50+ KPI Examples for Every Department (with Formulas)

This is a working library of KPI examples, organized by department. Each entry includes a one-line definition, the formula, the typical review cadence, and a short note on what it tells you. Pick the ones that match your business model; resist the temptation to adopt all of them. A team with five well-chosen KPIs will outperform a team with twenty mediocre ones, every time. The right KPIs for you depend on your stage, your priorities, and your operating model.

A note on benchmarks: industry benchmarks for these KPIs vary widely by company size, sector, and market. Treat any benchmark figure as directional, not authoritative. The most reliable comparison is your own historical baseline. If your win rate was 22 percent last year and is 28 percent this year, that is a meaningful signal regardless of what "the industry" averages. Build the discipline of measuring against yourself first.

Quota attainment: percentage of reps hitting their assigned quota in a given period. Formula: (reps at or above quota / total reps) × 100. Reviewed monthly. Tells you whether quotas are realistic and whether the team is performing against its capacity plan. Win rate: deals won divided by qualified deals reaching late-stage. Formula: (deals won / qualified deals closed-won-or-lost) × 100. Reviewed monthly. Tells you about pipeline quality and competitive positioning.

Average deal size: total closed-won revenue divided by deals closed. Sales cycle length: average days from opportunity created to closed-won. Pipeline coverage ratio: open pipeline divided by remaining quota; healthy ratio is typically 3-4×. Customer acquisition cost (CAC): total sales and marketing spend divided by new customers acquired. Lead-to-opportunity conversion rate: opportunities created divided by leads accepted. These six KPIs together give you a complete picture of sales efficiency, capacity, and pipeline health.

Marketing-qualified leads (MQLs): leads meeting predefined fit and intent criteria, typically reviewed monthly. Sales-qualified leads (SQLs): MQLs accepted by sales after qualification call, reviewed monthly. Cost per acquisition (CPA): paid spend divided by acquired customers from that channel. Pipeline contribution: percentage of new pipeline sourced or influenced by marketing. Organic traffic growth: month-over-month percentage change in organic sessions. Conversion rate by channel: visitors-to-MQL conversion broken down by traffic source.

Beyond top-of-funnel metrics, mature marketing teams track downstream impact: marketing-sourced revenue (revenue from accounts where marketing was the first touch), marketing-influenced revenue (revenue from accounts marketing touched at any stage), and brand search volume growth. The principle is to measure both efficiency (cost per lead, cost per customer) and effectiveness (revenue impact, pipeline quality). Efficiency without effectiveness leads to cheap leads that never convert; effectiveness without efficiency leads to unsustainable economics.

Net revenue retention (NRR): (starting MRR + expansions − churn − contractions) / starting MRR × 100. Reviewed monthly, target ≥ 110 percent for healthy SaaS. Gross retention: percentage of MRR retained excluding expansion. Customer health score: composite score combining product usage, support tickets, and engagement signals. Time-to-value: median days from signup to first meaningful product use. Customer satisfaction (CSAT): post-interaction survey, target ≥ 4.5 / 5.

Net Promoter Score (NPS): -100 to +100 scale based on the "would you recommend" question, reviewed quarterly. Product adoption depth: number of core features used by an account, indicating stickiness. Onboarding completion rate: percentage of new accounts completing the defined onboarding milestones within 30 days. Renewal rate: percentage of contracts up for renewal that successfully renewed. These KPIs together tell you whether customers are getting value, whether they are likely to stay, and whether the team is catching at-risk accounts early enough to save them.

Activation rate: percentage of new signups completing the defined activation event (varies by product). Daily active users (DAU) and monthly active users (MAU): unique users performing meaningful actions in the period. DAU/MAU ratio: stickiness measure, healthy products are 20+ percent. Feature adoption rate: percentage of active users using a specific feature, tracked per major feature. Time-to-value: same as customer success, but tracked per cohort to spot regressions.

Beyond engagement, product teams track quality and outcome: bug density (open bugs per active feature), customer-reported issues per release, percentage of roadmap shipped on schedule, and percentage of shipped features that hit their target adoption rate within 90 days. The last one is critical and often missed. Shipping fast does not matter if 60 percent of shipped features see no adoption. Tracking that ratio forces product teams to validate before building, not after.

The four DORA metrics, established by years of research, are the gold standard for engineering performance. Deployment frequency: how often code reaches production, target = on-demand (multiple times per day) for elite teams. Lead time for changes: median time from commit to production, target < 1 day. Change failure rate: percentage of deployments causing incidents, target < 15 percent. Mean time to recovery: median time to restore service after an incident, target < 1 hour.

Beyond DORA, valuable engineering KPIs include code review turnaround time (median hours from PR open to first review), test coverage on new code, percentage of incidents with documented root cause analysis, and on-call burden distribution (hours per engineer per month). The objective is to measure flow, quality, and team health together. Optimizing for deployment frequency while change failure rate climbs is a false win that catches up within a quarter.

Time-to-hire: median days from job posting to accepted offer. Offer acceptance rate: accepted offers divided by extended offers. Quality of hire: composite score combining first-year performance rating, retention through 12 months, and hiring-manager satisfaction at 90 days. Voluntary attrition rate: voluntary departures divided by average headcount, annualized. Engagement score: from quarterly engagement survey, on a defined scale. Internal mobility rate: percentage of role changes filled by internal candidates.

For performance management specifically: percentage of employees with active goals at quarter start, performance review completion rate (managers completing reviews on time), 1-on-1 cadence consistency (percentage of expected 1-on-1s actually held), and goal achievement rate (percentage of goals rated "met" or above at cycle end). These KPIs surface process health: whether the systems designed to develop and align people are actually being used. Most companies invest heavily in performance frameworks then never measure adoption, which is why 70 percent of performance management initiatives fail to deliver value.

Gross margin: (revenue − cost of goods sold) / revenue × 100. Reviewed monthly. Operating margin: operating income / revenue × 100. Cash runway: cash on hand divided by net monthly burn, expressed in months. Forecast accuracy: |actual − forecast| / forecast × 100, lower is better. Days sales outstanding (DSO): average days from invoice to payment received. Quick ratio (SaaS): (new MRR + expansion MRR) / (churned MRR + contraction MRR), healthy is 4× or higher.

For operations: order fulfillment time, inventory turnover, supply chain on-time delivery rate, and process cycle efficiency for the key operational workflows. The principle for finance and ops KPIs is the same as for everything else: pick the few that drive decisions, define them precisely, review them on the cadence at which someone can actually act, and pair them with guardrails. A finance team optimizing only for gross margin can starve the business of needed investment; a finance team that also tracks revenue growth and quick ratio sees the trade-off and makes balanced decisions.

From this catalog, most teams should pick five to seven KPIs per function and three to five at the company level. The company-level KPIs typically include one or two from each of: revenue (e.g., NRR, ARR growth), efficiency (e.g., CAC payback, gross margin), customer (e.g., NPS, gross retention), product (e.g., activation rate, DAU/MAU), and people (e.g., voluntary attrition, engagement). This portfolio gives leadership a balanced view of the business without overwhelming any individual review meeting.

Once you have your shortlist, the work shifts from selection to discipline: stable definitions, clean data, consistent review cadence, documented decisions, and follow-through on agreed actions. The KPIs themselves matter less than the operating rhythm around them. A team running KPILoop with five well-chosen KPIs and a religious monthly review will outperform a team with thirty KPIs in a spreadsheet and quarterly ad-hoc check-ins, every time. Choose carefully, define precisely, review consistently, and act on what you see.