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Research: Analytics

UXmatters has published 20 articles on the topic Analytics.

Top 3 Trending Articles on Analytics

  1. Tracking User Behaviors on Web Sites: Why It Matters and How to Do It

    June 23, 2025

    15 seconds. That’s how long 55% of users stay on an unfamiliar Web site before bouncing. Think about that—you spend time, money, and effort to bring people to your site, only for them to vanish in less than a minute. What makes new users leave? What makes other users stay longer? And, most importantly, how can you increase the duration of visits?

    The answer to all these questions lies in understanding what users actually do when they land on your Web site. The discipline that lets you gain this understanding is user-behavior tracking, which enables you to figure out what users click, how far they scroll down pages, and the exact point at which they lose interest. Read More

  2. Crafting Seamless User Experiences: A UX-Driven Approach to Log Monitoring and Observability

    May 20, 2024

    Log monitoring holds significant value for improving the user experience despite its primary association with Operations or Information Technology (IT). The problems that many IT teams face include stuttering pages, slow page-loading times, and frequent crashes. Logs can reveal bottlenecks and bugs and often hold the answers to identifying and solving such problems.

    Understanding why such problems are occurring lets you resolve their root cause and ensure a smooth user experience that prevents user frustration. Let’s consider several ways in which log monitoring can contribute to enhancing the user experience:

    • proactive issue identification
    • performance optimization
    • user-behavior analysis
    • enhanced troubleshooting
    • optimization of user journeys
    • security and privacy assurance  Read More

  3. Measuring What Matters: The Metrics That Prove Your IA Actually Works

    Structuring Success

    Organizing content to empower users

    A column by Henry Adepegba
    September 21, 2026

    In earlier installments of this column, I’ve written about making the business case for information-architecture (IA) investment using language that stakeholders respect, as well as about conducting quarterly audits that keep an IA-governance model honest. Both of those pieces leaned on the same unstated assumption: you must actually have numbers to report at the end of the quarter. But most teams don’t. Not because the data doesn’t exist, but because nobody decided in advance which numbers should count as evidence that an IA is working rather than just feel reassuring.

    This is the gap that exists between “the new navigation looks cleaner” and “the new navigation reduced task failures by twelve percent.” Only one of these statements can survive a skeptical stakeholder, and only one of them tells you whether to keep going or roll back to an earlier version. Read More

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