If PLG is the engine, then the fuel is product data.

The world of product-led growth (PLG) is thriving, with new ideas and strategies emerging every day. While we often hear about product-led marketing, product-led sales, hybrid-led sales, and more, there is an unsung hero in the PLG arena: product data.

Surprisingly, there’s a lack of thought leadership and practical advice in this area. That’s why we’re here to shed light on the importance of product data in the PLG ecosystem.

My team has extensive experience in implementing instrumentation and PLG stacks for startups and Fortune 50 companies alike. We’re currently working on scaling product data and PLG stack for an impressive 200 products.

Companies of all sizes tend to approach product data in a similar way. The process often looks like this:

Product: “We see people signing up and some of them eventually paying, but we don’t know what happens in between.”

Marketing: “We don’t know how our campaigns perform in product!”

Sales: “We’d love to know which users are potential big clients so we can sell to them.”

Everyone: “Should we use Segment, Amplitude, or Mixpanel?”

Before you run off to invest in a data tool, it’s crucial to understand and analyze how users interact with your product. Essentially, business goals meet user behavior.

To achieve this, follow a three-step process to define your product data and analytics approach: ask & define, KPI tree, and taxonomy.

Ask & define

Before signing up for a costly vendor, take a step back and ask some key questions. The goal of the ‘ask’ phase is to understand and align the factors driving growth, which will define your North Star Metric. By identifying your North Star Metric, you can track the KPIs necessary for success. Be sure to involve and align with other departments in your company, especially those driving revenue.

Consider these questions:

  • What’s your company’s core growth engine?
  • What’s your North Star Metric based on the growth engine defined above?
  • What business goals must you meet to grow your North Star Metric?
  • What KPIs feed into those business goals?

So how do you go about defining your North Star metric so that the entire company will align around it?

  1. 🤝 Involve key stakeholders: Engage representatives from different departments, such as product, marketing, sales, customer success, and engineering, in the ask & define process. This will ensure a holistic understanding of your business objectives and encourage cross-functional alignment around your North Star Metric and KPIs.
  2. 😞 Identify customer pain points: Understand the challenges your customers face when using your product. This can help you define metrics that track your product’s effectiveness in addressing these pain points, ultimately leading to better customer satisfaction and retention.
  3. 🕵️‍♀️ Understand your competitive landscape: Research your competitors and their performance in the market. This will give you insights into industry benchmarks and best practices, helping you define KPIs that are relevant and meaningful in your specific context.
  4. ♾️ Consider the different stages of the customer lifecycle: When defining your KPIs, take into account the various stages of the customer lifecycle, from acquisition to activation, retention, referral, and revenue. This will help you create a comprehensive view of your customers’ experience with your product and identify areas for improvement throughout the lifecycle.
  5. 🎬 Focus on actionable KPIs: While it’s essential to track high-level KPIs, like revenue or user growth, also prioritize actionable KPIs that can drive specific improvements in your product. Actionable KPIs can help you make targeted, data-driven decisions that directly impact your business goals.
  6. ⚖️ Balance leading and lagging indicators: In addition to tracking lagging indicators (results of past actions), also include leading indicators (predictive metrics) in your KPI set. This will help you anticipate future outcomes and make proactive adjustments to your strategy.

KPI tree

A KPI tree is a helpful tool for identifying the key metrics or events that should be instrumented in a product organization. Mapping out the user journey and key business outcomes will help you recognize the actions or events essential to driving those outcomes.

The KPI tree will guide the instrumentation process by highlighting the events or metrics most important to track and measure for delivering and capturing value.

Additionally, the KPI tree can be used to prioritize the development of new instrumentation or enhancements to existing instrumentation based on their impact on overall KPIs.

  1. Align KPI trees with company objectives: Ensure that your KPI tree is aligned with your company’s overall objectives and growth strategy. This’ll help you focus on the most important metrics and make data-driven decisions that contribute to your company’s success.
  2. Break down high-level KPIs into actionable sub-metrics: High-level KPIs, like revenue or user growth, can often be difficult to influence directly. Break them down into more specific and actionable sub-metrics that reflect the various aspects of your product or business. This’ll enable you to identify areas for improvement and make targeted, data-driven decisions.
  3. Visualize your KPI tree: Create a visual representation of your KPI tree to make it easier for team members to understand the relationships between different metrics and see how they contribute to your company’s overall goals. This can be as simple as a flowchart or diagram, or you can use specialized tools and software designed for this purpose.
  4. Map KPI trees to your instrumentation: Tranlsate the user actions that map to the sub-metrics in your KPI tree into your instrumentation plan. This’ll provide an actionable product data stream for your teams.

Example of a product whose North Star metric is Paid MAUs.


Based on the KPI tree, identify the user actions (events) you want to track and send. Good, well-planned instrumentation is essential, as inadequate instrumentation can lead to omitted events, poor naming, and misused properties, ultimately complicating your analyses and hindering the full utilization of your data.

Consider the properties you want to include in your events. Most product data tools will provide common properties (e.g., source, referrer, country) out-of-the-box. The properties you choose to track should be a mix of business goals and specific product requirements.

  1. Develop a comprehensive tracking plan: A tracking plan should outline the events and properties to be tracked, as well as the rationale behind each decision. This plan should be reviewed and updated regularly to ensure that it remains relevant and adapts to any changes in the product or business objectives.
  2. Focus on actionable data: When instrumenting your product, prioritize tracking events and properties that’ll provide insights that can directly inform decision-making and drive improvements. Avoid collecting data for the sake of having data; instead, focus on gathering information that’ll genuinely contribute to achieving your business goals.
  3. Validate and test your instrumentation: Ensure the accuracy and reliability of your data by thoroughly testing your instrumentation. This may involve checking for correct event firing, validating property values, and identifying any gaps or inconsistencies in data collection.
  4. Establish a naming convention: Develop and maintain a consistent naming convention for events and properties. This’ll make it easier for team members to understand and analyze the data, as well as reduce the potential for confusion or errors.
  5. Maintain documentation: Keep clear and up-to-date documentation of your instrumentation, including the tracking plan, naming conventions, and any changes made over time. This documentation will serve as a valuable reference for both current and future team members.
  6. Monitor and optimize your instrumentation: Regularly review your instrumentation to ensure that it continues to meet the needs of your business and product. This may involve adding new events or properties, updating existing ones, or removing those that are no longer relevant.

In conclusion, product data is the unsung hero of PLG, fueling growth and driving success across your organization. By implementing a well-thought-out product-led data strategy, including a thorough ask & define process, a comprehensive KPI tree, and a clear taxonomy, you can unlock the full potential of your product data.

This will empower you to make data-driven decisions, optimize your product’s performance, and better understand your customers’ needs and preferences.

As the world of PLG continues to evolve, don’t let the value of product data go unnoticed. Embrace the power of product-led data to propel your company forward, improve the user experience, and foster long-lasting relationships with your customers.

Remember, the key to PLG success lies in understanding and leveraging your product data to drive growth and outpace the competition. So, gear up, roll up your sleeves, and harness the power of product data to become a true PLG champion!