What to Track & How

Choosing the right metrics is one of the hardest parts of OKRs. Track the wrong things and you'll optimize for the wrong outcomes. This guide helps you identify meaningful metrics and set up effective tracking.

Leading vs Lagging Indicators

Understanding the difference between leading and lagging indicators is crucial for effective tracking.

  • Lagging indicators — Measure outcomes after they've happened (revenue, churn, NPS). They tell you how you did.
  • Leading indicators — Predict future outcomes (activation rate, feature adoption, engagement). They tell you how you'll do.
A good key result often pairs a lagging indicator (the ultimate goal) with leading indicators you can influence week over week.

Finding Your North Star Metrics

Start by identifying the metrics that truly matter for your business:

  1. What does success look like? — If this cycle went perfectly, what numbers would change?
  2. What do your customers value? — Metrics should connect to real customer outcomes.
  3. What can you actually influence? — Don't track things outside your control.
  4. What can you measure reliably? — Fuzzy data leads to fuzzy decisions.

Common Metric Categories

Growth Metrics

  • New users/customers acquired
  • Conversion rate (trial to paid)
  • Activation rate (new users completing key action)
  • Referral rate

Engagement Metrics

  • Daily/weekly/monthly active users
  • Session frequency and duration
  • Feature adoption rates
  • Actions per session

Retention Metrics

  • Churn rate (customer or revenue)
  • Retention cohorts
  • Net revenue retention
  • Customer lifetime value

Satisfaction Metrics

  • Net Promoter Score (NPS)
  • Customer Satisfaction Score (CSAT)
  • Customer Effort Score (CES)
  • Support ticket volume and resolution time

Operational Metrics

  • Cycle time / lead time
  • Error rates / uptime
  • Response times
  • Cost per acquisition

Setting Up Tracking

Before the cycle starts, ensure you can actually measure what you plan to track:

  1. Identify data sources — Where does this data live? Analytics, database, CRM, surveys?
  2. Establish a baseline — What's the current value? You can't measure progress without a starting point.
  3. Set up regular reporting — Can you get this number weekly without heroic effort?
  4. Validate data quality — Is the data reliable? Test it before committing.
If you can't get baseline data before the cycle starts, consider a different metric. "We'll figure out how to measure it" usually means you won't.

Using Metrics in Runsheet

Runsheet supports standalone Metrics that can be tracked independently or linked to key results:

  • Standalone metrics — Track KPIs that matter beyond a single cycle (MRR, churn, NPS)
  • Key result metrics — Specific targets tied to an objective for this cycle

For ongoing business health metrics, create standalone metrics and link them to key results when relevant. This gives you historical trends while still connecting to specific goals.

What NOT to Track

  • Vanity metrics — Numbers that look good but don't indicate real progress (total signups with no activation data)
  • Activity metrics as outcomes — Counting outputs instead of outcomes (features shipped, meetings held)
  • Metrics you can't influence — External factors outside your control
  • Too many metrics — If you're tracking 50 things, you're not focused on any of them

Qualitative vs Quantitative

Not everything that matters can be reduced to a number. Consider:

  • Customer interviews — "8 out of 10 interviewed customers say X"
  • Milestone completion — "Launch beta with 5 pilot customers"
  • Binary outcomes — "Achieve SOC 2 compliance"
Qualitative key results are valid, especially for new initiatives where you don't yet have data. Just make sure success is clearly defined and verifiable.

Related Topics