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Analysis

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Before starting any redesigns, I often need to delve into the site’s data. I collaborate with business strategists and analysts to extract and analyze the funnels and key data. This process allows me to pinpoint users’ pain points more effectively, and provides concrete evidence of how well the design is received by users.

I have been gathering data from Google Analytics, Fullstory, and Adobe Analytics. Fullstory helps me to understand and interpret what users are thinking at any given point. Funnel analysis is important for e-commerce design as it provides the most basic and universal evidence for making data-driven optimizations. Watching user videos, incorporating funnels, and analyzing data contribute to the best results when improving features.

 

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The first slide displays Fullstory’s dashboard, which enables UX designers to filter specific segments and watch video playbacks of those segments. It also allows me to easily set up funnels at the dashboard level, so I can see where and how users bounce out of the experience.

The second image shows Fullstory’s heatmap that tracks major buttons on the website for me to understand their click rates.

I find it useful to use page data and page views, durations, and bounce rates from Google Analytics to identify which parts of the experience are causing the most issues. It’s important to prioritize fixing these major issues first, and then collaborate with the business team to make specific improvements. Google Analytics provides a clear overview of site performance issues.

Project Description

These tools help to achieve quantitative study results and prevent bias that traditional face-to-face interviews may bring. Updating or designing new features or capabilities without first looking into data would be risk taking and lacking solid comparison of the outcomes.

  • Google Analytics
  • Adobe Analytics
  • Fullstory User Study

Skills: Research, Data Analytics