415 job changes in roughly three months, between June 1 and September 17, 2026. That is about 2.1 million job changes detected every single day. And 91% of them are people walking out of one company and into another.
Updated September 2026. All first-party figures queried September 17, 2026.
I’m going to be honest with you. Most job change statistics floating around the internet are recycled. One blog quotes another blog, which quotes a survey from 2019, and nobody links a primary source. I got burned by that once. In 2023, I built a renewal campaign in Hamburg on a champion list I trusted, and a quarter of those contacts had quietly moved on. We found out when the emails bounced. The deal we lost that quarter still stings.
So this page does it differently. Every first-party number below comes from a query I ran against CUFinder’s own data graph in September 2026, with dates on everything. Every external number comes straight from the Bureau of Labor Statistics or Gallup, linked. Cite anything here with a link back. That’s what it’s for.
Job Change Statistics 2026: The Key Numbers
Short on time? These are the headline job change statistics for 2026, each one self-contained and ready to quote:
- 224,684,415 job changes were detected worldwide in about three months, June 1 to September 17, 2026 (CUFinder, September 2026).
- That works out to about 2.1 million detected job changes per day, or roughly 24 every second (CUFinder, September 2026).
- Extrapolated to a full year, that pace implies roughly 760 million detectable job changes annually (CUFinder estimate, September 2026).
- 91.0% of detected job changes are company changes; only 0.8% are promotions and 8.2% are lateral title changes (CUFinder 100,000-event sample, September 2026).
- In 92.4% of detected company changes, the person’s new employer was not yet publicly visible at detection time (CUFinder, September 2026).
- The median US worker stays 3.9 years with one employer, down from 4.1 years in 2022 (BLS, January 2024 data).
- Americans born between 1957 and 1964 held 12.7 jobs on average between ages 18 and 56 (BLS NLSY79).
- 3.1 million Americans quit their jobs in July 2026 alone, a 1.9% monthly quits rate (BLS JOLTS).
- Workers aged 55 to 64 stay 9.6 years at a job; workers aged 25 to 34 stay just 2.7 (BLS, January 2024 data).
- Professionals with manager, senior, director, or VP titles appear about 35% less often among job changers than in the wider professional base (CUFinder estimate, September 2026).
Now let’s walk through where every one of those numbers comes from. Because that part matters more than people think.
The Three-Month Picture: How Fast Job Changes Pile Up
The single biggest takeaway from our data is velocity. Job changes are not an occasional event. They are a constant, massive stream.
CUFinder’s detection graph watches public professional profiles, mostly LinkedIn, and records an event when a person’s company or title changes. The current detection pipeline came online on June 1, 2026. In the roughly 108 days between then and September 17, it logged all 224.7 million events. Three months, not a year. Keep that pace in your head: extrapolated over a full year, it implies roughly 760 million detectable job changes, though that yearly figure is an estimate, not a measurement. Here’s the month-by-month view:
| Month (2026) | Job changes detected |
|---|---|
| June (pipeline ramp-up) | 14,674,617 |
| July | 100,237,234 |
| August | 87,027,817 |
| September 1 to 17 | 22,744,747 |
| Total, Jun 1 to Sep 17 | 224,684,415 |
Job changes detected per month, 2026
Source: CUFinder data graph (224M+ job changes in 3 months), September 2026.
Stat 1: 224,684,415 job change events were detected between June 1 and September 17, 2026, a window of about 108 days (CUFinder, September 2026).
Stat 2: Detection has averaged about 2.1 million job changes per day since June 1, 2026. That is roughly 86,000 per hour, or 24 per second.
Stat 3: The busiest detection week logged 32.97 million job changes (June 29 to July 5, 2026). Even the slowest week logged 7.5 million.
One honest note on reading that chart. The month-to-month swings reflect how our detection batches run, not seasonal hiring waves. July’s 100 million includes a burst of catch-up processing. So don’t quote July as “the biggest month for job hopping.” Quote the total and the daily average. Those are the solid numbers.
