A range estimated by company, title and seniority, with the confidence level stated. It feeds the acceptance prediction and blocks an unrealistic salary back at the definition of the role.
You find out the salary expectation in the third conversation, after investing hours. Or worse: you find out in the offer that gets turned down, when both sides have already built expectations.
The estimate appears in the assessment, before the first contact. If the person probably earns above the role’s ceiling, you know that when deciding whether to reach out, and with what argument.
The model’s market knowledge, your organization’s own base that grows with every use, web research, and what you correct by hand. The result comes with a confidence level and the factors that weighed on it.
Your own base decays over time: data from two years ago weighs less than data from last month.
monthly · estimated, CLT contract
range published in the JD
A market estimate, not something the candidate declared. It crosses your own organization’s history with intelligence by title, company and seniority. It is never exposed in outreach.
When the role’s range falls below the local market, EVO opens a challenge during the definition of the description, with the number and the practical consequence of insisting.
It is the same data serving twice: to calibrate the expectation about the candidate and to question the expectation of the company.
Of the responsibilities we captured, six are people leadership: defining what each analyst works on, running development plans and 1:1s, and owning the team’s capacity.
The practical consequence: you will attract a strong IC who turns down the management part, or a manager who accepts and then asks for the title back. Both scenarios cost you a cycle.
Reclassify as Team Leader and keep the scope. The range goes up ~25%: salary intel estimates R$ 18–24k for a Discovery TL in São Paulo, against R$ 14–19k for a senior specialist.
"I want your confirmation on both blockers before I write. I am not drafting this with the wrong seniority."
Salary data is the kind of number that gains undue authority once it appears on a screen. These are the caveats built in.
A score across four dimensions with text for each one, a read of the career, strengths, concerns and gaps, plus the odds of acceptance.
See inside →RealismFeasibility reportThe salary asked against the market, funnel reach per requirement and the risks being taken, versioned at every negotiation.
See inside →OutreachOutreach with approvalInvitation, message or InMail in your voice, citing something real from the career, sent from your account, after your approval.
See inside →It takes a real role to see EVO work, not a canned example.
Start using it