Account executives with two or fewer employers in the last twelve years
Needs: Dated title and company history
B2B data, United States (global on request)
Sales Talent Data
Quota-carrying sales talent selected on dated work history: loyalty, promotion velocity, industry switches and in-place promotions, counted across ~540k current US account executives.
A recruiting search normally runs on the current title. These cuts run on the whole dated history. On the August 2026 refresh, ~84k US account executives have had two or fewer employers in the last twelve years, ~2.3k were promoted from SDR to AE inside 18 months and are now three or more years in seat, ~56k sales reps moved from software into industrial, medical device or manufacturing, and ~24k VPs of Sales were promoted at least twice inside their current company.
Each cut is delivered as a list with the current role, the roles that qualified the person, and work email status, or as a monthly feed that adds the people who newly qualify. Counts are rounded and computed from self-described titles and employers, so a title match is a filter, not a verdict. For sourcing and outreach, not employment decisions.
Cuts we run today
SDRs promoted to AE inside 18 months who are now three or more years in seat
Needs: Ordered titles inside one employer
Sales reps who moved from software into industrial, medical device or manufacturing
Needs: Industry on every past employer
VPs of Sales promoted at least twice inside their current company
Needs: Three or more titles at one employer
General-graph counts are computed on a one-in-eight sample of the professional graph, US profiles only, scaled to the population and rounded, August 2026 release. License counts come from the monthly registers, September 2026 data. Career-changer counts come from a US real estate professional profile extract joined to the registers. Every cut is a query over self-described titles, employers and dates, so a match is a filter to sample, not a verdict about a person.
Sample rows
Illustrative and synthetic. Real samples for your geography are a reply away.
| profile_id | name | current_title | current_company | current_start | employers_12y | promotions_in_place | prior_industry | location | work_email_status |
|---|---|---|---|---|---|---|---|---|---|
| PR7••• | D••••• K•••• | Enterprise Account Executive | S••••• Software | 03/2021 | 2 | 1 | Industrial Automation | Chicago, IL | Verified |
| PR2••• | A•••• M••••• | VP Sales | N•••••• Health | 08/2019 | 1 | 3 | Medical Devices | Minneapolis, MN | Pattern inferred |
Schema
| Field | Type | Notes |
|---|---|---|
| profile_id | url | non-personal |
| name | text | personal data |
| current_title | currency | non-personal |
| current_company | currency | non-personal |
| current_start | currency | non-personal |
| employers_12y | text | non-personal |
| promotions_in_place | text | non-personal |
| prior_industry | text | non-personal |
| location | text | non-personal |
| work_email_status | personal data |
Abridged. The full data dictionary ships with every sample and lists every field, its fill rate and its source.
Used for
- Quota-carrying AE and enterprise rep sourcing
- Sales leadership searches with promotion history
- Industry-switcher lists for vertical SaaS
- Competitive talent mapping by employer
How it is built
Profiles are refreshed monthly. Titles, employers, industries and dates on every past role are normalized, then each cut is a query over the ordered history. Counts on this page are from a 12.5% sample of the file scaled to the population, August 2026 release.
Questions we get
Can you run a cut I describe in plain English?
Yes. Send the sentence. We turn it into a query, return the count, and send a sample before you commit.
Is this suitable for hiring decisions?
It is a sourcing and outreach list. It is not a consumer report and is not for use in employment, credit, insurance or housing eligibility decisions.