KPI Library: 100+ Metrics for Marketing, Sales, Finance, and More

How to choose the right metrics for data-driven decisions across departments and industries

Key Performance Indicators (KPIs) translate business processes into measurable values. They show whether goals are being reached, where bottlenecks exist, and which actions are working. They also make it possible to compare performance with the market, identify trends, and optimize almost every area of the company using data.

The goal is not to collect and monitor as many metrics as possible. It is to choose the right ones, define them clearly, and use them consistently in day-to-day work. Depending on the objective, a single metric or a small set may be enough.

Prioritizing and focusing on the business areas with the greatest potential maximizes impact. Once the processes, decisions, and optimizations work there, the approach can be transferred to the next most important area.

That is exactly where many teams fail: too many metrics are tracked, too few are tied to concrete goals, and definitions vary across departments. The result is dashboards that are full, but not decision-relevant (see Build effective dashboards).

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This article is a structured reference: more than 100 metrics, organized by functional area and industry, each with a definition, formula, interpretation, and benchmark guidance. Use it as a starting point for selecting your core metrics, not as an invitation to measure everything at once.

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How to use this library

Before you dive into the tables, answer three questions:

1. Which business goals matter most right now?
2. Which decisions should metrics improve?
3. Who works with these metrics, and what does that person need to see at a glance?

Those answers determine which metrics you choose and how you embed them in dashboards and reports. A useful starting structure is goal → outcome metric → driver metric (see Develop a BI strategy).

The benchmarks in the following tables are reference values. They vary by industry, business model, region, and company stage. Use them as a starting point, not as an absolute benchmark.

Marketing and sales

Marketing and sales metrics measure customer acquisition, campaign efficiency, and sales process performance. The biggest levers usually do not sit in isolated metrics, but in how they work together: acquisition cost only becomes meaningful when it is evaluated against customer value.

Metric	Definition	Formula	Benchmark guidance
Customer Acquisition Cost (CAC)	Cost of acquiring a new customer	(Marketing + sales costs) / New customers	Target: < CLV / 3
Customer Lifetime Value (CLV)	Total revenue from a customer over the relationship	Avg. revenue per customer × Customer lifetime	Clearly higher than CAC
Conversion Rate	Share of visitors completing a target action	(Conversions / Visitors) × 100	E-commerce: 1–3%, B2B landing pages: 2–5%
Return on Ad Spend (ROAS)	Revenue per ad dollar spent	Revenue from advertising / Ad spend	> 4.0 is often strong
MQL-to-SQL Rate	Share of marketing qualified leads that become sales qualified	(SQLs / MQLs) × 100	10–30%, highly industry-dependent
Sales Velocity	Speed at which opportunities turn into revenue	(Opportunities × Avg. deal value × Win rate) / Avg. sales cycle in days	Higher = more efficient
Churn Rate (customers)	Share of customers lost in a period	(Lost customers / Customers at period start) × 100	B2B SaaS annually: < 5% (established), < 10% (growth)
Net Promoter Score (NPS)	Customers’ willingness to recommend	% Promoters − % Detractors	> 50 is strong
Cost per Lead (CPL)	Cost of generating one lead	Ad spend / Number of leads	Industry- and channel-dependent
Lead-to-Customer Rate	Share of leads that become paying customers	(Paying customers / Leads) × 100	Industry-dependent
Average Deal Size	Average value of a won deal	Total revenue / Number of won deals	Upward trend is positive
Win Rate	Share of opportunities that are won	Won deals / Total opportunities	20–50%, strongly segment-dependent
Sales Cycle Length	Average time from first contact to close	Sum of all sales cycles / Number of deals	Shorter = more efficient
Email Open Rate	Share of delivered emails that are opened	(Opened / Delivered emails) × 100	20–30%
Click-Through Rate (CTR)	Share of clicks relative to impressions	(Clicks / Impressions) × 100	Search: 3–5%, display: 0.5–1%
Customer Retention Rate	Share of customers retained over a period	((Customers at end − New customers) / Customers at start) × 100	Higher = better
Pipeline Value	Total value of all sales opportunities	Sum of all opportunity values	Should be 3x to 5x the revenue target
Quota Attainment	Target attainment of the sales team	Achieved revenue / Target revenue	100% is the target

Finance and controlling

Finance metrics show liquidity, profitability, and capital efficiency. They are indispensable for business steering because they translate operational decisions into financial consequences.

