Usefulness

Usefulness measures whether users see your product as genuinely helpful. It reflects how well the experience supports their goals and whether it feels worth returning to.Use this metric when validating new features, testing early MVPs, or assessing products after launch. It’s especially helpful for understanding if you're solving real problems, not just delivering functionality.If something isn't useful, users won’t stick with it. Even a well-designed experience won’t matter if it doesn’t deliver value where it counts.Interpreting the ResultsUse this key to understand what your Usefulness score means and how to interpret that for your product experience:How to Calculate UsefulnessThe Usefulness metric measures how well a product or feature balances ease of use with the ability to meet users’ needs—based on their own perception of usability and utility.Set up questionsTo measure Usefulness, use two Likert scale questions: one asking participants to rate how easy the feature was to use, and the other asking how well it provided the functionality or features they needed.These questions should appear directly after participants interact with the product or feature, and can be delivered through a remote usability test or survey.Collect dataIn this example, participants used a new feature that allows users to reserve a try-on appointment at a local store.After completing the task, they rated both the Ease of Use and Effectiveness of the feature using 5-point Likert scales.Plug data into the formulaAfter collecting responses on a survey, utilize the following formula to calculate the usefulness of your designs:Calculate the Usefulness ScoreOnce you've calculated the easiness and effectiveness scores, the overall Usefulness score is simply the average of the two:This results in a Usefulness score of 79%, which is considered Good on a scale from Very Poor to Very Good. It suggests that most participants found the feature both simple to use and valuable in achieving their goal.When to Use Usefulness MetricsUsefulness UX metrics help measure how effectively your product fulfills user needs and achieves its intended purpose. By tracking these metrics, you can determine how valuable your product is to your audience, identify gaps in functionality, and refine your design to enhance usability and satisfaction. High usefulness scores indicate that your product aligns well with user goals, improving adoption and loyalty. Here are some common use cases for measuring usefulness:User WorkflowsUsefulness metrics can measure how well your product supports users in completing end-to-end workflows, such as filling out forms, making purchases, or managing accounts. Streamlined workflows ensure users can achieve their goals with minimal friction and effort.Core FeaturesMetrics like Task Success Rate and Feature Usage Frequency can help gauge how well your product's primary features meet user needs. Tracking usefulness ensures that the core functionality aligns with user expectations and solves their problems effectively.Problem ResolutionUsefulness metrics can evaluate how effectively your product helps users resolve issues, whether through support tools, troubleshooting guides, or self-service features. A well-designed resolution process ensures users can overcome challenges independently and efficiently.Example of Using Usefulness to Test an E-commerce Brand's New FeatureAn e-commerce clothing brand called Getup introduced a new “Try On in Store” feature that lets users send clothing items they find online to a nearby retail location for in-person try-ons. To ensure this cross-channel experience felt intuitive and valuable, the team turned to the Usefulness metric.The SetupUsefulness is calculated using the UX-Lite method, which pairs two core questions:Ease of useHow much do you agree with the following statement?“This website is easy to use.”EffectivenessHow much do you agree with the following statement?”This website’s features meet my needs.”The ResultsThe Likert scale ratings produced the following results:These responses generate an Ease Score and an Effectiveness Score, which are then averaged to produce a single Usefulness score:The Try On in Store feature received a Usefulness score of 79%, rated Good on the Glare scaleParticipants reported an Ease Score of 81.5%, indicating they had little trouble navigating the interface and selecting a nearby store and timeThe Effectiveness Score, slightly lower at 76.5%, suggested minor friction—most often related to questions about how item availability would be confirmed at the storeUsers responded positively to the concept, with many saying it “bridged the gap” between online browsing and in-store shoppingThe ImpactThese findings helped the Getup team prioritize adding more real-time inventory messaging and clearer confirmation steps. The solid Ease and Effectiveness ratings showed that