Overview

The AI Interviewer Dashboard tracks the full lifecycle of AI-conducted interviews — invitations, completions, feedback generation and review, candidate experience, and downstream hiring outcomes — along with credit purchase and consumption for your AI Interviewer plan.

Metrics

AI Interview Invites Sent

Definition: AI Interview Invites Sent represents the total number of interview invitations distributed through the AI Interviewer platform within the selected time period. This metric is a key indicator of usage volume, product adoption, and expected credit consumption — tracking invitation volume lets organizations gauge the scale of AI Interviewer deployment and recruiter engagement with the tool. A consistent increase in invites sent typically reflects growing confidence in AI Interviewer as a standard part of the candidate screening and assessment workflow.

How it is calculated: Counts invitations sent to candidates.

Note:

• Filtered by invitation sent date.

AI Interviews Completed

Definition: AI Interviews Completed measures the total number of AI interviews successfully completed by candidates within the selected date range. This helps TA teams track completion volume, understand candidate engagement with the AI interview process, and measure throughput of completed interviews feeding into feedback generation and review.

How it is calculated: Counts interviews with a recorded completion event.

Note:

• Filtered by completion date. Only interviews with a recorded invitation are counted, and interviews missing a valid entry for a preceding stage (invitation sent, call started) are excluded from the count — this is a change from filtering by invitation sent date.

Average Interview Time

Definition: Average Interview Time represents the mean duration (in minutes) of all completed AI interviews.

How it is calculated: Averages the time from call start to interview completion, across all completed interviews.

Note:

• Only completed interviews with a valid duration are included. Filtered by completion date.

Interview Completion Rate (%)

Definition: Interview Completion Rate (%) measures the percentage of AI interview invitations sent within the selected date range that resulted in interview completion within that same period. This helps TA teams understand interview attendance and completion during a specific timeframe and identify bottlenecks where candidates drop off after receiving an invitation.

How it is calculated: Divides completed interviews by invited interviews.

Note:

• Measures period-specific completion performance rather than cohort-based tracking: both the invitation-sent event and the completion event must fall within the selected date range. An invitation sent before the period but completed during it is excluded, and a completion that occurred before the period is excluded. This is a change from the previous cohort-style filtering (filtered only by invitation sent date, regardless of when completion happened).

Feedback Generation Rate (%)

Definition: Feedback Generation Rate measures the percentage of completed AI interviews that resulted in successfully generated feedback within the selected date range. This monitors the reliability and coverage of the AI evaluation process, ensuring recruiters have the data they need for candidate assessment. Knockout cases are excluded — a knockout question (e.g. visa eligibility) can trigger automatic rejection with feedback generated mid-interview, so those candidates never reach the "Interview Completed" stage and are excluded from both the numerator and denominator.

How it is calculated: Divides completed interviews that also produced generated feedback by all completed interviews.

Note:

• Both the completion event and the feedback-generation event must fall within the selected date range for an interview to count. This is a change from the previous filtering, which used the completion date only.

Feedback Turnaround Time

Definition: Feedback Turnaround Time measures the average duration (in minutes) between interview completion and AI feedback generation.

How it is calculated: Averages the time between interview completion and feedback generation, across interviews where feedback was generated.

Note:

• Filtered by completion date.

Interview Count by Feedback Time Bucket

Definition: Interview Count by Feedback Time Bucket categorizes completed interviews by how long feedback took to generate. Buckets: Within 5 mins, 5–15 mins, 15–30 mins, 30–60 mins, 1–4 hours, 4+ hours.

How it is calculated: Counts interviews per feedback-turnaround-time bucket.

Note:

• Only interviews with feedback generated are included. Filtered by completion date.

Completion Rate by Interview Type

Definition: Completion Rate by Interview Type shows the percentage of candidates who finish their AI interview, segmented by interview type (Screening, Coding, Functional/Behavioural, Modular, Other). Comparing completion rates across interview types helps teams optimize scheduling, communication, and technical setup for formats seeing lower completion, and target improvements to maximize engagement for each interview modality.

How it is calculated: Divides completed interviews by invited interviews, per interview type.

Note:

• Filtered by event date: both the invitation-sent and interview-completion timestamps must fall within the selected date range. This is a change from the previous filtering by invitation sent date alone.
• Interview type now includes a "Modular" category, in addition to Screening, Coding, Functional/Behavioural, and Other.

