Analytics
KPI Examples: 100+ Key Performance Indicators by Department
Saad Selim
May 4, 2026
15 min read
A KPI (Key Performance Indicator) is a measurable value that demonstrates how effectively a company or team is achieving key business objectives. This reference guide provides KPI examples for every major business function, including formulas, benchmarks, and guidance on which ones matter most.
Sales KPIs
| KPI | Formula | Good Benchmark |
|---|---|---|
| Monthly Recurring Revenue (MRR) | Sum of all recurring subscription revenue | Growing month-over-month |
| Annual Recurring Revenue (ARR) | MRR x 12 | Growing year-over-year |
| Net Revenue Retention (NRR) | (Start MRR + Expansion - Contraction - Churn) / Start MRR | > 110% (best: > 130%) |
| Win Rate | Deals Won / Total Deals | 20-30% typical |
| Average Deal Size | Total Revenue / Number of Deals | Increasing trend |
| Sales Cycle Length | Average days from first contact to close | Industry-dependent |
| Pipeline Coverage | Pipeline Value / Revenue Target | 3-4x for healthy pipeline |
| Quota Attainment | Revenue Closed / Quota | > 80% for healthy team |
| Customer Acquisition Cost (CAC) | Total Sales + Marketing Cost / New Customers | LTV:CAC > 3:1 |
| Revenue Per Rep | Total Revenue / Number of Reps | Increasing trend |
| Activity Metrics | Calls, emails, meetings per rep per day | Team-specific |
| Lead Response Time | Time from lead creation to first contact | < 5 minutes ideal |
Marketing KPIs
| KPI | Formula | Good Benchmark |
|---|---|---|
| Marketing Qualified Leads (MQLs) | Leads meeting qualification criteria | Growing, quality maintained |
| Cost Per Lead (CPL) | Marketing Spend / Leads Generated | Channel-dependent |
| Cost Per Acquisition (CPA) | Marketing Spend / New Customers | < 1/3 of first-year revenue |
| Return on Ad Spend (ROAS) | Revenue from Ads / Ad Spend | > 3:1 for profitability |
| Website Traffic | Monthly unique visitors | Growing month-over-month |
| Conversion Rate | Conversions / Total Visitors | 2-5% for most websites |
| Email Open Rate | Opens / Emails Delivered | 20-30% (industry-dependent) |
| Email Click Rate | Clicks / Emails Delivered | 2-5% |
| Content Engagement | Time on page, pages per session | Increasing trend |
| Social Media Engagement Rate | (Likes + Comments + Shares) / Followers | 1-5% |
| Marketing Sourced Pipeline | Pipeline $ from marketing-generated leads | 40-60% of total pipeline |
| Brand Awareness | Survey-based recognition, search volume | Increasing trend |
Customer Success KPIs
| KPI | Formula | Good Benchmark |
|---|---|---|
| Customer Retention Rate | (Customers End - New) / Customers Start | > 90% annual (B2B SaaS) |
| Churn Rate (Revenue) | Lost MRR / Starting MRR | < 5% annual gross churn |
| Net Promoter Score (NPS) | % Promoters - % Detractors | > 40 is excellent |
| Customer Satisfaction (CSAT) | Satisfied Responses / Total Responses | > 80% |
| Customer Effort Score (CES) | Average ease rating | > 5/7 |
| Time to Value | Days from purchase to achieving first outcome | Decreasing trend |
| Expansion Revenue | Upsell + Cross-sell Revenue | > 20% of total revenue |
| Health Score | Composite of usage, engagement, satisfaction | Custom per business |
| Support Ticket Volume | Tickets per customer per month | Decreasing trend |
| First Contact Resolution | Tickets resolved on first interaction / Total | > 70% |
Finance KPIs
| KPI | Formula | Good Benchmark |
|---|---|---|
| Gross Margin | (Revenue - COGS) / Revenue | > 70% for SaaS, 30-50% for retail |
| Operating Margin | Operating Income / Revenue | Positive and improving |
| EBITDA Margin | EBITDA / Revenue | Industry-dependent |
| Burn Rate | Monthly cash outflow | Decreasing toward profitability |
| Cash Runway | Cash Balance / Monthly Burn | > 12 months |
| Rule of 40 | Revenue Growth Rate + Profit Margin | > 40% for SaaS |
| Revenue Per Employee | Total Revenue / Full-Time Employees | > $200K for SaaS |
| Days Sales Outstanding (DSO) | (Accounts Receivable / Revenue) x Days | < 45 days |
| Days Payable Outstanding (DPO) | (Accounts Payable / COGS) x Days | 30-60 days |
| Working Capital Ratio | Current Assets / Current Liabilities | 1.5-2.0 |
| Budget Variance | (Actual - Budget) / Budget | Within +/- 5% |
| Forecast Accuracy | 1 - ABS(Actual - Forecast) / Actual | > 90% |
Product KPIs
| KPI | Formula | Good Benchmark |
|---|---|---|
| Daily Active Users (DAU) | Users with at least one session per day | Growing |
| Monthly Active Users (MAU) | Users with at least one session per month | Growing |
| DAU/MAU Ratio (Stickiness) | DAU / MAU | > 20% good, > 50% excellent |
| Feature Adoption Rate | Users using feature / Total active users | Varies by feature |
| Activation Rate | Users completing key action / Total signups | > 40% |
