How accurately can rediscovery software match old candidates to a new job?

Accuracy depends on how detailed your job requirements are and how the software evaluates candidates, but well-built rediscovery software scores matches based on verified skills, experience, and location rather than guessing from a job title alone. A detailed job description produces sharper, more reliable matches than a vague one.

Good matching software evaluates three core signals: skills evidence on the resume, years and relevance of experience, and location fit against the role. Each candidate gets a numeric score reflecting how closely they align with your specific requirements, not just whether their old job title sounds similar to the new one.

Software like Skima AI works this way. Every candidate card shows skills evidence found and not found directly on the application, so you see exactly which requirements a candidate meets and which they miss, rather than trusting a single opaque number. This transparency lets you verify accuracy yourself instead of trusting the score blindly.

You can also improve accuracy on your end. The more specific your job requirements, including exact skills, experience range, and location, the more precise the matching becomes. A vague job description like "looking for a marketer" returns broader, less reliable matches than one specifying "3 years of B2B content marketing experience with SEO and email campaign management."

If early results seem off, refine the job summary and requirements, then repeat the scan. Most candidate rediscovery tools, including Skima AI, let you edit criteria and search again instantly, so you can tighten accuracy without starting over from scratch.