Average Interview Time by Type

Definition: Average Interview Time by Type shows the average duration (in minutes) of completed interviews, broken down by interview type.

How it is calculated: Averages interview duration per interview type.

Note:

• Only completed interviews included. Filtered by completion date.

Candidate Survey (%)

Definition: Candidate Survey measures the proportion of candidates who submitted a post-interview rating after finishing their session.

How it is calculated: Divides completed interviews with a survey rating by all completed interviews.

Note:

• Filtered by completion date.

Candidate Satisfaction Score

Definition: Candidate Satisfaction Score is the average rating (1–5 scale) provided by candidates about their AI interview experience.

How it is calculated: Averages the survey rating across all rated sessions.

Note:

• Only candidates who provided a rating are included. Filtered by completion date.

AI Interview - Active Positions

Definition: AI Interview - Active Positions measures the proportion of job positions where AI Interviewer is actively configured.

How it is calculated: Divides positions with at least one AI interview session by the total count of positions.

Note:

• No date filter — reflects the current snapshot. Denominator includes all positions, not just open ones.
• This metric was previously displayed as "AI Enabled Positions" — same definition and calculation, updated display name.

Time to Screen using AII

Definition: Time to Screen using AII measures the average time (in days) from when the candidate is invited for the AI interview to when they complete it. Only Screening AI interviews are considered.

How it is calculated: Averages the days between invitation and completion, for Screening-type interviews only.

Note:

• Filtered by completion date.

Time to Fill using AII

Definition: Time to Fill using AII measures the average of median days from position creation to hire for AI-enabled positions.

How it is calculated: For each AI-enabled position, the median time-to-fill is computed, then averaged across all such positions.

Note:

• Only positions with at least one hire are included. The two-step median-then-average approach reduces the impact of outlier positions. Filtered by hire date.

Time to Hire using AII

Definition: Time to Hire using AII measures the average days from application submission to hire for candidates screened using AI Interview.

How it is calculated: Averages the days between application and hire, for hired candidates who went through an AI interview.

Note:

• Filtered by hire date.

Feedback Review Rate (%)

Definition: Feedback Review Rate (%) measures the percentage of AI-generated feedback reports that have been opened and reviewed by recruiters within the selected date range. This is a key indicator of recruiter engagement, confirming that AI-generated insights are actually being used in hiring decisions rather than accumulating unread. A low review rate may suggest recruiters are overwhelmed, that feedback delivery isn't well-integrated into their workflow, or that feedback is accumulating faster than review capacity.

How it is calculated: Divides feedback reports marked as reviewed by all generated feedback reports.

Note:

• Both the feedback-generation event and the feedback-review event must fall within the selected date range. This is a change from the previous filtering, which used the feedback generation date only.

Feedback Review Time

Definition: Feedback Review Time measures the average days a recruiter takes to review AI-generated feedback after it becomes available.

How it is calculated: Averages the time between feedback generation and feedback review.

Note:

• Filtered by feedback review date.

Pending Feedback Reviews

Definition: Pending Feedback Reviews counts interviews where AI feedback has been generated but not yet reviewed by a recruiter.

How it is calculated: Counts interviews with generated feedback that hasn't been marked as reviewed.

Note:

• Filtered by feedback generation date. Also available as a monthly trend (Trend in Pending Feedback Reviews).

Trend in Pending Feedback Reviews (New)

Definition: Trend in Pending Feedback Reviews shows the monthly trend of unreviewed AI feedback reports.

How it is calculated: Counts feedback reports not yet marked as reviewed, aggregated by the month feedback was generated.

Note:

• Filtered by feedback generation date.

Time to Action and Experience Metrics by Recruiter

Definition: A per-recruiter view of AI Interview activity, responsiveness, and candidate experience.

How it is calculated: For each recruiter: total sessions invited, interviews completed, average interview duration, average time to interview, average feedback review time, count of feedback reviewed, and average candidate satisfaction score.

Note:

• Unassigned recruiters are excluded. Filtered by invitation sent date. A parallel view exists broken down by sourcer (Time to Action and Experience Metrics by Sourcer).

Time to Action and Experience Metrics by Sourcer (New)

Definition: A per-sourcer view of AI Interview activity, responsiveness, and candidate experience. Mirrors the recruiter breakdown, grouped by sourcer instead.