📌 Example: A 10,000-contact CRM sounds stable. But at the global pace our graph observes, the professional world it describes shifts millions of times before your Monday pipeline review.
Week by Week: The Velocity Never Drops to Zero
Monthly totals smooth things out. The weekly view shows the raw pulse of the pipeline:
| Week starting (2026) | Detections | Week starting (2026) | Detections |
|---|---|---|---|
| Jun 22 | 7.50M | Aug 3 | 12.21M |
| Jun 29 | 32.97M | Aug 10 | 18.03M |
| Jul 6 | 20.74M | Aug 17 | 12.35M |
| Jul 13 | 10.75M | Aug 24 | 28.44M |
| Jul 20 | 31.82M | Aug 31 | 7.97M |
| Jul 27 | 21.39M | Sep 7 | 11.64M |
Job changes detected per week (12 weeks to September 14)
Source: CUFinder data graph (224M+ job changes in 3 months), September 2026.
Twelve weeks, 215.8 million detections, an average of 18 million per week. The peaks and valleys track our processing batches, so read the average, not any single spike. But here’s the part worth quoting: even the quietest week on record still surfaced 7.5 million job changes. There is no off-season.
Company Changes vs Promotions vs Lateral Moves
Not every job change means a new employer. So we split every detected event into three kinds: a company change, a promotion inside the same company, or a lateral title change. I sampled 100,000 random events to measure the mix. The result surprised me.
| Kind of job change | Share of sample | Scaled to full window (est.) |
|---|---|---|
| Company change (new employer) | 91.0% | ~204.5 million |
| Lateral title change (same company) | 8.2% | ~18.4 million |
| Promotion (same company, step up) | 0.8% | ~1.7 million |
What kind of job changes are they? (100,000-event sample)
Source: CUFinder data graph (224M+ job changes in 3 months), September 2026.
Stat 4: 91.0% of detected job changes are company changes: the person left one employer for another (CUFinder 100,000-event sample, September 2026).
Stat 5: Lateral title changes make up 8.2% of detected events, and clear promotions just 0.8% (CUFinder 100,000-event sample, September 2026).
What does that mean? Public profiles dramatically under-show internal careers. People update LinkedIn when they switch companies. They often don’t bother for an internal step up, or they only touch the title line, which lands in our lateral bucket. So the honest reading is not “promotions are rare.” It’s “promotions are rarely announced.” If you track champions by waiting for promotion posts, you’re seeing the tip of the tip of the iceberg.
I learned this one the embarrassing way. In 2024, a contact I’d been nurturing for months went silent, and I assumed she’d ghosted us. Nope. She had been promoted from marketing manager to head of demand gen at the same company and inherited a completely different budget. Her profile never announced it. Her email signature did. Internal moves break deals just as thoroughly as external ones, and they leave far fewer public footprints.
The Detection Gap: Departures Show Up Before Destinations
Here’s the number nobody else publishes, and it changes how you should think about job change data.
When our graph catches a company change, there are two possible states. Either the person’s new employer is already visible on their profile, or the old role has ended and the destination is still blank. I measured the split in the same 100,000-event sample:
| State at detection time | Share of company changes |
|---|---|
| Departure visible, new employer not yet public | 92.4% |
| New employer already visible | 7.6% |
The detection gap: what a company change looks like at detection
Source: CUFinder data graph (224M+ job changes in 3 months), September 2026.
Stat 6: In 92.4% of detected company changes, the new employer was not yet publicly listed at the moment of detection (CUFinder, September 2026).
Stat 7: Only 7.6% of company changes surface with the destination already filled in (CUFinder, September 2026).
So there is a real gap between “this person left” and “here’s where they landed.” People wrap up notice periods, take a break, or wait out probation before they update the new role. Gallup’s research points the same direction from the other side: over 77% of voluntary departures happen within three months of someone starting to look. The move happens fast. The public record catches up slowly. And whoever notices the departure first gets months of head start on everyone waiting for the shiny new title.
💡 Pro tip: Treat a detected departure as the trigger, not the new title. By the time a profile proudly shows the new company, the welcome window has usually closed.
