Attitudinal Metrics

Attitudinal metrics measure user attitude, how users feel or what they say about the product. They are usually collected through surveys, interviews or focus groups. In product management, attitudinal measures are often used to track perceived usability and customer satisfaction.

What is an example of an attitudinal measure?

A trivial common example of an attitudinal measure is a thumbs-up or thumbs-down response. Although not very specific, it can be used to measure the attitude of a small group of people easily. Other examples are the ubiquitous 5-star rating, or pictorial questionnaires such as the smiley-face (mood assessment) scale or the Self-Assessment Manikin (SAM) scale.

Attitudinal Mood Scale
A mood assessment scale is a trivial way to collect attitudinal metrics

For more systematic quantification, a common attitudinal measure is the Likert Scale, rating statements or questions from “Strongly disagree” to “Strongly agree” through various grades in between (usually with a five-point or a seven-point scale). A survey with Likert Scale ratings makes it relatively easy to quantify subjective responses, and perform attitudinal research with large groups.

What are attitudinal metrics examples?

Attitudinal metrics quantify people’s feelings about a brand, service or a product. They can be relatively simple such as a single question (for example, asking a potential customer how likely they are to purchase a specific product in the future, with the rating from “very unlikely” to “very likely”), or multi-page complex structured interviews. Some popular examples of attitudinal metrics surveys are:

When and how to collect Attitudinal Metrics

Attitudinal surveys can be conducted after a specific task (post-task), or after an entire session (post-test or post-study), or combining the two interaction points. Post-task questions are more focused and direct, but using them too frequently can interrupt the flow of a usage session and negatively impact the overall experience. Post-test surveys can provide a holistic overview of a system, but they can suffer from biases as people tend to remember later interactions more than the earlier ones. When

Attitudinal metrics are usually collected through quantitative surveys, which are excellent for capturing trends and showing the big picture view. For example, they are good to compare user happiness before and after a redesign. On the other hand, quantitative surveys do not capture the reasons behind the ratings, so you may want to complement quantitative research with follow-up interviews to go into the details with a few selected participants.

The opposite of attitudinal metrics are behavioral metrics, which look at what people actually do as opposed to what they say. Popular metrics frameworks, such as HEART usually combine attitudinal and behavioral metrics for a holistic view of a product.

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