Executive Turnover Signals

Executive Turnover Signals

Anticipate risk and opportunity with verified board exits and C-suite moves, tied to company viability.

Anticipate risk and opportunity with verified board exits and C-suite moves, tied to company viability.

Why this matters

Why this matters

Executive movement opens doors for advisory and GTM — but signals are scattered across registries, press, and profiles, making them hard to trust or operationalize. This segment consolidates board resignations (hard signals) and C‑suite changes (soft signals), ties them to company viability, and delivers flat, explainable events you can plug into CRM/BI for timely outreach.

How Starzdata solves this

How Starzdata solves this

  • Resolve input companies from name/website to verified entity.

  • Detect board resignations (registries) and executive changes (web/press/profiles).

  • Classify roles using standardized role/level taxonomy.

  • Add timestamps for last change and last verification with source & confidence.

  • Overlay company solvency/active status and generate a plain‑language comment.

This segment is activated with a blend of trusted sources and your own inputs

AI reasoning

User Input

Curated APIs

Web intelligence

What you get:

What you get:

  • Structured churn events with unique IDs

  • Verified executives, roles, and timelines

  • Confidence scores for each enriched field

  • Solvency and active status overlays

  • Taxonomy tags to align with your workflows

One dataset, ready for GTM or CRM integration.

Sample data for this segment

#company name input(input)website input(input)event idcompany id externalcompany id external confidencecompany namecompany name confidencewebsite domainwebsite domain confidenceexecutive nameexecutive name confidenceexecutive linkedin urlexecutive linkedin url confidencerole titlerole title confidencerole categoryrole category confidencerole levelrole level confidenceposition typeposition type confidenceemployment start dateemployment start date confidenceemployment end dateemployment end date confidencejob last changedjob last changed confidencejob last verifiedjob last verified confidenceevent typeevent type confidenceexit sourceexit source confidenceexit reasonexit reason confidenceexit confidencesolvency scoresolvency score confidenceactive status flagactive status flag confidenceviability flagviability flag confidencechurn commentcustom taxonomy tags
1Nordic Energy ABnordicenergy.comEVT-2025-0001CO_20019100%Nordic Energy AB100%nordicenergy.se96%Anna Lindqvist96%https://www.linkedin.com/in/anna-lindqvist90%Board Member100%board100%board100%Board100%2019-05-12100%2025-03-18100%2025-03-19T08:12:00Z100%2025-03-20T10:30:00Z100%exit100%registry100%Resignation90%100%82100%true100%true100%Board resignation filed in registry; solvency 82 —...["Energy","Transition"]
2AgriChain France SAagrichain.frEVT-2025-0028CO_20044100%AgriChain France SA100%agrichain.fr98%Jean Moreau94%https://www.linkedin.com/in/jean-moreau-45688%Chief Financial Officer90%cxo95%cxo95%C-suite95%2022-02-0180%2025-07-0585%2025-07-06T09:20:00Z90%2025-07-10T11:45:00Z90%exit90%linkedin90%Role ended (profile update)80%88%78100%true100%true100%CFO exit detected via profile update; firm remains...["AgriTech"]
3BuildSmart Italia SRLbuildsmart.itEVT-2025-0042CO_20101100%BuildSmart Italia SRL100%buildsmart.it99%Clara Rossi93%https://www.linkedin.com/in/clara-rossi90%Chief Operating Officer88%cxo93%cxo93%C-suite93%2021-09-1585%2025-06-3085%2025-07-01T12:00:00Z90%2025-07-03T10:00:00Z90%exit90%press88%Restructuring announcement85%87%80100%true100%true100%COO departure confirmed by press; viable balance s...["Construction"]
4MedLife Diagnostics GmbHmedlife-diagnostics.deEVT-2025-0060CO_20122100%MedLife Diagnostics GmbH100%medlife-diagnostics.de97%Thomas Berger96%https://www.linkedin.com/in/thomas-berger87%Chair of the Board100%board100%board100%Board100%2017-01-10100%2025-04-15100%2025-04-16T08:00:00Z100%2025-04-18T10:15:00Z100%exit100%registry100%Mandate ended95%100%85100%true100%true100%Chair mandate ended per filing; high solvency — bo...["MedTech","Healthcare"]
5ChemPro Polska Sp. z o.o.chempro.plEVT-2025-0074CO_20130100%ChemPro Polska Sp. z o.o.100%chempro.pl99%Sofia Johansson95%https://www.linkedin.com/in/sofia-johansson89%Chief Technology Officer88%cxo92%cxo92%C-suite92%2019-10-0180%2025-08-0185%2025-08-02T07:30:00Z90%2025-08-05T09:10:00Z90%exit90%linkedin90%Profile update — role ended80%88%52100%true100%100%CTO exit via profile change; low solvency — potent...["Chemicals"]
Showing 1 to 5 of 5 entries • Click row for details