How it is calculated: For each sourcer: total sessions invited, interviews completed, average interview duration, average time to interview, average feedback review time, count of feedback reviewed, and average candidate satisfaction score.

Note:

• Unassigned sourcers are excluded. Filtered by invitation sent date.

Most Prolific Recruiters Using AI

Definition: Most Prolific Recruiters Using AI provides a ranked breakdown of recruiter activity across unique applications that were sent at least one AI interview invite within the selected date range. Each row represents a recruiter's contribution to the hiring funnel, from invite through hire. Comparing Completion Rate, Review Rate, and Hire Rate across recruiters helps talent acquisition leads identify top adopters, share best practices, and spot team members who might benefit from additional support.

How it is calculated: For each recruiter, across distinct candidate-position combinations: invites sent, interviews completed, feedback reviewed, offers extended, hires, plus completion rate, review rate, and hire rate as percentages, and total positions worked.

Note:

• Unassigned recruiters are excluded. Offer and hire data is sourced from your applications data. A parallel view exists broken down by sourcer (Most Prolific Sourcers Using AI).
• Hire Rate (%) reflects conversion from offer to hire, not from invite to hire.
• An invitation sent before the selected period is still included if a subsequent stage event (completion, review, offer, hire) occurs within the period. This is a change from the previous filtering by invitation sent date alone.

Most Prolific Sourcers Using AI (New)

Definition: Most Prolific Sourcers Using AI provides a ranked breakdown of sourcer activity across unique applications that were sent at least one AI interview invite within the selected date range. Each row represents a sourcer's contribution to the hiring funnel, from invite through hire. Comparing Completion Rate, Review Rate, and Hire Rate across sourcers helps talent acquisition leads identify top adopters, share best practices, and spot team members who might benefit from additional support.

How it is calculated: For each sourcer, across distinct candidate-position combinations: invites sent, interviews completed, feedback reviewed, offers extended, hires, plus completion rate, review rate, and hire rate as percentages, and total positions worked.

Note:

• Unassigned sourcers are excluded. Offer and hire data is sourced from your applications data.
• Hire Rate (%) reflects conversion from offer to hire, not from invite to hire.
• An invitation sent before the selected period is still included if a subsequent stage event (completion, review, offer, hire) occurs within the period. This is a change from the previous filtering by invitation sent date alone.

Overdue Interviews

Definition: Overdue Interviews counts AI Interview invites that expired without the candidate completing the interview.

How it is calculated: Counts invited interviews where the invitation link expired before completion.

Note:

• Only sent invites are included. Filtered by invitation sent date.

Interviews with Retry/Rejoin

Definition: Interviews with Retry/Rejoin counts completed AI Interviews where the candidate had at least one retry or rejoin attempt.

How it is calculated: Counts completed interviews with more than one call session recorded.

Note:

• Filtered by completion date.

Retry/Rejoin Rate (%)

Definition: Retry/Rejoin Rate measures the percentage of completed AI Interviews that involved at least one retry or rejoin attempt.

How it is calculated: Divides completed interviews with more than one call session by all completed interviews.

Note:

• Filtered by completion date.

Completion Rate Post Retry

Definition: Completion Rate Post Retry measures the percentage of interviews completed after at least one retry/rejoin.

How it is calculated: Divides interviews that had a retry/rejoin and were still completed, by all interviews that had a retry/rejoin.

Human Assistance Requested

Definition: Human Assistance Requested counts interview sessions where candidates triggered a request for help.

How it is calculated: Counts interview sessions with a recorded assistance-request event.

Note:

• Filtered by invitation sent date. High counts may indicate unclear instructions or technical issues.

Interviews with Call Initiation Error

Definition: Interviews with Call Initiation Error counts interviews where candidates could not successfully connect.

How it is calculated: Counts interviews where a call was initiated but never actually started.

Note:

• Filtered by call-initiated date.

Candidate NPS - AI Interviews

Definition: Candidate NPS measures how likely candidates are to recommend the AI Interview experience. NPS = (Promoters − Detractors) / Total Respondents × 100. Promoters = rating of 5, Detractors = rating of 3 or below.

How it is calculated: Subtracts the count of detractors (rating ≤3) from the count of promoters (rating 5), divided by all respondents, times 100.

