How can you create a scalable product metrics framework?

I call these L1, L2, and L3 metrics ('L' stands for level). Depending on your team/company size, the audience for these metrics is different. The leadership team (GM/VP/Director) is the audience for L1/product vision metrics. These are lagging indicators. The product managers and engineering teams are focused on L2 and L3 metrics, which are usually leading indictors that influence the L1 metrics. Simplicity is the key at each level, so that we focus on a small set of right metrics that track the OKRs. Having too many metrics introduces noise and overwhelms the audience.

A product metrics hierarchy consists of three key levels: Product Vision: These are high-level, strategic indicators directly linked to the product's overarching vision and value proposition. Examples include tracking revenue, measuring customer satisfaction, monitoring retention rates, and evaluating market share. Product Strategy : These metrics are more specific and help measure progress toward strategic goals aligned with the product vision. Examples include user adoption rates, feature adoption, user engagement, and churn rates. Product Execution Metrics: Focusing on operational aspects, these metrics ensure product performance and quality. Examples include page load times, error rates, usability testing scores, and conversion rates.

It's often easier to start with what I call "Metric Chains". It can be difficult and intimidating to apply general frameworks like the product metric hierarchy to your unique product or situation. Instead, it might simpler to pick a metric that you care about, and then ask two questions. 1. What causes this metric to change? 2. What changes if this metric goes up or down? For example, you might care about how many users sign up for your app. What causes this metric to change? The answer might be latency or marketing dollars spent. Then ask, what number changes if more/less users sign up? The answer might be revenue. Boom! You have your metric hierarchy. And like @darshan wrote, you can then group them for the appropriate audiences.

Spot on with the idea of a structured metrics hierarchy—it's like a roadmap in this complex journey of product management! It’s crucial to align every layer, from the broad vision to the specific details, to ensure coherence and relevance. Having those top-level vision metrics sets the stage, strategy metrics keep us goal-oriented, and execution metrics ensure everything’s running smoothly. It’s this careful balancing of overarching goals with the daily grind that leads to creating products that resonate, truly meeting user needs and standing up to market dynamics.

Another good framework to consider is the “heart metrics” framework. Happiness Engagement Adoption Retention Task success Each product should have some metrics in each of these categories for a well rounded picture.

There should be multiple levels which needs to be considered like on 1. strategic level 2. Tactical level, 3. operational level , 4. user level, 5. Financial level, 6. compliance and security level, 7. Marketing and sales level, 8. customer support level Plus we need to communicate regularly and review metrics with the respective teams to ensure alignment and drive continuous improvement.

Choosing the right metrics is about setting strategic signposts on the product development journey. Aligning metrics with product context, customer needs, and business goals is crucial. Using SMART criteria is about ensuring clarity, realism, and alignment at every product evolution stage. Avoiding vanity metrics is key—they may flatter but can distract from the real value and impact. A focus on substantive, insightful metrics is essential for developing products that truly resonate with users and meet market needs.

Establishing baselines and targets is like crafting a navigational chart for product journeys. The baseline, a reflection of current reality, is foundational for assessing progress. Targets are beacons, guiding toward desired success. The OKR framework is pivotal—it harmonizes qualitative aspirations with quantitative milestones, aligning ambitions with tangible steps. It’s this meticulous crafting of trajectory, balancing ambition and realism, that shapes a pathway for continuous refinement and realization, ensuring every stride is measured, meaningful, and aligned with overarching objectives.

It’s important to also not forgot tracking metrics from areas that may be affected and you want to make sure are not negatively affected. IE - sure you increase signups but you’ve cratered retention. You want to only the retention piece even if your goal is to grow signups.

Don't forget that behind the numbers are real people using your product! In addition to surveys and interviews you can: 1) Become your own customer - use your product! 2) Establish a regular "walk-the-product" exercise where you use the product as if you were a customer (ideally for each user persona). This has two benefits. First, you'll capture qualitative data that didn't arise in surveys or interviews because the question was just never asked. Second, you'll be inspired to invent new features on behalf of your customers.