Leadership-grade hiring metrics across your whole company.
Why it exists Reports hiring performance to management with real numbers.
Recruiting is chronically under-measured, which is why it is so often argued about with anecdotes — "hiring is slow", "the candidates are bad" — that nobody can confirm or refute. This dashboard converts your day-to-day pipeline activity into the metrics leadership actually asks for: how long a hire takes, how many offers are accepted, how many roles are open. It is also the strongest argument for keeping statuses current, since every number here is derived from status history. Garbage pipeline discipline produces garbage board slides.
How to use it
Click "Analytics" in the top navigation bar.
Select a period: 90 days, 6 months, 12 months or All time.
Read the top KPI cards: Avg. Time to Hire, Avg. Time to Offer, Offer Acceptance Rate, Hires in Period, Open Positions, Total Applications.
Scroll through the charts described below.
Requires the Administrator, Recruiter, Hiring Manager or Read Only role.
Good to know
Requires the Administrator, Recruiter, Hiring Manager or Read Only role — Interviewers do not have access.
Every figure derives from application status history, so accuracy depends entirely on keeping statuses up to date.
Short periods on a low-hire month produce volatile averages; use 6 or 12 months for anything you plan to present.
Offer Acceptance Rate is the single most diagnostic number here — a falling rate usually points at compensation or process speed.
Shows how candidates move from interview loop to offer.
Why it exists Reveals which stage loses the most candidates.
Every hiring process leaks, and the useful question is where. A funnel answers it in a way that raw counts cannot, because it shows both the share of the original applicant pool and the drop from the immediately preceding stage — which distinguishes a genuinely selective step from a bottleneck. Each pattern implies a different fix: heavy loss at first review usually means your posting is attracting the wrong people, while loss late in the process points at interview experience, speed or compensation.
How to use it
Open the Analytics page.
Scroll to "Pipeline Conversion Funnel".
Read each stage's share "of applied" and "from previous stage".
Identify the stage with the biggest drop-off.
Change the period selector to compare across time ranges.
Good to know
"From previous stage" is the more actionable of the two percentages — it isolates where the loss actually happens.
Early-stage loss is usually a sourcing or job-description problem; late-stage loss is a process or offer problem.
Custom statuses are placed in the funnel according to the Category you assigned them, so a miscategorised stage distorts the picture.
Compare the same period year over year rather than against a different-length window.
Which channels produce applications versus actual hires.
Why it exists Directs sourcing budget to the channels that convert.
Recruitment spend is usually allocated by habit and by whoever sells hardest, not by evidence. This report separates the two numbers that matter and are constantly confused: volume and conversion. A board that sends five hundred applications and no hires is costing you screening time, while one that sends twelve applications and two hires is the best investment you have. Seeing them side by side is what turns "we always post there" into a defensible budget decision — and it only works if you actually publish to multiple channels.
How to use it
Open the Analytics page.
Scroll to "Source of Hire" to see where hires came from.
Scroll to "Source Effectiveness" for the Source / Applications / Hires / Conversion table.
Compare high-volume channels against high-conversion ones.
Reallocate spend toward the best converters.
Good to know
Volume and conversion are different questions. Optimise for conversion unless you are short of applicants entirely.
Attribution depends on candidates arriving through the correct application URL, so use the per-portal URLs from "Post on Any Portal".
Manually added candidates and referrals only appear correctly if they were entered in Canvider rather than tracked by email.
Give a new channel a full hiring cycle before judging it — a channel with two applications has no meaningful conversion rate.
Categorised reasons candidates declined your offers.
Why it exists Shows whether compensation or process is losing candidates.
A declined offer is the most expensive failure in hiring — weeks of work by recruiters, interviewers and hiring managers, with nothing to show for it. Individually each decline feels like bad luck; in aggregate a pattern emerges, and the pattern is almost always fixable. If most declines cite compensation, your bands are out of date. If they cite a competing offer that arrived first, your process is too slow. This report only works if you record the reason at the time, which takes ten seconds and is the step most teams skip.
How to use it
Open the Analytics page.
Scroll to "Reasons for Offer Rejection" for the categorised breakdown.
Scroll to "Recent Rejection Notes" for the raw recruiter notes.
Record a note when a candidate declines so this stays accurate.
Good to know
The report is only as good as your notes — record the reason when the candidate tells you, not from memory later.
