Resources

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

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Blog Post

Qualitative data: Examples and how to use it

Learn how to analyze qualitative data. We show examples of how to collect, organize, and analyze qualitative data to gain insights.

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Blog Post

Holiday code freezes: Unwrapping the pros and cons

Code freeze has been a standard practice for ecommerce sites for years. But are the benefits still worth the risks? Let’s explore.

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Blue ripples
Deep Dive

How to understand, use, and build customer journey maps

A customer journey map is key to building a solid marketing strategy. We cover everything you need to know about customer journey maps, their different types, examples, and the steps to making your own.

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Guide

Building the ideal ecommerce tech stack for growth

How to build an ecommerce stack that’s tailored to your business—and, more importantly, your customers.

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Customer Story

Why Gap Inc. chose FullStory’s Digital Experience Intelligence platform

By implementing FullStory, Gap Inc. is able to gain a comprehensive and granular understanding of customers’ experiences throughout the shopping process without compromising site speed.

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Blog Post

What's a scroll map? How to build, analyze, and use scroll maps

See how far users scroll and get stakeholders on the same page when it comes to prioritizing content and features within a given page design.

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A number sign
Blog Post

Quantitative data examples to help you understand how to take action

Quantitative data is used for calculations or obtaining numerical results. Learn about the different types of quantitative data uses cases and more.

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Blog Post

4 ways to improve your holiday shopping experience, according to consumers

We surveyed 1,600+ US consumers to find out how and where they plan to shop for holiday gifts—plus what they expect from retailers.

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Blog Post

Categorical vs. quantitative data: The difference plus why they’re so valuable

Categorical & quantitative variables both provide vital info about a data set. But each is important for different reasons and has its own pros/cons.

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