Use case: Job-change signals

Prioritize outreach with job-change predictions

Ask Xverum's Next Move Signal scores how likely a person is to change jobs, before they declare they are open to work.

200 free credits every month, no credit card.

See it in action

Demo data

Input: a shortlist of six people. The AI assistant asks for a score for each one, then ranks the ones that have a score. The sixth person was added to show a result with no score. In real shortlists, most people have none.

RankNameCompanyScoreEvidence observed
1Ethan DemoVitalink Health0.91August 28, 2026
2Maya DemoCardia Health0.88August 19, 2026
3Daniel DemoNimbus Health0.74August 5, 2026
4Priya DemoHelix Care0.63July 22, 2026
5Sofia DemoCorvus Health0.57June 30, 2026
Noah DemoFront Range HealthNo scoreNone
  • Factors behind Ethan's score, most significant first: professional presentation (high), skills and networking (moderate), career activity (low).

Credits at standard rates: 50 (5 scores, and the unscored call is free)

Technical details

One demo call per person, in table order. The demo returns fixed sample data.

curl "https://search-api.xverum.com/v1/demo/profiles/9990000004/job-change"
curl "https://search-api.xverum.com/v1/demo/profiles/9990000001/job-change"
curl "https://search-api.xverum.com/v1/demo/profiles/9990000002/job-change"
curl "https://search-api.xverum.com/v1/demo/profiles/9990000003/job-change"
curl "https://search-api.xverum.com/v1/demo/profiles/9990000005/job-change"
curl "https://search-api.xverum.com/v1/demo/profiles/9990000011/job-change"

How it works

  1. Start from a list of people. Use a shortlist of candidates, or the champions in your deals and accounts. Each person needs the profile ID that a people search returns.

  2. Get the scores. Scores run from 0.5 to 1, and a higher score means a move is more likely. Each score is based on the last 180 days of profile activity before that week's run, and comes with the factors behind it and a signal date — when the evidence was observed. Scores refresh weekly, so a current score can rest on older evidence.

    predict_job_change_xverum · 10 credits per score, free when there is no score

  3. Act on the scores. In recruiting, start with the highest scores on a shortlist that already fits the role. In sales, check in on the accounts where a champion has a high score. Some people with a high score will stay where they are.

See every field in the job-change docs →

Two ways to use it

In your AI assistant or agent, through MCP. Recruiters rank a shortlist and sales teams check on their champions, from Claude, ChatGPT, Cursor, or another MCP client.

Set up the MCP server →

In your product, through the REST API. Add job-change scores to a recruiting product, a CRM workflow, or a talent-movement analysis.

Read the API quickstart →

FAQs

  • What is a job-change signal?

    A job-change signal is a sign that a person may change jobs. Next Move Signal predicts a possible move, while a job-change alert reports one that has already happened.

  • How does Next Move Signal work?

    Next Move Signal scores job-change likelihood from profile-change patterns, not from self-reported status alone.

  • Does every person have a score?

    No. Next Move Signal returns a score only when the evidence is strong, so most people have none. Roughly one profile in nine carries one. No score is different from a low score.

  • What time frame does a score cover?

    Each score is based on the last 180 days of profile activity before that week's run date. It also comes with a signal date — the date the signal was detected, a weighted average of the change dates across those 180 days.

  • How should I read a score?

    Scores run from 0.5 to 1 (think 50% to 100%), and a higher score means a move is more likely. A score of 1 means there is explicit evidence the person is ready for their next move — for example, profile text saying they are open to new opportunities. A score between 0.5 and 1, such as 0.7, means the person made profile changes that are 70% similar to people we know are looking for work in their country.