Feeling

Feeling reveals the emotional tone of the experience as it’s happening. It moves beyond satisfaction and gets to the heart of what the design stirred up, calm, stress, excitement, frustration, or something else entirely.Use this metric when emotional impact is part of the goal. It’s especially useful for testing moments meant to reassure, inspire, or create trust, like onboarding, storytelling flows, or brand moments that aim to connect on a deeper level.Feeling helps you understand if the experience resonates the way you intended. It brings emotion into focus so you can design with empathy, not just efficiency.Interpreting the ResultsUse this key to understand what your Feeling score means and how to interpret that for your product experience:How to Calculate FeelingsThe Feeling metric measures the emotional response that a design evokes, focusing specifically on the positive emotions of Trust and Joy.Set up questionsTo collect this data, use a multiple choice question with eight emotion options, allowing participants to select up to three.Present this question immediately after showing the design—such as a brand element, image, or UI screen—so participants can choose the emotions they feel in the moment. Distribute the survey to your target audience via a remote testing platform to capture authentic, in-context reactionsCollect dataIn this example, participants viewed a set of brand colors and chose from eight emotions:Their selections included positive feelings like Trust and Joy, as well as other emotions such as Anticipation, Surprise, Fear, Disgust, Sadness, and Anger.Plug data into formulaFor this dataset, Trust received 30% of selections and Joy received 28% of selections. These two values are added together for the numerator, while the denominator is the sum of percentages for all eight emotions. This ensures the score reflects the proportion of positive emotional responses compared to the total emotional reactionsCalculate the Feeling scoreAdd up the sum of the positive emotion percentages as well as all emotion percentages to reveal the score:This score indicates a Poor Feeling result on a scale from Very Poor to Very Good, showing that fewer than half of the emotional responses were the desired positive feelings of Trust or Joy.When to Use Feeling MetricsFeeling metrics help evaluate how users emotionally respond to key features, workflows, or content. These metrics capture positive and negative emotions, helping teams refine designs to create experiences that build trust, satisfaction, and engagement. By tracking emotional responses, teams can identify areas that delight or frustrate users and optimize accordingly. Here are some common use cases for measuring feelings:Onboarding ExperiencesEvaluate how users feel during onboarding. Emotional responses such as confusion, frustration, or excitement can highlight whether the flow builds trust or creates barriers for new users.Product or Feature LaunchesMeasure emotional reactions to new features or updates. Feeling metrics identify whether changes spark excitement, frustration, or indifference, helping teams refine releases for maximum impact.Content or MessagingAnalyze how users emotionally respond to specific copy, imagery, or messaging. Feeling metrics reveal whether content resonates with your audience and creates the intended emotional connection.How an Ad Platform Used the Feeling Metric to Test New Brand ColorsAdvent, a B2B advertising management platform, was rolling out a brand refresh that included a bold new color palette. While internally praised for being energetic and modern, the brand team wanted to validate how the new colors emotionally resonated with users—particularly marketers and media buyers. They turned to the Feeling UX metric to capture users’ instinctive reactions before finalizing the paletteThe SetupParticipants were shown a full preview of the new brand color set within a sample interface. Using the Feeling metric, they were asked to select up to three emotional reactions from a standardized list based on Plutchik’s Wheel of Emotions: Anticipation, Trust, Joy, Surprise, Fear, Disgust, Sadness, and Anger. These responses were then tallied and used to calculate a Feeling score, defined as the percentage of positive emotions selected across all impressions.The ResultsThe responses from participants produced the following data set:We plugged the data into the Feeling formula to reveal the score:The new palette received a Feeling score of 43%, suggesting a lukewarm emotional impactTop positive emotions included Anticipation (33%), Trust (30%), and Joy (28%)However, notable percentages of users also selected Sadness (10%) and Disgust (8%), indicating emotional dissonance for some participantsSeveral users commented that the dark color combinations “felt heavy” or “clashed with the energetic tone Advent normally conveys”The ImpactThe design team used the feedback to fine-tune the brand system, softening some of the darker tones and pairing them more carefully with vibrant accents. They also added additional use-case testing with interface components to better isolate color emotion in real-world contexts. By grounding their visual identity decisions in measurable emotional feedback, Advent ensured their rebrand would inspire confidence, not confusion.SourceHelio SurveyCSVHow to Use AI to Measure FeelingsUsing the multiple choice question outlined in the How to Calculate section above, gather responses on a survey from an audience of at least 100 respondents. We find that 100 responses is statistically significant in most markets. Once the responses are collected, download the CSV file of your data report and upload it into an AI platform along with the prompt below.Copy this AI prompt to calculate your own Feelings score, and check out the type of output it would produce:Technicals for Measuring FeelingWe’ve built out a UX Metric framework that we’re using in our Helio platform. Here, we’ve laid out what we’ve done, and how other developers can use this. You can also become a Glare Code Contributor on ourUX Metric framework.How to UseFeeling Data ParserWith our framework, you can use theGlare::UxMetric::Feeling::Parsermodule to parse Feeling data.Here are the steps:First we have to require the module in order for us to use it.Then, we need to use a validdatastructure to pass into the choices parameter as an argument.When callingGlare::UxMetric::Feeling::Parser.new, we return aParser. This gives us access to a parse andvalid?method.We useparsehere in order to give us a score result, also known asGlare::UxMetric::Result.require \u0022glare/ux_metrics\u0022\n\ndata = {\n\tvery_easy: 0.1\n somewhat_easy: 0.4,\n neutral: 0.2,\n somewhat_difficult: 0.2,\n\tvery_difficult: 0.2\n}\n\nparser = Glare::UxMetrics::Feeling::Parser.new(\n\tchoices: data\n)\n\nparser.parse # Glare::UxMetric::ResultTemplates & Presentation MaterialsCreate effective presentation slides, document design concepts, and implement UX Metrics with templates and resources.We've done the work to provide professional layouts that communicate to your stakeholders. UX Metric cards clearly communicate the totals, allow space for breakdowns, and styled to allow for your own brand.Visit Findings for TemplatesTake This Further with the UX Metrics AI SkillsFeeling measures the emotional response users have to your product using survey questions turned into a single number score. TheUX Metrics AI Skillsis a package you load into your LLM so you can ask questions and get expert answers anytime.Write survey questions that capture emotional responseUnderstand which parts of your product cause friction or delightCompare feeling scores across flows or featuresConnect emotional data to design changesDrop it into your LLM and start asking questions right away.