Measuring the User Experience - Deepstash

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Introduction to main definitions and myths

Usability: the ability of a user to accomplish a task successfully

UX: entire interaction of a user using a product, including thoughts, feelings, perceptions

Metric - way of evaluating a particular phenomenon

Myths:

  1. Too much time to collect data -> Data can be collected in a few extra mins during an interview or testing session
  2. Too much money -> Even free tools offer reliable insights
  3. Not useful when focusing on new improvements -> Improvements need to have a baseline when measured throughout the change
  4. Data doesn't help understand causes -> It can if done properly with qualitative data

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More myths about collecting UX data

5.Too noisy -> You don't need to measure everything, only what is important

6.You can trust your gut -> No, you cannot, we are biased

7.They don't apply to new products -> They do because they set baselines for future improvements

8.No metrics for our specific issues -> There is a metric for everything

9.Not appreciated by management -> If presented properly it should be

10.Small sample size -> You don't need a big sample size to use UX metrics, even

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Types of data in UX metrics

Independent variables - you can control in your studies (e.g. age of participants)

Dependent variables: you cannot control, you get as a result of the experiment (e.g. success rate)

Data types:

  • nominal/categorical: unordered groups (e.g. gender). Cannot be compared against each other
  • ordinal: it can be compared against each other but the distance between the values is not meaningful (e.g. excellent, good, fair, poor)
  • interval: differences between values are meaningful but there is no 0 point (e.g. freezing point of water is not the absence of heat)
  • ratio: they have an absolute 0 (e.g height)

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IDEAS CURATED BY

magdamihalache

User Researcher, passionate about behaviours and building the right products. I 'stash' about research, self-development and education.

CURATOR'S NOTE

You cannot improve what you cannot measure.

Magda Mihalache's ideas are part of this journey:

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