Metric	Definition	Formula	Benchmark guidance
Gross Profit Margin	Share of revenue after direct costs	(Revenue − Cost of goods sold) / Revenue	Industry-dependent
Net Profit Margin	Share of revenue after all costs	Net profit / Revenue	Industry-dependent
EBITDA	Earnings before interest, taxes, depreciation, and amortization	Net profit + Interest + Taxes + Depreciation + Amortization	Industry-dependent
Operating Cash Flow	Cash generated from ongoing operations	Cash from operating activities	Positive and growing
Burn Rate	Monthly net cash outflow	Monthly expenses − Monthly income	As low as feasible
Runway	Months of survival with current cash reserves	Cash reserves / Monthly burn rate	> 12 months
Days Sales Outstanding (DSO)	Average payment duration for receivables	(Receivables / Annual revenue) × 365	< 45 days
Return on Investment (ROI)	Return on an investment	(Profit − Investment) / Investment	Higher = better
Quick Ratio	Ability to cover short-term liabilities immediately	(Cash + Receivables) / Short-term liabilities	> 1.0
Debt-to-Equity Ratio	Relationship between debt and equity	Total liabilities / Equity	Industry-dependent; lower is often better
Working Capital	Capital available for day-to-day operations	Current assets − Short-term liabilities	Positive
Inventory Turnover	How often inventory is sold through	Cost of goods sold / Avg. inventory	Higher = more efficient
Revenue Growth Rate	Revenue growth versus the previous period	((Current revenue − Previous revenue) / Previous revenue) × 100	Industry-dependent
Contribution Margin	Product contribution toward covering fixed costs	Revenue − Variable costs	Positive
Break-Even Point (units)	Sales volume at which costs are covered	Fixed costs / Contribution margin per unit	As low as possible
Break-Even Point (revenue)	Revenue level at which costs are covered	Fixed costs / Contribution margin ratio	As low as possible
Cash Conversion Cycle (CCC)	Time until investments turn back into cash	DIO + DSO − DPO	Shorter = more efficient
Return on Assets (ROA)	Profitability relative to total assets	Net profit / Total assets	Higher = better

Human resources

HR metrics measure recruiting efficiency, employee retention, and workforce productivity. They become especially valuable when linked to business metrics, for example revenue per employee combined with turnover.

Metric	Definition	Formula	Benchmark guidance
Employee Turnover Rate	Share of employees leaving the company	(Departures / Avg. headcount) × 100	Industry-dependent
Time to Hire	Time from posting to signed contract	Sum of days / Number of hires	Shorter = better
Cost per Hire	Total cost of a new hire	Recruiting costs / New hires	Industry-dependent
Revenue per Employee	Revenue per full-time equivalent	Total revenue / FTE	Higher = more productive
Absenteeism Rate	Share of absence days relative to working days	(Absence days / Working days) × 100	< 3%
eNPS	Employee willingness to recommend the employer	% Promoters − % Detractors	> 30 is good, > 50 strong
Training ROI	Return on learning and development	(Productivity gain − Training costs) / Training costs	Positive
Employee Engagement Score	Result from employee surveys	Avg. score from surveys	Higher = better
Internal Promotion Rate	Share of internal promotions in all filled roles	Internal promotions / Total placements	Higher = better
Offer Acceptance Rate	Share of accepted job offers	Accepted offers / Extended offers	Higher = better
First-Year Turnover	Share of employees leaving within the first year	First-year departures / New hires	Lower = better onboarding
HR-to-Employee Ratio	HR employees per 100 staff members	HR employees / (Total employees / 100)	1–3 depending on industry

Operations and supply chain

Operations metrics cover the efficiency of order fulfillment, supply chains, and production. They matter most when cost, quality, and delivery reliability need to improve at the same time.

Metric	Definition	Formula	Benchmark guidance
Order Fulfillment Cycle Time	Time from order receipt to delivery	Delivery timestamp − Order timestamp	Shorter = better
Perfect Order Rate	Share of error-free orders	(Error-free orders / Total orders) × 100	> 95%
Capacity Utilization	Use of production capacity	(Actual output / Maximum output) × 100	80–90%
Inventory Accuracy	Match between physical and digital inventory	(Physical inventory / System inventory) × 100	> 99%
Out-of-Stock Rate	Share of unavailable items	(Unavailable items / Total items) × 100	As low as possible
First Pass Yield (FPY)	Share of defect-free products in the first pass	(Defect-free products / Total production) × 100	Higher = better
Overall Equipment Effectiveness (OEE)	Overall equipment effectiveness	Availability × Performance × Quality	> 85% is world-class
On-Time Delivery (OTD)	Share of orders delivered on time	(On-time orders / Total orders) × 100	> 95%
Mean Time Between Failures (MTBF)	Average time between two failures	Total operating time / Number of failures	Higher = more reliable
Mean Time to Repair (MTTR)	Average repair duration	Sum of repair times / Number of repairs	Shorter = better
Supplier Defect Rate	Share of defective parts from suppliers	(Defective parts / Total parts) × 100	As low as possible
Scrap Rate	Share of scrap in total production	(Scrap / Total production) × 100	As low as possible
Energy Consumption per Unit	Energy use per produced unit	Energy consumption / Produced units	Downward trend is positive
Safety Incident Rate	Workplace incidents per 100 employees	(Incidents / Employees) × 100	As low as possible

E-commerce and retail

In e-commerce, success is driven by basket size, checkout efficiency, and repeat purchase behavior. Metrics in this area depend heavily on traffic quality and product category.