How Often Do People Change Jobs?
The average American changes jobs roughly every four years, and holds 12.7 jobs between ages 18 and 56. That’s the direct answer, straight from the Bureau of Labor Statistics.
Let’s unpack it, because the lifetime numbers are wilder than most people expect. The BLS National Longitudinal Surveys followed the same Americans for decades. Workers born between 1957 and 1964 held an average of 12.7 jobs from age 18 to age 56. Men averaged 12.8 and women 12.5. Nearly identical.
Stat 8: The average American born 1957 to 1964 held 12.7 jobs between ages 18 and 56 (BLS NLSY79).
Stat 9: Younger workers are on the same road: Americans born 1980 to 1984 had already held 9.0 jobs by age 36 (BLS NLSY97).
Stat 10: 3.1 million Americans quit in July 2026 alone, a 1.9% quits rate. At that pace, about 37 million US quits a year (BLS JOLTS, July 2026).
And here’s where the official numbers meet ours. JOLTS counts about 3.1 million monthly US quits from a survey of employers, published with a month of lag. Our graph logs around 18 million job changes per week globally, in something close to real time, including the title moves surveys never see. Different lenses, same story. The BLS tells you the average. The detection graph shows you the stream.
Do Younger Generations Really Change Jobs More?
Yes, but mostly because they’re young, not because they’re built differently. The longitudinal data is humbling here. The boomer cohort that ended up with 12.7 lifetime jobs did much of that hopping in its first working decade, back in the 1970s and 80s. Early-career churn has always been the norm.
Compare like with like and the generations look similar. Millennials born 1980 to 1984 held 9.0 jobs by age 36, which puts them on pace for a boomer-like lifetime count. What HAS changed is visibility: every one of those moves now updates a public profile, feeds an algorithm, and lands in a graph like ours within days. Your grandfather changed jobs quietly. Your SDR changes jobs in front of 224 million data points.
Average Job Tenure in 2026
The median US worker has been with their current employer for 3.9 years, per the latest BLS Employee Tenure release (January 2024 data). And that number hides a huge age split.
| Age group | Median tenure (years) |
|---|---|
| 16 to 19 | 0.8 |
| 20 to 24 | 1.4 |
| 25 to 34 | 2.7 |
| 35 to 44 | 4.6 |
| 45 to 54 | 7.0 |
| 55 to 64 | 9.6 |
| 65 and over | 9.8 |
| All workers | 3.9 |
Median job tenure climbs with age (US, January 2024)
Source: US Bureau of Labor Statistics, Employee Tenure release, January 2024 data.
Stat 11: Median US job tenure is 3.9 years, down from 4.1 years in January 2022 (BLS, January 2024 data).
Stat 12: Workers aged 55 to 64 stay 9.6 years with an employer. Workers aged 25 to 34 stay 2.7. That is a 3.6x gap (BLS, January 2024 data).
Stat 13: Men hold a 4.2-year median tenure vs 3.6 for women; public sector workers stay 6.2 years vs 3.5 in the private sector (BLS, January 2024 data).
Notice something? “Job hopping” isn’t a generational personality trait. It’s a career stage. Twenty-five-year-olds in 1990 hopped too. People settle as they age into senior roles, and today’s 25 to 34 cohort will likely follow the same curve. So when you plan around average job tenure, plan around the age mix of YOUR audience, not the national blend.
One more trap worth naming: average vs median. The BLS reports the MEDIAN, the middle worker, and that’s the number to use. A plain average gets dragged upward by 30-year veterans, so it flatters your data’s stability. If you’re modeling how fast a contact list ages, the median is the honest yardstick. Half of all employment relationships are already shorter than 3.9 years.
🔍 Did you know? Public sector workers stay almost twice as long as private sector workers: 6.2 years vs 3.5 (BLS, January 2024 data). Selling into government? Your contacts decay at nearly half the speed.
