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


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


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


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

Set Meaningful Goals



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

Building Idea

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

Leveraging Data To Build Consumer Products

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Our story so far.

See a Recap of How Far We've Come

Engagement Drives Stickiness Drives Retention Drives Growth

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Understand the connection between engagement, stickiness, retention and growth.

Learn More About the Cycle


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Engaging experiences provide value.

Understand the Meaning of Engagement

Engagement Part I: Introduction to Activity Feeds

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Engagement is the earliest indicator of product market fit.

Intro to Activity Feeds

Engagement Part II: Content Production

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Content production is the single most important factor that influences engagement.

How to Track Content Production

Engagement Part III: Connections and Inventory

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Connecting people with the right content will drive greater relevant inventory.

Learn the Importance of Connecting Users

Engagement Part IV: Activity Feed Ranking

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Activity Feed Ranking is critical for driving Engagement in high inventory situations.

Discover the Significance of Activity Feed Ranking

Engagement Part V: Consumption

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Delightful consumption of stories leads to higher engagement and ultimately to stickiness, retention and growth.

Discover Key Considerations for Content Consumption

Engagement Part VI: Feedback

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Understanding the various types feedback of feedback and the role feedback plays in building an engaging product.

Examine the Role of Feedback in Engagement

Engagement Part VII: Summary and Product Implications

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Driving a sustainable highly engaging product requires careful considerations.

Learn About Additional Considerations that Affect Engagement

Engagement: Professional Content Part 1: Content Production

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Producing evergreen content is the most important lever for engagement.

How to Create Evergreen Professional Content

Engagement: Professional Content Part 2: Recommendations

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For a platform offering professional content, recommendations are the primary means of highlighting the content users will find most relevant.

How to Make Content Relevant Through Recommendations

Engagement: Professional Content Part 3: Content Consumption

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Consumption of content is strongly affected by device and connectivity.

Understanding Content Consumption

Two-Sided Marketplaces and Engagement

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Designing a thoughtful framework is valuable to understand engagement.

Creating Two-Sided Marketplaces

The Building Blocks of a Data-Informed Company

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Successful data-informed companies do two things well — focus on impact and build a data-informed culture.

How to Build a Data-Informed Culture

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