Getting an AI score on a mock interview answer is only half the value — the other half is understanding why you got that score and what it would take to score higher. Until now, that second part took more digging than it should have.

The problem: feedback was there, but not always easy to navigate or interpret. Reviewing a specific answer meant moving through questions one by one, scores didn’t capture the fine differences between a good answer and a great one, and it wasn’t always clear what a given score actually meant or how to improve it.

Introducing the Updated Mock Interview Experience

This update makes AI feedback in Mock Interview easier to navigate, easier to interpret, and more accurate to what was actually said.

What’s new:

• Clickable question navigation — click directly on a question number to jump straight to its AI feedback, instead of moving through every question in sequence
• More granular scoring — scores now move in 0.5 increments from 1 to 5, with each level labelled from “Off Topic” to “Excellent,” so results reflect real differences in answer quality and are easier to read at a glance
• Rubric-based feedback — every scoring factor (Relevance, Clarity and Language, Depth of Insight, Confidence) comes with a rubric explaining what each score level means, so users can see exactly what separates their current score from the next one up
• More relevant AI feedback — comments are now better aligned with the actual content of each answer, so feedback speaks to what was really said, question by question and factor by factor

Why it matters

Feedback only helps if people can act on it. By making scores easier to navigate, easier to interpret, and more precisely tied to what a candidate actually said, this update turns Mock Interview feedback from “here’s your score” into “here’s what to do differently next time.”