Metric	Definition	Formula	Benchmark guidance
Average Order Value (AOV)	Average order value	Total revenue / Orders	Upward trend is positive
Cart Abandonment Rate	Share of abandoned carts	(Abandonments / Started carts) × 100	Around 70% is common; lower is good
Repeat Purchase Rate	Share of customers buying again	(Customers with > 1 order / Total customers) × 100	Higher = more loyal
Revenue per Visitor (RPV)	Revenue per site visitor	Total revenue / Visitors	Higher = more efficient
Product Return Rate	Return rate	(Returns / Sales) × 100	Fashion: 30–50%, electronics: 5–10%
Add-to-Cart Rate	Share of visitors adding a product to cart	(Added to cart / Product views) × 100	Higher = stronger product interest
Bounce Rate	Share of visitors viewing only one page	(Single-page visits / Total visits) × 100	Lower = more relevant content
Mobile Conversion Rate	Conversion rate on mobile devices	(Mobile conversions / Mobile visitors) × 100	Typically below desktop rate
Gross Merchandise Value (GMV)	Total transaction value before deductions	Sum of all transactions	Higher = more volume
Net Sales	Revenue minus returns and discounts	Gross revenue − Returns − Discounts	Growing
Inventory-to-Sales Ratio	Relationship between inventory and sales	Inventory value / Sales value	Industry-dependent; lower is often more efficient
Customer Acquisition Cost (E-commerce)	Cost per acquired online customer	Online ad spend / New online customers	Industry-dependent

SaaS and subscription

In SaaS, the core metrics revolve around recurring revenue, customer retention, and growth efficiency. Metrics in this area are often more standardized than in other industries because investors and benchmarks create clearer expectations.

Metric	Definition	Formula	Benchmark guidance
Monthly Recurring Revenue (MRR)	Recurring monthly revenue	Sum of all monthly subscriptions	Growing
Annual Recurring Revenue (ARR)	Recurring annual revenue	MRR × 12	Growing
MRR Churn Rate	Share of MRR lost per month	Lost MRR / MRR at month start	< 2% monthly (established), < 5% (growth)
Net Revenue Retention (NRR)	Revenue from existing customers including expansion and contraction	(Start MRR + Expansion − Contraction − Churn) / Start MRR	> 100% is good, > 120% strong
LTV:CAC Ratio	Customer value relative to acquisition cost	CLV / CAC	> 3.0
CAC Payback Period	Months until CAC is recovered through contribution margin	CAC / (ARPU × Gross margin)	< 12 months
Average Revenue Per User (ARPU)	Average revenue per user	Total revenue / Users	Growing
Expansion MRR	Additional MRR from upselling and cross-selling	MRR from upgrades − MRR from downgrades	Positive and growing
DAU/MAU Ratio	Ratio of daily to monthly active users	DAU / MAU	> 0.2 is good
Activation Rate	Share of users reaching the product’s core value	Activated users / Registered users	Higher = better onboarding
Logo Churn	Share of customer accounts lost	Lost accounts / Accounts at period start	< 5% annually (established)
Rule of 40	Sum of revenue growth and profit margin	Growth rate + Profit margin (in %)	> 40% is healthy
Gross Margin Retention	NRR based on gross margin	(Start GM + Expansion GM − Churn GM) / Start GM	> 100%
Booking-to-Bill Ratio	Bookings relative to billed value	Order value / Billed value	> 1.0 indicates growth

Fact

Current benchmarks put average annual churn in B2B SaaS at around 3.5%. Established enterprise-focused companies often stay below 5% annually. SMB-focused vendors typically land around 3 to 5% per month. Median Net Revenue Retention (NRR) is roughly 106%, while top performers exceed 120%.

Source

Manufacturing and production

In manufacturing, throughput, equipment availability, and quality are central. These metrics are often closely tied to lean management principles.

Metric	Definition	Formula	Benchmark guidance
Scrap Rate	Share of scrap in total production	(Scrap / Total production) × 100	As low as possible
Downtime	Standstill caused by disruptions	Sum of downtime	As low as possible
Changeover Time	Time needed to retool a machine	End timestamp − Start timestamp	Shorter = more flexible
Cycle Time	Production time per unit	Sum of cycle times / Units	Shorter = more efficient
Takt Time	Required pace to meet demand	Available production time / Customer demand	≤ Cycle Time
MTBF	Average time between failures	Total operating time / Failures	Higher = more reliable
MTTR	Average repair duration	Sum of repair times / Repairs	Shorter = better
Labor Productivity	Output per labor hour	Output / Labor hours	Higher = more productive
Energy Intensity	Energy use per production unit	Energy consumption / Produced units	Falling
OTD (On-Time Delivery)	Share of orders completed on time	(On-time orders / Total orders) × 100	> 95%

From library to dashboard

A KPI library is a reference, not an action plan. The real value only starts when you select three to nine metrics from this overview for your first dashboard, define them clearly, and distribute them to the right people.

Three steps help here. First, clarify which business goals matter most right now. Then assign one outcome metric and one or two driver metrics to each goal. Finally, define who owns the metrics, how often they are reviewed, and which thresholds indicate the need for action.

Conclusion

Metrics are valuable when they improve decisions. That does not happen through quantity, but through the right selection, clear definitions, and disciplined day-to-day use.

Start with a small set of goal-linked metrics. Build a first dashboard that answers one concrete question. Review regularly whether the chosen metrics still fit your current goals, and adjust them when needed.

Start small, sharpen the metrics, then scale.