CEO: steer growth
Revenue growth, net revenue retention, north star metric.
KPIs, OKRs and metric frameworks
A KPI, or key performance indicator, is a measurable value that shows progress toward a specific goal. Every key indicator is a metric, but most metrics are not key indicators.
A good indicator has five parts: a written formula, a data source, a target, an owner and a review rhythm. Without them, the same number shows different values in different meetings. A business can track hundreds of metrics, yet it should steer by a small set tied to its organizational goals.
The three terms are often mixed up. They do different jobs. Each row compares a metric, a key indicator and an OKR, in that order.
| Metric | KPI | OKR | |
|---|---|---|---|
| Know what each one is for | Measures any activity | Tracks a strategic goal | Sets an objective with key results |
| Know how long each one lasts | Continuous | Ongoing, reviewed regularly | Usually a quarter or a year |
| See each one in practice | Website sessions | Net revenue retention | Enter a new segment, measured by pipeline |
A metric measures something that happens in the business. Most metrics support analysis, not steering.
A KPI is one of the few metrics leadership chooses to steer by, with a formula, source, target, owner and review rhythm.
An OKR sets direction for a period. Its key results are measured, often with KPIs.
These 12 analytics KPIs follow the path from first visit to retained revenue, plus two that measure the data team itself. Each row gives the KPI formula, the question it answers and the one role that usually owns it.
| Formula | What it tells you | Owner | |
|---|---|---|---|
| Conversion rate | Conversions / sessions x 100 | How well the site turns visits into the action you want, such as a demo request | CMO |
| Engagement rate | Engaged sessions / sessions x 100 | Whether visitors find the content worth their time; GA4 counts a session as engaged when it lasts longer than 10 seconds, has a key event or has 2 or more page views | CMO |
| Customer acquisition cost (CAC) | Sales and marketing spend / new customers won in the period | What it costs to win one customer, and whether growth is getting cheaper or dearer | CMO |
| Lead-to-opportunity rate | Opportunities created / leads created x 100 | Whether marketing sends leads that sales accepts and works | CMO |
| Win rate | Deals won / deals closed (won plus lost) x 100 | How often the sales team turns a qualified opportunity into revenue | Head of sales |
| Pipeline coverage | Open pipeline due in the period / revenue target for the period | Whether there is enough pipeline to reach the target before the quarter starts | Head of sales |
| Net revenue retention (NRR) | (Starting recurring revenue + expansion - contraction - churned revenue) / starting recurring revenue x 100 | Whether existing customers grow or shrink as a group, before any new sales | CEO |
| Customer churn rate | Customers lost in the period / customers at the start of the period x 100 | How many customers you lose, and whether retention work is paying off | Head of customer success |
| Gross margin | (Revenue - cost of goods sold) / revenue x 100 | How much of each sale is left to pay for overheads and growth | CFO |
| Forecast accuracy | (1 - absolute value of (actual - forecast) / actual) x 100 | How far leaders can trust the forecast when they plan hiring, spend and cash | CFO |
| Dashboard adoption rate | Active dashboard users in the period / intended users x 100 | Whether the reports the data team builds are used to make decisions | Head of data |
| Data quality pass rate | Records that pass the agreed quality rules / records checked x 100 | Whether the numbers behind every other KPI can be trusted | Head of data |
Treat each formula as a starting point. Agree the filters, data source and period with the owner, then record them in your metric dictionary so every report calculates the KPI the same way.
Targets and benchmarks vary by industry, size and business model. Set them from your own baseline rather than from a published average whose definition may not match yours.
Download the KPI formulas template (Excel, free)↓ The same 12 KPIs in one Excel file: each formula, a worked Excel example on demo inputs and the usual owner. No sign-up.
Our sample executive dashboard uses demo data. It shows revenue, margin, pipeline coverage and retention rate, each with its target, trend and owner.
