Choosing the Right Product Analytics Tool: A Guide Beyond Metrics

Navigating the Essentials: Questions to Prioritize for Success

In a world where data is king, choosing the right product analytics tool can feel like searching for a needle in a haystack. Adam Nash, former VP of Product at LinkedIn and Dropbox, famously wrote that PMs should always remind themself “what game are we playing and how do we keep score?”. This wisdom extends beyond merely tracking the North Star metric; it’s about ensuring every metric you measure directly contributes to your business’s success. Without this focus, metrics are just distractions.

Pick and Choose From Only 89 Selected Vendors!

There’s currently an overwhelming choice. G2 lists 89 different platforms under ‘Product Analytics’. Making the task of choosing the ‘right’ one seems daunting. Reliance on recommendations from peers might seem like a safe bet, but when the nuances of each product’s context vary widely, such advice may lead you astray. An internal survey of current and past clients, revealed a surprising trend: despite the dissatisfaction with their current analytics platforms, many Product Managers shy away from switching due to the perceived costs, both monetary and in terms of human resources. This scenario highlights a market flooded with ill-fitting solutions — prestigious, perhaps, but not tailored to truly fit the actual needs.

The Big Five Questions

To navigate this crowded landscape, focus on what truly matters to your product. Here are five critical questions to guide your selection process:

1. Market Domain: Are you operating in B2B, B2C, or B2B2C markets? Each has unique analytics needs.
2. Platform Compatibility: Does your product live on the web, mobile apps, or across multiple platforms? Your Analytics tool should seamlessly integrate with your product’s environment.
3. Setup Complexity and Developer Dependency: Do you prefer a tool that offers quick setup with minimal developer involvement, or one that provides deeper insights at the cost of more complex implementation?
4. Volume and Pricing Model: Consider your expected usage volumes. Since pricing models vary — based on events, sessions, or unique users — this will significantly influence your choice.
5. Advanced Features: Are additional features like session recordings, heatmaps, and rage click detection critical to your needs? Be prepared; these features may significantly impact the cost.

Understanding your specific requirements upfront can save you from investing in a solution that’s akin to choosing a sports car when you actually need a 20-ton truck.

Case in Point

Given these criteria, let’s examine recommendations for a hypothetical B2B company, web only, prioritizing ease and a speedy setup, ~200 monthly users and session recording are essential:

• Heap stands out for its auto-tracking capabilities, enabling quick setup without extensive manual configuration. It’s ideal for businesses seeking immediate insights with minimal development effort.
• FullStory offers detailed session recording and playback, alongside robust analytics features tailored for web platforms. It shines in automatically identifying frustrations and UI problems.

These tools, selected based on low usage volumes and a qualitative focus, offer insights that quantitative tools might miss due to lack of statistical significance. Yet, changing any of the five key answers could and most likely would, lead to a different recommendation.

Final Thoughts

Selecting the perfect Product Analytics tool is a nuanced process that extends beyond simple metrics. By asking the right questions and prioritizing your product’s specific needs, you can cut through the noise and find a solution that not only fits but propels your product towards success. Whether you’re busting myths or chasing ghosts, the key is to understand what you’re really looking for — before you start looking.

About the Author

Yoav Yechiam is a globally recognized expert in the field of Behavioral Analytics. He serves as the managing partner at strategic consulting firm The Product Alliance. Leveraging his extensive experience, Yoav has contributed to the development of the GPT-powered 🤖 Analytics Advisor Bot, designed to guide and assist Product Managers in choosing the right analytics tool for their organization. This innovative yet simple and intuitive tool helps navigate the complexities of Product Analytics selection. Feel free to try it out for yourself while it’s still free to use.