Note:

• NPS ranges from -100 to +100. Only candidates who provided a rating are included. Filtered by completion date.

Low Satisfaction Scores

Definition: Low Satisfaction Scores counts AI Interviews where the candidate gave a survey rating below 3.

How it is calculated: Counts rated interviews with a survey rating under 3.

Note:

• Only rated sessions are included. Filtered by completion date. Also available broken down by interview type (Low Satisfaction by Interview Type).

Low Satisfaction by Interview Type (New)

Definition: Low Satisfaction by Interview Type shows the count of interviews with a rating below 3, broken down by interview type.

How it is calculated: Counts rated interviews with a survey rating under 3, grouped by interview type.

Note:

• Only rated sessions are included. Filtered by completion date.

Average Match Score- AII Hires

Definition: Average Match Score of hired candidates who were interviewed through AI Interviewer. Assesses the quality of candidate-position fit for AI-screened hires.

How it is calculated: Averages the match score for hired candidates who went through an AI interview.

Note:

• Only hired candidates who went through AI Interview are included. Filtered by hire date.

AI Recruitment Funnel

Definition: AI Recruitment Funnel visualizes the end-to-end candidate journey from the initial AI interview invitation through to hire within the selected date range. Stages: Invite Sent → Interview Completed → Recruiter Reviewed → Offer Extended → Hired. This is useful for identifying drop-off points across the full recruitment lifecycle — where candidates disengage, where review bottlenecks occur, and how effectively the AI interview process converts to downstream hiring outcomes.

How it is calculated: Counts distinct candidate-position combinations reaching each stage.

Note:

• Only entries where the previous stage's timestamp exists are included.
• This is a period-based view: a candidate invited before the selected period is still counted if their subsequent stage event (completion, review, offer, hire) occurs within the period. This is a change from the previous filtering by invitation sent date alone.

AI Interview Funnel (New)

Definition: AI Interview Funnel visualizes the candidate journey through the technical stages of the AI interview process — Invited → Call Started → Completed → Feedback Generated → Feedback Reviewed → Human Assistance Requested. It's useful for pinpointing exactly where candidates disengage or where technical friction occurs during the interview itself — a different, narrower lens than the AI Recruitment Funnel's hiring-outcome stages. Including Human Assistance Requested as a final stage lets teams see the volume of support needs relative to the entire candidate flow.

How it is calculated: Counts distinct candidates reaching each stage.

Note:

• Only entries where the previous stage's timestamp exists are included. Candidates invited before the selected period are still counted if a later stage occurs within it.

Hire Rate % - AII (New)

Definition: Hire Rate % - AII measures the percentage of candidates who completed at least one AI interview and were subsequently hired within the selected date range. This helps TA teams understand the conversion effectiveness of the AI interview process from completion to hiring outcome. A high hire rate indicates candidates completing AI interviews are strong candidates who progress successfully through the rest of the hiring process; a low rate may suggest AI interview quality, feedback utilization, or downstream hiring process efficiency needs attention.

How it is calculated: Divides hired candidate-position combinations by completed-interview candidate-position combinations.

Note:

• Only candidates who fully completed the AI interview are included in the denominator — partial or incomplete sessions are excluded.
• Both the completion event and the hire event must fall within the selected date range.

Weekly Trend in Invites Sent (New)

Definition: Weekly Trend in Invites Sent visualizes the volume of AI interview invitations sent each week, helping TA teams track recruiter outreach activity, identify staffing fluctuations, and measure invitation capacity over time. Monitoring weekly trends lets teams assess whether outreach is consistent, spot seasonal dips or peaks in sourcing activity, and correlate changes in invitation volume with recruitment campaigns or staffing adjustments.

How it is calculated: Sums invitations sent per calendar week, based on invitation date.

Note:

• Can be broken down by interview type or recruiter.

Weekly Trend in Interviews Completed (New)

Definition: Weekly Trend in Interviews Completed visualizes the volume of AI interviews completed each week, helping TA teams track completion activity, identify engagement patterns, and measure candidate participation rates over time. This provides insight into weekly completion velocity and downstream hiring progression.

How it is calculated: Sums completed interviews per calendar week, based on completion date, limited to interviews with a recorded invitation.