the design was working well, but that addressing uncertainty around follow-through could make the feature even more valuable.SourceHelio SurveyCSVHow to Use AI to Measure UsefulnessUsing the Likert scale questions 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 Usefulness score, and check out the type of output it would produce:Technicals for Measuring UsefulnessThe code snippets below show how UX metrics can be measured using data from a survey platform. Take a peak into the development of these metrics, and even become a contributor in ourpublic repo.Data StructureHere’s a breakdown of all the properties within the Usefulness data model:Net UsefulnessTheNet Usefulnessscore calculates the usefulness of the product or feature based on user impressions. It is derived from the sum of positive impressions minus the sum of neutral and negative impressions.ImpressionsTheimpressionsdata captures how users perceive the usefulness of the product, ranging from "very useful" to "useless."NPSNet Promoter Score (NPS) measures how likely users are to recommend the product based on their perceived usefulness. NPS scores are divided intoPromoters(9-10),Passives(7-8), andDetractors(0-6).[\n {\n \u0022net_usefulness\u0022: {\n \u0022very_useful\u0022: 0.45,\n \u0022somewhat_useful\u0022: 0.25,\n \u0022neutral\u0022: 0.15,\n \u0022somewhat_useless\u0022: 0.10,\n \u0022useless\u0022: 0.05\n },\n \u0022nps\u0022: {\n \u0022promoters\u0022: 0.28,\n \u0022passives\u0022: 0.50,\n \u0022detractors\u0022: 0.22\n }\n }\n]\nParsing DataParsing data from aUsefulnessmetric survey involves assessing users’ perceptions of how effective and practical the product is for their needs. The following data points are collected:Thequestionsparameter includes:NPS: Measuring likelihood to recommend based on usefulness.Likert Scale: Capturing how users rate the usefulness of the product.class UxMetric\n def usefulness_score(questions)\n impressions = questions[:net_usefulness]\n very_useful = impressions[:very_useful]\n somewhat_useful = impressions[:somewhat_useful]\n neutral = impressions[:neutral]\n somewhat_useless = impressions[:somewhat_useless]\n useless = impressions[:useless]\n\n # Calculate Net Usefulness\n net_usefulness = (very_useful + somewhat_useful) - \n (neutral + somewhat_useless + useless)\n\n # Calculate NPS based on promoters and detractors\n nps = questions[:nps]\n promoters = nps[:promoters]\n detractors = nps[:detractors]\n\n {\n net_usefulness: net_usefulness,\n nps_score: promoters,\n total_usefulness_score: net_usefulness + promoters - detractors\n }\n end\nendValidationTo validateUsefulnessdata, the survey should include:The function checks for the presence of the Likert scale and NPS, ensuring that both metrics are captured correctly.function isValidUsefulnessQuestions(questions) {\n if (!questions.net_usefulness || !questions.nps) {\n return false;\n }\n\n const impressions = questions.net_usefulness;\n if (!impressions.very_useful || !impressions.useless) {\n return false;\n }\n\n const nps = questions.nps;\n if (!nps.promoters || !nps.detractors) {\n return false;\n }\n\n return true;\n}Score TranslationThe finalUsefulnessscore is translated into qualitative categories:This categorization helps identify how effectively the product meets user needs.function translateUsefulnessScore(score) {\n if (score.net_usefulness \u003e 0.30) return 'High Usefulness';\n else if (score.net_usefulness \u003e= 0.10) return 'Average Usefulness';\n else return 'Low Usefulness';\n}Formula for Net UsefulnessThe finalUsefulnessscore is translated into qualitative categories:This categorization helps identify how effectively the product meets user needs.function calculateNetUsefulness(impressions, nps) {\n const net_usefulness = (impressions.very_useful + impressions.somewhat_useful) -\n (impressions.neutral + impressions.somewhat_useless + impressions.useless);\n const total_score = net_usefulness + nps.promoters - nps.detractors;\n\n return total_score;\n}For example, if we have the following values:The code for the net usefulness score would be: (see example at right)const impressions = {\n very_useful: 0.45,\n somewhat_useful: 0.25,\n neutral: 0.15,\n somewhat_useless: 0.10,\n useless: 0.05\n};\n\nconst nps = { promoters: 0.28, detractors: 0.22 };\n\nconst totalUsefulnessScore = calculateNetUsefulness(impressions, nps);\nconsole.log(totalUsefulnessScore); // Outputs 0.61 (61% total usefulness score)Templates & 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 SkillsUsefulness measures whether users feel your product actually helps them get things done 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 measure perceived usefulnessFind out which features users see as valuable vs. unnecessaryTrack usefulness scores across product changesUse usefulness data to guide what to build or cutDrop it into your LLM and start asking questions right away.