| Time to Activation | Days from signup to key action completion | Decreasing trend |
| Session Duration | Average time per session | Context-dependent |
| Retention (Day 1, 7, 30) | Users returning on day N / Users who signed up | Day 1 > 40%, Day 30 > 15% |
| Error Rate | Errors / Total actions | < 1% |
| Page Load Time | Average time to interactive | < 3 seconds |
| Net Promoter Score (Product) | % Promoters - % Detractors | > 30 |
| Feature Request Volume | Feature requests per period | Track by category |
Engineering KPIs
| KPI | Formula | Good Benchmark |
|---|---|---|
| Deployment Frequency | Deploys per day/week | Multiple per day (elite) |
| Lead Time for Changes | Commit to production time | < 1 day (elite) |
| Change Failure Rate | Failed deploys / Total deploys | < 15% |
| Mean Time to Recovery (MTTR) | Average time from failure to resolution | < 1 hour (elite) |
| Sprint Velocity | Story points completed per sprint | Stable and predictable |
| Code Coverage | Lines tested / Total lines | > 80% |
| Technical Debt Ratio | Remediation cost / Development cost | < 5% |
| Bug Escape Rate | Bugs found in production / Total bugs | Decreasing |
| On-Call Pages | Pages per engineer per week | < 2 |
| Developer Satisfaction | Survey-based score | > 7/10 |
HR and People KPIs
| KPI | Formula | Good Benchmark |
|---|---|---|
| Employee Turnover Rate | Departures / Average Headcount | < 15% annual |
| Voluntary Turnover | Voluntary departures / Average headcount | < 10% annual |
| Time to Hire | Days from job posting to offer acceptance | < 30 days |
| Cost Per Hire | Total recruitment costs / Hires | $4,000-$7,000 average |
| Offer Acceptance Rate | Offers accepted / Offers extended | > 85% |
| Employee Engagement Score | Survey-based composite score | > 70% |
| eNPS | % Promoters - % Detractors (employee version) | > 20 |
| Training Hours Per Employee | Total training hours / Headcount | > 40 hours/year |
| Diversity Ratio | Underrepresented groups / Total headcount | Improving toward goals |
| Internal Mobility Rate | Internal fills / Total fills | > 20% |
| Absenteeism Rate | Absent days / Available workdays | < 3% |
| Revenue Per Employee | Total revenue / Headcount | Increasing |
Operations KPIs
| KPI | Formula | Good Benchmark |
|---|---|---|
| On-Time Delivery Rate | On-time deliveries / Total deliveries | > 95% |
| Order Accuracy | Correct orders / Total orders | > 99% |
| Cycle Time | Time from start to completion | Decreasing |
| Throughput | Units processed per time period | Increasing |
| Capacity Utilization | Actual output / Maximum possible output | 70-85% |
| First Pass Yield | Good units / Total units (no rework) | > 95% |
| Inventory Turnover | COGS / Average Inventory | Industry-dependent |
| Order Fulfillment Time | Time from order to delivery | Decreasing |
| Supplier Lead Time | Days from PO to receipt | Stable or decreasing |
| Cost Per Unit | Total operational cost / Units produced | Decreasing |
How to Choose the Right KPIs
The SMART Framework
Every KPI should be:
- Specific: Clearly defined, no ambiguity
- Measurable: Quantifiable with available data
- Actionable: Someone can influence the outcome
- Relevant: Connected to a business objective
- Time-bound: Measured over a specific period
The Rule of 5-7
Each team should track no more than 5-7 KPIs. More than that creates information overload and dilutes focus. Choose the vital few that most directly indicate whether you are achieving your objectives.
Leading vs. Lagging Indicators
| Type | Description | Example |
|---|---|---|
| Leading | Predicts future outcomes, actionable now | Pipeline coverage (predicts revenue) |
| Lagging | Confirms past outcomes, not immediately actionable | Revenue (result of past actions) |
Track both, but focus action on leading indicators (you can still change them).
Tracking KPIs Effectively
The best KPIs are useless without a system to track them:
- Automate collection. Manual KPI tracking degrades over time.
- Set targets. Every KPI needs a goal (otherwise, what is "good"?).
- Review regularly. Weekly for operational, monthly for strategic.
- Act on findings. If a KPI declines, someone must investigate and respond.
Platforms like Skopx connect to your data sources and let teams ask about any KPI in natural language ("What is our current NRR?" or "Show me sales cycle length by deal size for Q1") without pre-building dashboards for every possible metric.
Summary
KPIs are only valuable when they connect to decisions. Choose a small number of relevant indicators for each team, ensure they are measurable and actionable, pair them with targets, and review regularly. The goal is not to track more, it is to track what matters and act on what you find.
Saad Selim
The Skopx engineering and product team