1. Introduction to Metrics

In product management, metrics are essential tools for measuring the success and performance of a product or a business. Understanding these metrics helps product managers (PMs) make data-driven decisions that guide product development, customer satisfaction, and overall business growth. In this document, we will explore the concept of metrics, categorize them into business, product, and engineering metrics, and discuss how to apply them effectively.

Business, Product, and Engineering Metrics

There are three primary types of metrics: business, product, and engineering metrics.

• Business Metrics: These metrics are typically financial and give insights into the overall health of a company. Common business metrics include revenue, profit, and churn rate. These are key metrics that investors often focus on, as they reflect the company's profitability and sustainability.

• Product Metrics: Product metrics measure how users engage with the product. They provide insights into user behavior and satisfaction. Metrics such as Monthly Active Users (MAU), user retention, and satisfaction scores are examples. These metrics help PMs understand how well the product is fulfilling user needs.

• Engineering Metrics: These are technical metrics related to the functionality of the product. Metrics like system uptime (availability) and response time are crucial for ensuring that the product is performing as expected. Engineering metrics are critical to maintaining a reliable product that users can trust.

Engagement Metrics

Engagement metrics vary by product, but they measure how users interact with a product and how engaged they are with its features. Some examples:

• In HR software like Único People, the number of digital document signings or employee admissions might be the primary engagement metrics.
• For Nubank, the percentage of active users across various financial products or the share of wallet (the percentage of a user's income managed through Nubank) serves as key engagement indicators.
• In marketplaces like Catho or Viva Real, engagement metrics include the number of job applications by candidates or the response time of advertisers to inquiries in a real estate marketplace.

Leading and Lagging Metrics

A crucial concept in metrics is the distinction between leading and lagging metrics:

• Leading Metrics: These are predictive metrics that provide insights into future performance. For example, user engagement during a product trial can predict future conversion rates from trial users to paying customers.

• Lagging Metrics: These reflect past performance. For example, customer churn is a lagging metric as it measures users who have already left the product.

Vanity Metrics

Not all metrics are actionable. Some are considered vanity metrics, which can give a false sense of success. For example, the number of app downloads might seem like a good indicator of success, but it doesn’t necessarily translate to active or paying customers. Similarly, article views don’t directly correlate with lead generation unless those views convert into actual sales or leads.

North Star Metric vs. Constellation of Metrics

When managing a product, it is essential to define key metrics. There are two main approaches:

• North Star Metric: This is a single, overarching metric that captures the core value delivered to users. For example, Airbnb may focus on the total number of nights booked, or Spotify might measure total listening time. All other metrics feed into this primary metric.

• Constellation of Metrics: A more complex but comprehensive approach involves tracking multiple metrics simultaneously. For instance, Airbnb shifted from just measuring nights booked to also monitoring Net Promoter Score (NPS) for quality and customer service tickets per reservation for efficiency. This method helps balance different aspects of performance, such as growth, quality, and operational efficiency.

The Metrics Tree

The metrics tree is a visual representation of how various metrics relate to and impact each other. It shows the breakdown of a key metric into sub-metrics and dimensions. For example, a SaaS B2B company might track Monthly Recurring Revenue (MRR) and break it down into the number of customers and average revenue per customer. Each of these can be further broken down into subcategories, such as new customers, churn rate, customer satisfaction (NPS), and engagement levels.

In practice, each metric may influence others. For example, higher NPS scores often correlate with lower churn rates. However, the relationship between these metrics can vary by context and over time.

Conclusion

Metrics are essential for product management, providing insights into the performance of both the product and the business. Whether you choose to focus on a single North Star Metric or a constellation of metrics, the key is ensuring that your metrics align with your product’s goals and strategy. Additionally, understanding the difference between leading and lagging metrics, as well as avoiding vanity metrics, helps ensure that decisions are based on meaningful, actionable data. Using tools like the metrics tree can also provide a structured way to see how different factors impact the product's overall success.