Read the raw notes as well as the categories; the specifics are usually where the actionable detail is.
Repeated compensation declines are evidence for a salary-band review, and this is the report to bring to that conversation.
"Accepted another offer" without more detail is worth probing at the time — it usually masks speed or compensation.
Monthly hires, cumulative headcount, and hires by department.
Why it exists Shows leadership where and how fast the org is growing.
These are the charts that belong in a board pack rather than a recruiter's daily work. They answer planning questions instead of operational ones: are we hiring at the rate the plan assumed, which functions are absorbing the growth, and is application volume trending with or against our needs. The department breakdown is usually the most revealing, because it makes visible when growth has quietly concentrated in one function — a pattern that is obvious in a chart and invisible in a list of individual hires.
How to use it
Open the Analytics page.
Review "Org Growth — Hires" for monthly and cumulative hires over 12 months.
Review "Application Volume" for monthly application counts.
Review "Hires by Department" to see which teams are growing.
Good to know
"Hires by Department" only works if jobs were assigned a department at creation — set them up in Settings first.
These charts count hires made through Canvider, not total company headcount.
Read hires and application volume together: rising hires on falling applications means your pipeline is tightening.
The 12-month view is designed for planning conversations rather than weekly management.
Average days per stage and where candidates sit now.
Why it exists Finds bottlenecks and supports pipeline planning.
These two panels answer the past and the present. Average days per stage is diagnostic — it tells you which step in your process consistently consumes time, which in most companies turns out to be waiting for hiring-manager feedback rather than anything candidates do. The snapshot is operational: it shows where people are sitting right now, and a pile-up in one stage is a queue that needs clearing today. Speed is not a vanity metric here; candidates in demand accept the first good offer, so time in stage converts directly into lost hires.
How to use it
Open the Analytics page.
Scroll to "Avg. Days per Stage" to see where candidates wait longest.
Scroll to "Current Pipeline Snapshot" for live candidate counts per stage.
Act on any stage with an unusually long wait.
Good to know
Long averages in a review stage almost always mean people are waiting on a human, not on information.
The snapshot is live; the averages are historical. Use the first for today's work and the second to fix the process.
Both are computed from status changes, so a pipeline that is updated late will understate your real delays.
Cross-check any suspicious stage against individual candidates' Journey timelines.
Download the full analytics dataset as an Excel workbook.
Why it exists Enables offline reporting and board-deck preparation.
Dashboards are for looking; spreadsheets are for arguing. The moment recruitment numbers enter a board pack or a budget conversation they need to be combined with data Canvider does not hold — finance's cost figures, headcount plan, agency invoices — and that work happens in Excel. Export also serves the archival need: a dashboard always shows current data, so if you want a defensible record of what the numbers were when a decision was made, you need a file with a date on it.
How to use it
Open the Analytics page.
Select the period you want to export.
Click "Export to Excel" in the header.
Save the downloaded .xlsx file.
Open it in Excel or Google Sheets.
Good to know
The export honours the period selector, so set it before exporting.
Export a fixed snapshot before any meeting where the numbers will be quoted — live dashboards move.
The workbook contains candidate and hiring data; store and share it with the same care as any HR file.
Useful for combining recruitment metrics with cost data that Canvider does not track.
Charts of applicants over time, portal and status for one job.
Why it exists Measures whether a single posting is performing.
Company-level analytics tell you how hiring is going overall; they cannot tell you that this particular role is in trouble. Per-job charts answer that while there is still time to act. The applicants-over-time curve is the one to read first — job postings naturally spike on publication and decay over the following weeks, so a flat line from the start means a distribution or description problem, while a decayed curve on an unfilled role means it is time to repost or source rather than keep waiting.
How to use it
Open the job's details page from the Jobs list.
Review "Applicants Over Time" for the application trend.
Review "Number of Applicants by Job Portal" to see which board works.
Review "Distribution of Applicants by Status" for pipeline health.
Review "Top Applicants" for the strongest candidates so far.
Good to know
A flat "Applicants Over Time" from day one points at distribution or the job description, not at the market.
Application volume decays naturally after publication — plan sourcing for week two or three rather than waiting.
"By Job Portal" is the per-job version of source effectiveness and is the fastest way to see which board earns its place for this kind of role.
"Top Applicants" ranks by AI score, so run analysis before treating it as a shortlist.