Resources

Tips, tutorials, guides, and product insights from FullStory’s Digital Experience Intelligence experts

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A magnifying glass zooming in on data.
Blog Post

Why is product analytics so important?

We dive into why product analytics is important to customer experience and how you can become better data-informed.

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Angry signals on a mobile app
Deep Dive

What is user friction? How to avoid the mistakes and optimize your UX

User friction is when something stands in the way of creating an optimal user experience. Discover how you can use it to boost your usability.

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An example of a product analytics dashboard showing checkout conversion rates.
Deep Dive

What is product analytics? Your ultimate guide

A comprehensive guide to product analysis and analytics platforms, how important they are, and why they’re a valuable asset for your bottom line.

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Blog Post

7 ways leading ecommerce brands stay agile

Experts share 7 key trends among retailers who have successfully navigated the pandemic’s challenges.

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fs-guide-mobile-app-optimization-1
Guide

The 8 mobile metrics high-performing teams must track

Optimizing mobile performance for your organization? Use this guide to narrow focus on critical metrics.

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Blog Post

Black Friday recap: 3 ecommerce trends we noticed

How did retailers’ Digital Experience Intelligence fare during Black Friday 2021? See inside for high-level signals from FullStory data.

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A completed customer journey map
Blog Post

How to create a customer journey map

Map out how your customers navigate your website or app—and determine where you need to improve.

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Data in the FullStory platform, including rage click and subscribers.
Deep Dive

What is quantitative data? How to collect, understand, and analyze it

A comprehensive guide to quantitative data, how it differs from qualitative data, and why it's a valuable tool for solving problems.

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Examples of qualitative data.
Deep Dive

What is qualitative data? How to understand, collect, and analyze it

A comprehensive guide to qualitative data, how it differs from quantitative data, and why it's a valuable tool for solving problems.

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