Product Analytics

Don’t release anything without instrumentation! NEVER!

Marty Cagan

Collect product data as early as possible. Don’t save on data, collect generously. Make the information available freely internal to your organization – share data widely. Share findings in your data, be honest and report good news as well as bad news.

Product data inspires new product work, measures progress and allows to understand customer behavior. Most important, product data is the fundament to allow informed decisions. Collect data, find evidence that ideas work and let data influence your decision making process.

What can be measured?

• Behavior (click paths, engagement)
• Business (active users, conversion)
• Financial (average selling price (ASP), billings, time to close)
• Performance (load time, uptime, crashes)
• Operational costs (storage, network, computing)
• GTM costs (acquisition, programs)
• Sentiment (NPS, C-SAT, exit surveys)
• External sources (PR mentions, comments, social media)

Example – Experience Metrics – following the H.E.A.R.T. Framework

For a broader discussion of the H.E.A.R.T. Framework follow the link.

Happiness	‣ actual NPS ‣ % satisfied users
Engagement	‣ % active users of X / time frame ‣ avg. number key action per user ‣ avg. time between key actions
Adoption	‣ adoption rate ‣ time to first action
Retention	‣ retention rate ‣ mean time to churn
Task Success	‣ completion time ‣ error rate

One key criterion for B2B services to move away from on-premise to cloud based services is that instrumentation comes basically for free. B2B has to relax on security, safety and privacy concerns – or find ways to implement their high standards in cloud services – but these businesses get a lot of analytics from the cloud provider – they know, what’s going on.

This blog post is part of a series. It summarizes my personal notes of the workshop held by Marty Cagan “How to Create Tech Products Customers Love” from 5th to 6th of June in 2019 in San Francisco.

• #1 Foreword
• #2 Introduction & Root Causes of Product Failures
• #3 Key Terms & Concepts
• #4 Product Teams & Product People
• #5 Product Vision & Objectives
• #6 Product Analytics
• #7 Product at Scale
• #8 Product Development Process
• #9 Product Discovery Principles
• #10 Product Discovery Techniques
• #11 Product Culture & Transformation