Employee Turnover Statistics: What the Churn Costs
US employers recorded 5.1 million total separations in July 2026 alone, a 3.2% monthly rate, per BLS JOLTS. Quits, layoffs, retirements: the churn never pauses.
| JOLTS measure (July 2026) | Level | Rate |
|---|---|---|
| Job openings | 7.3 million | 4.4% |
| Hires | 5.1 million | 3.2% |
| Total separations | 5.1 million | 3.2% |
| Quits (voluntary) | 3.1 million | 1.9% |
The US labor market in one month (JOLTS, July 2026)
Source: US Bureau of Labor Statistics, JOLTS, July 2026.
Stat 14: US employers posted 7.3 million job openings and made 5.1 million hires in July 2026 (BLS JOLTS).
Stat 15: 42% of employees who quit say their manager or organization could have prevented it (Gallup, 2024).
Stat 16: Replacing a leader costs about 200% of their salary; a technical professional about 80%; a frontline employee about 40% (Gallup).
Stat 17: 51% of US workers say they are watching for or actively seeking a new job (Gallup, 2024).
Gallup’s framing deserves a direct quote, because HR teams tend to treat turnover like weather:
“42% of employees who voluntarily left their organization in the past year report that their manager or organization could have done something to prevent them from leaving.”
Gallup, Employee Turnover Is Preventable but Often Ignored, 2024
Half of turnover is weather. The other half is a leaky roof someone chose not to fix. And with half the workforce quietly watching job boards, the 224 million moves in our graph stop looking surprising. They look inevitable.
A quick word on industry benchmarks, because “what’s a good turnover rate” is the most common follow-up question. I won’t hand you a made-up league table. Rates differ wildly by sector, and most industry tables online trace back to nothing. Instead, pull your industry’s quits and separations rates directly from the JOLTS data tables in the release above, then compare your trailing 12 months against that. Ten minutes of work, and you’re benchmarking against the primary source instead of a screenshot of a screenshot.
Who Changes Jobs the Most? Seniority Tells the Story
Individual contributors change jobs the most, and every management tier above them changes measurably less. Our data lets us measure this in a way surveys can’t.
Here’s the method, in one breath. I classified the pre-move job titles of 100,000 sampled changers with English keyword rules, then ran the exact same rules over a 0.2% sample of the 270 million professionals in CUFinder’s contact base. Same yardstick on both sides. If a tier moves at an average rate, its two shares should match.
| Seniority tier (from title) | Share of job changers | Share of professional base | Mover index |
|---|---|---|---|
| Founder / C-level / owner | 10.6% | 10.2% | 1.04 |
| Manager / lead | 8.2% | 12.5% | 0.65 |
| Senior individual contributor | 2.5% | 3.9% | 0.65 |
| Director / head of | 0.4% | 0.7% | 0.65 |
| VP | 0.2% | 0.2% | 0.67 |
| Other individual contributors | 78.1% | 72.5% | 1.08 |
Leadership titles are underrepresented among job changers
Source: CUFinder data graph (270M+ contacts, 224M+ job changes in 3 months), September 2026.
Stat 18: Manager, senior, director, and VP titles each appear about 35% less often among job changers than in the professional base, a mover index near 0.65 (CUFinder estimate, September 2026).
Stat 19: Founder and C-level titles move at parity with their base share: 10.6% of changers vs 10.2% of the base (CUFinder estimate, September 2026).
This lines up beautifully with the BLS tenure curve. Churn concentrates in earlier-career people who haven’t hit the manager rungs yet. But the C-level parity is the fun one. Executives keep moving: founders wind down companies, C-suites get reshuffled, fractional roles multiply. Seniority slows job changing. It never stops it. One promotion from our sample says it best: a “data processing specialist” resurfaced as a “senior data operations analyst.” Careers compound quietly like that, millions of times a week.
Which Functions Show Up Most Among Job Changers?