Net revenue retention vs target, by month, %
So what: Look first at the tile off target and trending the wrong way, then ask its owner why.
| KPI | Actual | Target | Owner |
|---|---|---|---|
| Revenue | $1.32M | $1.28M | CEO |
| Gross margin | 44% | 44% | CFO |
| Pipeline coverage | 2.9x | 3.0x | Head of sales |
| Net revenue retention | 101% | 105% | CEO |
Revenue vs target by quarter, $M
So what: Strong revenue can hide weak retention; read both tiles before deciding where to act.
| KPI | Q1 | Q2 | Q3 |
|---|---|---|---|
| Revenue | $3.5M | $3.7M | $3.9M |
| Gross margin | 44.1% | 43.9% | 43.6% |
| Net revenue retention | 106% | 104% | 102% |
Use it to decide where to look first: the tile that is off target and trending the wrong way. Then ask its owner why.
Key indicators turn strategy into a few numbers everyone can follow.
Defined well, they align teams, show progress and flag problems early enough to act.
They also change meetings. Leaders stop arguing about whose figure is right. They discuss why a number moved and what to do next, so the team makes informed decisions instead of guesses. Over time, historical data on each indicator helps show which initiatives worked.
All of this depends on governance. An indicator with an unclear formula or a weak data source is worse than none, because it builds confidence in the wrong number.
Good indicators also make accountability fair. When each one has one owner and one formula, people are judged on the same basis.
They support continuous improvement too. Leaders read a few numbers, see which ones moved and spend the meeting on causes and actions.
Five best practices keep an indicator set small and useful.
Pick measures that track a stated goal, not what is easiest to report.
Record formula, source, filters and refresh in a metric dictionary.
One person is accountable for each measure and its target.
Only the few measures that drive leadership decisions.
Drop measures that no longer drive action; revisit targets each planning cycle.
Follow them in order before any measure reaches a dashboard.
Leading and lagging measures work as a pair.
| Act before results land | Leading indicators signal outcomes early, such as pipeline coverage | Lagging indicators confirm them, such as revenue |
|---|---|---|
| Match the measure to the horizon | Strategic measures track goals over quarters | Operational measures track daily or weekly execution |
| Measure what people feel too | Quantitative measures use numbers, such as margin | Qualitative measures capture views, such as satisfaction |
The common mistakes: too many indicators, measuring activity instead of outcomes, undocumented formulas and each team calculating the same number its own way. Setting targets without a baseline is another. Each one erodes trust in the dashboard, and a metric dictionary entry prevents each of them.
Treat each list as a KPI sample to adapt, not a standard.
Revenue growth, net revenue retention, north star metric.
Gross margin, cash conversion, forecast accuracy.
Sourced pipeline, cost per opportunity, conversion rate.
On-time delivery, cycle time, capacity utilization.
Questions leaders ask when they define or review their KPIs.
Analytics KPIs are the few measures a business uses to judge whether its marketing, sales, finance, customer and data work is reaching its goals. Each one has a written formula, a data source, a target and an owner. Common examples are conversion rate, customer acquisition cost, win rate, net revenue retention and forecast accuracy.
There is no fixed number. A leadership team usually steers by a short list it can review in one meeting, and each department adds a few of its own. If a KPI has not led to a decision or an action for several review cycles, retire it or move it back to the supporting metrics.
Use benchmarks with care. Published figures often mix company sizes, business models and definitions, so they rarely compare like with like. Start from your own baseline over the last few periods, then set a target the owner agrees is ambitious and achievable. Use an external benchmark only when its source and definition match yours.
Leading KPIs move before the result, such as pipeline coverage or engagement rate, so there is still time to act. Lagging KPIs confirm the result after the period, such as revenue, gross margin or churn. A useful KPI set pairs each lagging KPI with one or two leading KPIs that drive it.
Name the numerator, the denominator, the period and the filters. For conversion rate, that means which conversions count, whether you divide by sessions or users, which dates apply and whether internal traffic is excluded. Record the formula and its source system in a metric dictionary, so every report calculates it the same way.
One named person per KPI, usually the leader whose team moves it most. The business owner sets the target and decides the actions when the KPI is off track. The data team owns the calculation, the data source and the data quality checks, so the owner can trust the number in every review.
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