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Ankur Chavda – Professeur — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Executive Leadership And Management →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
helenlinda.com ↗	70 match 1 shared topics	Helen Linda – Professional Change Agent	en	executive-leadership-and-management WordPress	robotsllmsaihumans	emailphone	none
keithbirch.com ↗	69 match 1 shared topics	Keith Birch – Professional	en	executive-leadership-and-management WordPress WooCommerce	robotsllmsaihumans	emailphone	none
inclusiveprofessions.co.uk ↗	66 match 1 shared topics	Inclusive Professions	United Kingdom en	executive-leadership-and-management WordPress	robotsllmsaihumans	emailphone	none
houseofroseprofessional.com ↗	65 match 1 shared topics	House of Rose Professional \| Home	en	executive-leadership-and-management WordPress	robotsllmsaihumans	emailphone	none
barrynalebuff.com ↗	64 match 1 shared topics	Barry Nalebuff – Milton Steinbach Professor of Management	en	executive-leadership-and-management WordPress	robotsllmsaihumans	emailphone	none
rephlo.com ↗	64 match 1 shared topics	Jeremy Rephlo: Professional Portfolio	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none
danielbooysen.com ↗	64 match 1 shared topics	Daniel Booysen - Professional Portfolio	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none
kayleeharmon.com ↗	64 match 1 shared topics	Kaylee – Probably Not Texting You Back	en	executive-leadership-and-management WordPress	robotsllmsaihumans	emailphone	none
bryanchai.com ↗	64 match 1 shared topics	Bryan Chai \| Assistant Professor in Strategic Management	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none
evanmhamiltonofficial.com ↗	64 match 1 shared topics	Evan M Hamilton – Expert, Leader & Innovator \| A Professional Chronicle	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	partial · 8
vissasamtaletrening.com ↗	64 match 1 shared topics	VISSA – LeaderLab	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none
antwonjames.com ↗	64 match 1 shared topics	Product Management Professional \| Antwon James	en	executive-leadership-and-management Wix	robots llmsaihumans	emailphone	none
katiehurst.com ↗	64 match 1 shared topics	Katie Hurst – Project Management \| Operations	en	executive-leadership-and-management WordPress	robotsllmsaihumans	emailphone	none
keithabrahamzoom.com ↗	64 match 1 shared topics	Keith Abraham: Certified Speaking Professional	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none
baprofessionalprogrammes.com ↗	64 match 1 shared topics	Home - BUSINESS ANALYSIS PROFESSIONAL PROGRAMMES	en	executive-leadership-and-management WordPress WooCommerce	robotsllmsaihumans	emailphone	none
bryanbanisaba.com ↗	64 match 1 shared topics	Bryan Banisaba \| – Product and Strategy Leader	en	executive-leadership-and-management WordPress	robotsllmsaihumans	emailphone	none
ankushmehrotra.com ↗	63 match 1 shared topics	Ankush Mehrotra – Your Next Door CEO	en	executive-leadership-and-management WordPress	robotsllmsaihumans	emailphone	none
dariagolub.com ↗	63 match 1 shared topics	Daria Golub — Coaching for Senior Tech Professionals	en	executive-leadership-and-management	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.