Metrics worth tracking in Metabase

The share of deals that close won — by cohort, segment, and stage entered.

How long deals take to close, and why medians beat averages for a skewed distribution.

Open pipeline divided by the quota or target it has to cover in a period.

Stage-to-stage and overall funnel conversion — where deals advance and where they stall.

The typical value of a won deal (ACV), and how mix and outliers distort the mean.

The share of contacted prospects who reply to outbound — by sequence, rep, and segment.

Qualified meetings generated by outbound — booked vs. held, without double-counting.

How close the forecast came to actuals — why you need snapshots, and how to track bias.

The share of sent emails that fail to deliver — hard vs. soft, and protecting deliverability.

The normalized monthly value of active subscriptions — the base for churn, retention, and LTV.

Revenue vs. customer churn, and voluntary vs. involuntary — where recurring revenue leaks.

Expansion minus contraction and churn across your existing customers.

Average recurring revenue per user or account, and how it differs from ARPA.

The expected gross-margin value of a customer over their lifetime.

The share of payments that fail — the main driver of involuntary churn.

The four keys: deployment frequency, lead time for changes, change failure rate, and MTTR.

How often you ship to production — a DORA throughput metric.

Time from commit to running in production — a DORA throughput metric.

The share of deploys that cause a failure — a DORA stability metric.

How fast you recover from a failure in production — a DORA stability metric.

Time from work started to done — how fast issues move once picked up.

Time from request created to delivered — end-to-end issue flow.

How long customers wait for the first human reply — the median, not the average.

Time from ticket created to resolved, and whether to subtract pending time.

Customer satisfaction — positive ratings ÷ rated tickets, and why response rate matters.

Tickets created vs. solved per period, plus the open backlog behind them.

The typical revenue per order, and how mix and discounts move it.

The share of customers who buy again — the core signal of retention and loyalty.

How long a candidate takes from application or first touch to accepted offer.

How long an open requisition takes to reach an accepted offer or start.

Accepted offers divided by extended offers, with pending and rescinded offers separated.

Stage-to-stage recruiting funnel conversion from ATS stage history.

Which recruiting sources produce qualified candidates, offers, and accepted hires.

The share of candidates who advance after a completed interview stage.

Available operating cash divided by average monthly net burn, with restricted cash and FX handled explicitly.

Open invoice balances grouped by days past due at a specific as-of date.

The number of days of credit sales represented by average accounts receivable.

Gross operating cash outflow and net cash consumed after operating inflows.

Revenue remaining after direct cost of revenue, based on an approved account mapping.

Actual results compared with one approved budget version at a shared reporting grain.

Payments allocated to an invoice cohort divided by the value invoiced in that cohort.

Foreign-currency balances and commitments translated at a documented valuation rate.

Completed work divided by due or committed work in a period.

How much work is completed per period, by project, team, or work type.

Open work past due divided by open work with due dates.

How open work is distributed across owners, teams, projects, and statuses.

A transparent risk score for overdue, blocked, stale, and incomplete work.

The share of active content reviewed or meaningfully updated inside its policy window.

Required topics and workflows with current, owned documentation.

The share of eligible boards, spaces, sites, or channels with meaningful recent activity.

Time from a question or new thread to its first useful human reply.

Conversion value over ad spend, by campaign and channel — with the attribution caveats spelled out.

Spend over new customers — blended vs. paid-only, and the payback math that follows.

Spend over leads generated — raw vs. qualified, so cheap channels don't hide bad leads.

The price of attention per channel, with CPM alongside — and why cross-channel comparisons mislead.

Clicks over impressions or delivered emails — the denominator changes by context.

Conversions over sessions per landing page, with sample-size thresholds that keep rankings honest.

Search visibility from Search Console rows — branded vs. non-branded, position, and CTR together.

Signups reaching the product's value moment — the bridge between marketing spend and retention.

Qualifying incidents per period, segmented by severity and service.

How fast a responder picks up an incident — the paging-health half of response.

Failed events over total requests, sessions, or users — per service and release.

The share of alerts that never became incidents — the alert-fatigue early warning.

Successful requests or minutes over total, per service — uptime, done per service.

Reliability against explicit targets — error budgets and burn rates.

Used capacity over requested or provisioned — the bridge between reliability and cost.