patterns

Rejection pattern analysis detects funnel shifts, score-vs-outcome relationships, archetype performance, and recurring blockers across your tracked job applications. By parsing your application tracker data, it identifies what is driving negative outcomes and where your time is being wasted.

Funnel analytics reports from tracked job applications provide recommended score thresholds and specific changes to portal filtering and archetype targeting. By running a Node.js script against your local application data, you generate a dated markdown report for career-ops decision making.

Yes, Node.js is required to execute the analyze-patterns script that parses your local JSON application data. The analysis enforces a minimum data threshold to ensure sufficient tracked application records exist before generating reliable rejection pattern insights.

Yes, you can improve job targeting by analyzing score-vs-outcome relationships and archetype performance across your applications. The analysis recommends a specific score threshold and targeted changes to portal filtering and archetype focus to increase interview conversion.

The main limitation is the minimum data threshold enforcement, meaning insufficient tracked application records will prevent reliable rejection pattern analysis. Insights are also bounded by the quality and consistency of your local scoring context and JSON application tracker inputs.