Each row is a churn event detected for one company. Your inputs (name, domain) are resolved into verified entities with confidence scores. Executive details (name, role, LinkedIn, dates) are captured and scored, alongside the event type, evidence source, and reason. Overlays like solvency, active status, and taxonomy tags show business impact at a glance.

Your questions on this segment, answered

How fast can I test this?

How fast can I test this?

How fast can I test this?

How do you handle personal data (names, LinkedIn)?

How do you handle personal data (names, LinkedIn)?

How do you handle personal data (names, LinkedIn)?

For 1,000 companies, what should I expect? And if I scale to 50,000?

For 1,000 companies, what should I expect? And if I scale to 50,000?

For 1,000 companies, what should I expect? And if I scale to 50,000?

How is this different from LinkedIn scraping or a registry feed?

How is this different from LinkedIn scraping or a registry feed?

How is this different from LinkedIn scraping or a registry feed?

Can this integrate directly into my CRM?

Can this integrate directly into my CRM?

Can this integrate directly into my CRM?

What makes an exit a real business signal?

What makes an exit a real business signal?

What makes an exit a real business signal?

How fast after a filing or LinkedIn update will the signal appear?

How fast after a filing or LinkedIn update will the signal appear?

How fast after a filing or LinkedIn update will the signal appear?

Are your signals really reliable and complete?

Are your signals really reliable and complete?

Are your signals really reliable and complete?

Your questions on this segment, answered

How fast can I test this?

On the platform, first signals appear in minutes to hours depending on volume. In project mode, a dataset is delivered in 48–72h. In both cases, you validate quickly before scaling.

How do you handle personal data (names, LinkedIn)?

Everything runs in a dedicated EU instance, with audit logs and external DPO oversight. No unnecessary storage: each signal keeps its source, you keep compliance.

For 1,000 companies, what should I expect? And if I scale to 50,000?

A leadership team averages 6–8 members. For 1K firms, that’s 6–8K people. With 15–25% annual churn, expect 900–2,000 signals per year. Scaling is credit-based: you pay for volume, not licenses.

How is this different from LinkedIn scraping or a registry feed?

Because we combine multiple sources, score every signal, and align them to your taxonomy. Not raw noise, but actionable data.

Can this integrate directly into my CRM?

Yes. Native connectors for Salesforce, HubSpot, or data lakes. Or simple export to CSV, JSON, or Sheets. No rework needed: scores and structure are preserved.

What makes an exit a real business signal?

Each event comes with a plain comment, a solvency overlay, and press/market reactions when available. You immediately know if it’s routine churn or a strategic alert.

How fast after a filing or LinkedIn update will the signal appear?

It depends on the country and sector: sometimes hours, sometimes days. LinkedIn and press tend to be faster. Every event is timestamped so you know its freshness.

Are your signals really reliable and complete?

We don’t rely on a single source. Each event is cross-checked (registry, press, profiles, APIs) and scored. You see the signal, its source, and its confidence level.

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