Function is harder to measure than seniority, so treat this table as directional. About a third of sampled mover titles match common English function keywords; the rest are non-English or too idiosyncratic to classify. Among the classifiable third:
| Function (keyword match) | Share of classifiable movers | Function (keyword match) | Share of classifiable movers |
|---|---|---|---|
| Education | 20.7% | Finance | 6.6% |
| Engineering | 18.1% | IT & data | 6.5% |
| Healthcare | 9.4% | Operations | 6.5% |
| Design | 9.1% | HR & recruiting | 2.8% |
| Sales | 8.4% | Customer service | 2.8% |
| Marketing | 7.2% | Legal | 2.0% |
Teachers, engineers, and clinicians dominate the classifiable stream, partly because those professions are huge and label their titles clearly. Sales and marketing together account for roughly one in six classifiable moves. So if your pipeline lives on sales and marketing contacts, congratulations: you picked two of the most mobile B2B functions to build relationships with.
The Professional Base Behind the Numbers
All those ratios need a denominator, so meet the base: 270,154,592 contact records with company and role context. Here’s how the ten biggest departments break down, scaled from a 0.2% sample:
| Department | Contacts (est.) |
|---|---|
| Engineering & Technical | 46.7M |
| C-Suite | 30.5M |
| Information Technology | 29.4M |
| Operations | 25.1M |
| Marketing | 21.8M |
| Sales | 20.2M |
| Human Resources | 15.3M |
| Finance | 14.5M |
| Medical & Health | 10.8M |
| Product | 10.2M |
The ten biggest departments in the professional graph
Source: CUFinder data graph (270M+ contacts), September 2026.
Stat 20: Engineering & Technical is the largest department in the professional graph at an estimated 46.7 million contacts (CUFinder 0.2% sample, September 2026).
Stat 21: 50.2% of size-tagged contacts work at companies with 1,000 or more employees, and 27.7% at companies with more than 10,000 (CUFinder 0.2% sample, September 2026).
Company Size: Where These Professionals Work
Size matters for churn math too, because enterprise contacts and startup contacts decay differently. Here’s the company-size mix of the base, from the same 0.2% sample:
| Company size (employees) | Share of size-tagged contacts |
|---|---|
| 1 to 10 | 9.6% |
| 11 to 50 | 11.6% |
| 51 to 200 | 12.3% |
| 201 to 1,000 | 16.4% |
| 1,001 to 10,000 | 22.6% |
| 10,001 and up | 27.7% |
Company size of the professional base (share of size-tagged contacts)
Source: CUFinder data graph (270M+ contacts), September 2026.
Why show this? Because every “who moves” statistic above is relative to this population, and I’d rather you see the denominator than trust me blindly. It skews toward big companies and toward people who keep public profiles. That’s exactly the crowd whose job changes you can actually observe.
What 224 Million Job Changes Mean for Your CRM
Now the part that made me build this page in the first place. If the median worker moves every 3.9 years, then simple arithmetic says roughly a quarter of any B2B contact list changes employer within a year. Call it about 2% a month, before you count promotions and title moves.
Stat 22: A 3.9-year median tenure implies that roughly 25% of a typical contact list changes employer within 12 months, around 2% every month (estimate derived from BLS tenure data).
Back in my Hamburg days, we treated list decay like an annual cleanup chore. Wrong mental model. It’s a leak, not a spill. Run the arithmetic on your own database once and it changes how you plan:
→ 10,000 contacts → ~200 change employer every month → ~2,400 gone stale in a year → one in four “warm” contacts emailing into the void.
The teams that handle this well flip it. They treat job changes as buying signals instead of hygiene problems: a champion landing somewhere new is the warmest door-opener in B2B, and Gallup’s 77% figure says most of those landings happen within three months of the first quiet job search. That’s why job change alerts exist as a category, and why engineering teams wire job change data APIs into their CRMs to catch the 92.4% departure window while it’s still open.
And that’s as promotional as this page will get. The numbers stand on their own, whoever’s tooling you use.
