Product managers rely on various performance metrics to track the health of their products and make sound, data-driven decisions. These metrics are broadly divided into two categories – Lagging and Leading Indicators. Lagging indicators and leading indicators. Lagging indicators evaluate past performance based on results like revenue, customer satisfaction scores, and churn rate. Leading indicators focus on predicting future performance by tracking measurable precursors and drivers of key outcomes.
Product managers need to monitor both lagging and leading indicators to effectively manage their products. While lagging metrics offer valuable insight into prior decisions through a rearview mirror, leading metrics provide the headlights needed to guide products forward successfully.
Lagging Indicators
Lagging indicators quantify the output and results from past product actions and initiatives. They measure the rearview performance. Some examples of lagging metrics include:
- Revenue – Total sales or revenue generated in a given period
- Customer satisfaction – Scores from customer satisfaction surveys
- Churn or attrition rate – Percentage of customers canceling subscriptions
- Profit margins – Revenue remaining after expenses
- Market share – Portion of the total market captured
- Customer referral rates – Percent of new customers from referrals
These lagging metrics are essential for product managers to periodically evaluate the tangible outcomes from product decisions they have made, and determine if those decisions led to success. However, lagging indicators have some key limitations:
- They measure past performance, not future progress
- Data is only available infrequently, like quarterly or annually
- They reveal outcomes but not why they occurred
- They do not point directly to solutions or next steps
Due to these drawbacks, product managers cannot rely solely on lagging indicators. They need complementary leading indicators to drive decisions and improvements proactively.
Leading Indicators
Unlike lagging indicators, leading indicators focus on predicting future performance by tracking precursors and drivers of desired outcomes. Some examples include:
- Early customer engagement metrics – App Store wish lists, newsletter subscriptions
- Quality of product requirements – Completeness, clarity, acceptance criteria
- Development velocity – Rate of story point completion per sprint
- Software defect rates – Bugs reported per line of code
- Net Promoter Score (NPS) – Likelihood of customer recommendation
- Feature usage – Percentage of users activating new features
- Social media sentiment – Positive versus negative mentions
- Customer support volume – Support tickets opened per customer
While these metrics do not directly quantify revenue, market share, or other definitive outcomes, they provide crucial visibility into the health of activities that ultimately drive those results. For instance, low velocity or high defects during development can foreshadow roadblocks in achieving business goals after launch. Leading indicators enable product managers to course correct proactively.
However, leading metrics also have limitations in terms of directly measuring product outcomes and performance. They require proper context and trend analysis to translate into actions. Product managers need balance with lagging metrics to confirm their decisions led to the intended business impact.
Key Differences
The key differences between lagging and leading indicators include:
- Lagging indicators measure past results while leading indicators predict future outcomes
- Lagging metrics offer valuable hindsight into product performance while leading metrics provide actionable foresight to guide products forward
- Lagging indicators are reactive and evaluate past decisions. Leading indicators are proactive and influence future decisions.
- Lagging metrics quantify definitive outcomes and results from product efforts. Leading metrics focus on measuring the process and precursors tied to outcomes.
- Lagging indicators confirm whether past product decisions and initiatives led to success. Leading indicators identify whether the current product direction will likely succeed.
- Lagging metrics provide objective data and context on outcomes. Leading metrics require interpretation and analysis to translate signals into actions.
While lagging and leading indicators have distinct differences, product managers should leverage both types of metrics. Lagging indicators offer crucial validation of product performance and business impact. Leading indicators enable teams to make course corrections before outcomes are significantly impacted. Focusing solely on either metric type can lead to blind spots. Using lagging and leading indicators together provides the rearview and headlights product teams need to manage products successfully.
Selecting Leading Metrics
Product managers should follow these best practices when selecting leading indicators to track:
- Identify key drivers of business results – Focus on leading metrics that have a proven correlation to lagging indicators like revenue and market share.
- Ensure alignment to outcomes – Leading metrics must have a direct and plausible relationship to lagging outcomes, otherwise, they provide little value.
- Prioritize actionable metrics – Opt for metrics that will provide specific, tangible insights on what actions to take to drive outcomes.
- Target areas where improvements can be made – Track leading indicators tied to parts of the product or process that can be optimized.
- Get cross-functional input – Work with departments like engineering, marketing, sales, and support to select meaningful metrics based on their needs and insights.
- Validate through statistical analysis – Quantitatively validate the correlation between leading metrics and business results.
- Examples – Great leading indicators include velocity, defects, NPS, customer engagement, and adoption rates.
Careful selection of the right leading indicators is crucial to realize their benefits. Vanity metrics that show impressive trends but no relationship to outcomes waste time versus contributing strategic value.
Using Leading vs. Lagging Metrics
Product managers should use leading and lagging metrics for different purposes:
- Lead with leading metrics for making forward-looking product decisions on priorities, roadmaps, and resourcing.
- Use lagging metrics during periodic business reviews to evaluate past performance.
- Leverage leading indicators to guide corrective actions during development and execution.
- Rely on lagging indicators to formally validate if product initiatives succeeded.
- Ensure leading metrics directly influence lagging metrics, not vanity metrics.
- Beware of spending too much time improving lagging metrics that may not correlate to leading indicators impacting future results.
For example, product managers may rely on leading indicators like release velocity to assess the pace of development, and course correct if needed. After launch, lagging metrics around customer acquisition and revenue help quantify market success.
In another scenario, NPS surveys may signal declining customer satisfaction. The product team can then use leading indicators around app performance to identify and fix pain points proactively before churn increases.
Product managers should tap into the complementary relationship between lagging and leading indicators to support data-driven decisions. Leading metrics guide products forward, while lagging metrics validate progress.
Guiding Product Development with Leading Indicators
Leading indicators empower product managers to take action during development for greater launch success. Examples include:
- Monitor development velocity as a leading indicator to assess product delivery timelines and staffing needs proactively.
- Use early customer feedback on product designs or prototypes as a leading indicator to refine requirements before build-out.
- Track defect rates and resolution times during testing as a leading indicator of overall product quality.
- Analyze feature usage data from early-stage testing as a leading indicator of what customers truly value.
- Monitor social sentiment related to early product marketing as a leading indicator of sales pipeline health.
- Assess iteration velocity on UX through A/B tests as a leading indicator of customer experience quality.
- Evaluate levels of customer support inquiries during beta trials as a leading indicator of customer onboarding needs.
Getting ahead of potential downstream issues during development is a key benefit of properly using leading indicators.
Conclusion
Leveraging both lagging and leading indicators is crucial for product managers to make sound, data-driven decisions. Lagging indicators provide objective validation of past product outcomes and performance. Leading indicators offer actionable insights to adjust product direction and processes for future success. While lagging metrics represent the rearview mirror, leading metrics give the headlights to guide products forward effectively. However, leading indicators must be carefully selected based on proven correlation to lagging business results. Relying solely on either lagging or leading metrics can cause product blindness.
Using these two metrics together lets product teams check their blind spots. Savvy product managers continuously track and analyze both types of metrics to manage successful products. They lead with leading indicators, validate with lagging indicators, and proactively connect the dots between the two.
