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Building Products Using Data

Data Science Team

Companies and products are growing faster than ever before. Strategically collecting and analyzing newly created data has never been more important not only for "counting numbers" and building dashboards, but for helping define goals, roadmaps and strategies. Product analytics is now a must-have, not an afterthought.

There is a scarcity of literature that explains how to conduct product analysis. To help fill this gap, we will publish a series of posts over the coming months on how to build both data-informed products and world-class data science teams.

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Introduction: Data-Informed Product Building

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Explore why data-informed product building has never been more necessary, and how this series will help you do it.

See Our Plan


Evolution of a Product

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Understand the characteristics of successful products from conception to maturity.

Learn How Products Mature

Measuring Product Health

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Metrics to diagnose and analyze product health.

Diagnose Your Product's Health

Defining Product Success: Metrics and Goals

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Setting the right goals and metrics is imperative to product success.

Set Meaningful Goals

Retention

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Techniques to improve user retention and drive growth.

Keep People Coming Back

Sustainable Product Growth

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Learn about growth pitfalls that can limit long-term success.

Learn to Grow Sustainably

Frameworks for Product Success

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Understand the need for frameworks by exploring product-focused examples.

Analyze Product Problems

Analyzing Metric Changes

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Learn how to diagnose shifts in metrics and develop an action plan for monitoring changes in your product.

Understand Changes in Your Metrics


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