Methodology: Where Every Number Comes From
First-party data. Job change figures come from CUFinder’s detection graph: 224,684,415 events detected between June 1 and September 17, 2026, the roughly three-month period since the current pipeline came online. The collection retains up to 12 months of events on a rolling basis; this report covers the detection period observed so far. A job change here means a detected company or title transition on a public professional profile. The graph sits alongside 270,154,592 contact records and 22,012,935 LinkedIn company profiles; the same event stream powers CUFinder’s job changes API.
Definitions. Company change: new employer detected. Promotion: same employer, higher title. Lateral title change: same employer, changed title without a clear step up. Monthly totals are exact counts; detection timing reflects processing batches, not the day a person physically switched desks.
Sampling. Kind split, destination resolution, and seniority figures are estimates from 100,000-event random samples. Base distributions come from a 0.2% table sample of the contact base (about 540,000 records). Seniority classification uses English keyword rules on job titles, so non-English titles concentrate in the “other” tier on both sides of the comparison; the mover index divides like by like.
External data. US tenure and turnover figures come from the Bureau of Labor Statistics (Employee Tenure, January 2024 data; JOLTS, July 2026) and Gallup (2024). Every external stat links its primary source. Nothing here is quoted from a stats aggregator.
How to Cite These Job Change Statistics
Quote any number on this page freely, with a link back. Ready-made citation: “According to CUFinder’s job change statistics report (September 2026), 224.7 million job changes were detected in about three months, 91% of them company changes.” Canonical URL: https://cufinder.io/blog/statistics/job-change-statistics/
FAQ
What percentage of people change jobs each year?
Roughly a quarter of US workers separate from their employer in a year. JOLTS counted 5.1 million separations in July 2026 alone, about 3.2% of employment in one month. Our detection graph sees the same story globally: 224.7 million changes detected in about three months.
How often does the average person change jobs?
About every four years, based on the 3.9-year median tenure from the BLS. Over a working lifetime that compounds to 12.7 jobs between ages 18 and 56 for Americans born 1957 to 1964.
How many jobs will millennials have in their lifetime?
Millennials born 1980 to 1984 had already held 9.0 jobs by age 36, per the BLS NLSY97 survey. They are tracking toward the 12-plus lifetime jobs of earlier generations, possibly more.
What is a normal employee turnover rate?
US total separations ran at 3.2% per month in July 2026 (JOLTS), which annualizes to a bit under 40% including all quits, layoffs, and retirements. Voluntary quits alone ran 1.9% monthly. Anything well above your industry’s blend deserves a hard look.
Is 20% employee turnover high?
Not by itself. A 20% annual rate sits below the recent US all-industry pace implied by JOLTS separations. But context rules: 20% is painful for a hospital’s nursing staff and unremarkable for seasonal retail.
Is 42% of employee turnover preventable?
That’s Gallup’s finding, yes. 42% of employees who quit said their manager or organization could have done something to keep them. Most cited fixes were simple: a conversation, recognition, or a growth path.
What is considered good tenure at a job?
It depends on your age band. The US median is 3.9 years, but 2.7 years is typical for ages 25 to 34, while 7.0 years is typical for ages 45 to 54. Matching or beating your cohort’s median reads as solid.
Is 7 years at a job too long?
No. Seven years is right at the median for workers aged 45 to 54, and below the 9.6-year median for ages 55 to 64. Long tenure only becomes a career risk when growth stalls with it.
What is the number one reason people quit their jobs?
Preventable, manager-shaped reasons lead. Gallup found 42% of leavers say the organization could have stopped it, and 45% of departing employees had no proactive conversation with their manager in their final three months.
How fast does B2B contact data decay from job changes?
Around 2% of a typical contact list changes employer every month, roughly 25% a year, based on the 3.9-year BLS median tenure. Title changes and promotions push effective decay higher still.
It’s Time to Treat Job Changes as Data
224.7 million moves in one window. 2.1 million a day. Every four years, on average, every person in your pipeline.
So stop treating job changes as annoying surprises. They’re the most predictable force in B2B data. Bookmark this page, quote the numbers in your next deck, and check back: the figures refresh as the window rolls.
Spot a number you’d like sliced differently, by industry, region, or role? Tell me. This report grows with its readers. You got this!
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