Note:

• Can be broken down by interview type or recruiter.
• Interviews without a valid entry for a preceding stage (invitation sent, call started) are excluded from the count.

Monthly Trend in Interviews Completed (New)

Definition: Monthly Trend in Interviews Completed visualizes the volume of AI interviews completed each month, helping TA teams track completion activity over longer time horizons, identify engagement patterns, and spot seasonal patterns in candidate participation and downstream hiring progression.

How it is calculated: Sums completed interviews per calendar month, based on completion date, limited to interviews with a recorded invitation.

Note:

• Can be broken down by interview type or recruiter.
• Interviews without a valid entry for a preceding stage (invitation sent, call started) are excluded from the count.

Plans Purchased Data

Definition: Plans Purchased Data shows a row-level breakdown of all AI Interviewer credit plans purchased by the customer, including plan details such as opportunity name, product type, purchase date, plan start and end dates, and total credits allocated per plan. This table provides full transparency into the customer's credit purchase history and is useful for auditing plan configurations, verifying contract details, and understanding how total purchased credits are distributed across multiple plans.

How it is calculated: Displays each purchased plan as its own row, along with its total credit allocation.

Note:

• Each row represents one purchased credit plan — no aggregation across plans. No date filter — shows all purchased plans.

AI Interview Credits Used - All Time

Definition: AI Interview Credits Used - All Time shows the cumulative total consumption of interview credits from the start of AI Interview usage through today. This metric provides a snapshot of overall credit utilization and is essential for budget tracking and resource planning. By tracking cumulative credit consumption alongside interview types and recruiters, hiring teams can monitor total usage against allocated budgets, identify high-volume departments, and forecast future credit requirements.

How it is calculated: Sums credits used across all interview sessions to date.

Note:

• No date filter — reflects all-time cumulative usage. Can be broken down by interview type or recruiter.

Total Credits Purchased

Definition: Total Credits Purchased shows the total number of AI Interviewer credits purchased by the customer across all plans, past, present, and future (including plans whose start date has not yet arrived). This metric provides a static snapshot of the overall credit budget allocated and is essential for understanding total capacity and planning against usage. By tracking total purchased credits alongside credits used and current balance, hiring teams can monitor overall budget allocation, assess how much capacity has been consumed, and plan future purchases.

How it is calculated: Sums the total credits across all purchased plans, regardless of plan dates.

Note:

• No date filter — includes past, present, and future-dated plans. No breakdowns available.

Total Credit Consumption %

Definition: Total Credit Consumption % shows the percentage of total purchased AI Interviewer credits that have been consumed through completed interviews. This metric provides a quick view of how much of the allocated budget has been utilised and is essential for tracking credit efficiency and forecasting remaining capacity. By monitoring consumption percentage alongside total credits purchased and credits used, hiring teams can assess budget burn rate, identify periods of high utilisation, and take proactive action to purchase additional credits before capacity runs out.

How it is calculated: Divides all-time credits used by total credits purchased.

Note:

• No date filter — reflects all-time consumption against the total purchased. A value of 100% indicates full consumption of the purchased budget.

Weekly Trend in Credit Consumption

Definition: Weekly Trend in Credit Consumption shows the total AI Interviewer credits consumed each week through completed interviews. This metric helps hiring teams track usage patterns over time and identify weeks with unusually high or low credit consumption. By monitoring weekly credit consumption alongside interview volume and interview type, teams can correlate hiring activity spikes with credit burn, plan budget replenishments proactively, and ensure credits are not exhausted during peak hiring periods.

How it is calculated: Sums credits used per calendar week, based on interview completion date.

Note:

• Each week is represented by its Monday start date. To see a complete week, set the filter's start date to a Monday — mid-week filtering shows only partial-week consumption. Can be broken down by interview type.

Monthly Trend in Credit Consumption

Definition: Monthly Trend in Credit Consumption shows the total AI Interviewer credits consumed each month through completed interviews. This metric helps hiring teams track usage patterns over time and identify months with unusually high or low credit consumption. By monitoring monthly credit consumption alongside interview volume and interview type, teams can correlate hiring activity spikes with credit burn, plan budget replenishments proactively, and ensure credits are not exhausted during peak hiring periods.

How it is calculated: Sums credits used per calendar month, based on interview completion date.

Note:

• Can be broken down by interview type.