Reading the Influencing Factors Breakdown in Seeker

Last updated: April 27, 2026

Every profile returned by Seeker includes an influencing factors breakdown — a table visible in the Mesh UI and available via the API. This breakdown tells you which factors drove the match score and how strongly, without requiring any data science knowledge to interpret.

How the breakdown works

Seeker identifies the single most powerful factor for a given match and automatically assigns it a normalised value of 5. Every other factor is then graded relative to that "winner." This means the values shown are always relative to each other, not absolute measurements.

Each factor shows both a strength and a direction:

  • Strength — Very Strong, Strong, Weak, Very Weak (mapped from values 1–5)

  • Direction — an upward arrow (↑) means the factor increased the score; a downward arrow (↓) means it reduced it

  • Unknown — the factor could not be evaluated, usually because the required data (e.g. year of birth or country) was not provided in the search

Worked example: Carol Ann Johnson vs Carl Johnson (score: 28)

The influencing factors for this match are: Exact names 5, Equivalent names 0, Inexact names 3, Years of birth 0, Countries 0, Unmatched names −2, Name rarity 2.

  • Exact names: 5 — the surname "Johnson" triggered an exact match, and as the strongest factor it anchors the scale at 5.

  • Inexact names: 3 — "Carol" and "Carl" are one letter apart, contributing a positive but weaker signal.

  • Unmatched names: −2 — the middle name "Ann" has no counterpart in the profile, reducing the score.

  • Name rarity: 2 — "Johnson" and "Carol/Carl" are both common names. This low rarity score dampens the overall confidence, which is why the score sits at 28 despite the exact surname match.

Key point: The influencing factor values cannot be added together to reproduce the match score. They show relative contribution only. Think of them like a credit score breakdown — you can see which factors helped and which hurt, but the numbers don't directly sum to the final figure.

What "Unknown" means in practice

If year of birth or country shows as Unknown, it means that data was either not provided in the search query or not present on the matched profile. Providing more data — especially year of birth and country — almost always improves score precision, particularly for common names.