Category
Data Analysis
Duration
5 weeks
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Data Analysis
Tableau Analysis, Event Documentation and Heuristic Evaluation for central user flows
What?
Setting up continuous usability benchmarking to systematically and data-driven analyze the use of central flows and features.
Why?
The goal is to gain a better understanding of how users interact with content and features in order to reveal weaknesses in navigation and the learning experience. This will support targeted optimizations in the future to simplify access to content and improve the overall experience.
How?
Event tracking in the app to monitor user activity in central flows and features
Analyzing flows based on the ten UX heuristics to identify concrete strengths and weaknesses, prioritize improvements, and make progress measurable over time
What?
Setting up continuous usability benchmarking to systematically and data-driven analyze the use of central flows and features.
Why?
The goal is to gain a better understanding of how users interact with content and features in order to reveal weaknesses in navigation and the learning experience. This will support targeted optimizations in the future to simplify access to content and improve the overall experience.
How?
Event tracking in the app to monitor user activity in central flows and features
Analyzing flows based on the ten UX heuristics to identify concrete strengths and weaknesses, prioritize improvements, and make progress measurable over time
Analysed Flows
The black post-its mark the most important user flows in the app, with our focus for this UX audit on the first four of them.
Analysed Flows
The black post-its mark the most important user flows in the app, with our focus for this UX audit on the first four of them.
Tableau Analysis
Using Tableau, the tracked events in the app were analyzed and evaluated. Based on this, detailed user flows and funnels were created and missing Events were documented to ensure the data could be monitored reliably over time.
Tableau Analysis
Using Tableau, the tracked events in the app were analyzed and evaluated. Based on this, detailed user flows and funnels were created and missing Events were documented to ensure the data could be monitored reliably over time.
The 10 Heuristics
For this first UX Audit we used the 10 Heuristics defined by the NN Group. These help to evaluate and improve user interfaces to make them understandable, efficient, and enjoyable to use.
The 10 Heuristics
For this first UX Audit we used the 10 Heuristics defined by the NN Group. These help to evaluate and improve user interfaces to make them understandable, efficient, and enjoyable to use.
Heuristic Evaluation
Each of the four flows was evaluated in a dedicated sheet based on the 10 UX heuristics. For every heuristic, detailed questions were marked as passed, failed, or not relevant. The results were combined into a severity rating and an overall UX score with grade.
Heuristic Evaluation
Each of the four flows was evaluated in a dedicated sheet based on the 10 UX heuristics. For every heuristic, detailed questions were marked as passed, failed, or not relevant. The results were combined into a severity rating and an overall UX score with grade.
Results
UX Benchmarking
Through Event Analysis in Tableau, we were able to answer key questions such as:
At which points do users drop off in the process?
In which flows are important events missing?
Which features are used less frequently than expected?
UX Heuristics
The UX Scores and Evaluations gave us a clear overview of which areas met expectations and which needed improvement, especially regarding usage frequency. These insights strengthened our results from the benchmarking phase and helped us set standards for more informed, data-driven design decisions in the future.
Results
UX Benchmarking
Through Event Analysis in Tableau, we were able to answer key questions such as:
At which points do users drop off in the process?
In which flows are important events missing?
Which features are used less frequently than expected?
UX Heuristics
The UX Scores and Evaluations gave us a clear overview of which areas met expectations and which needed improvement, especially regarding usage frequency. These insights strengthened our results from the benchmarking phase and helped us set standards for more informed, data-driven design decisions in the future.
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