{"id":260904,"date":"2025-02-24T23:07:33","date_gmt":"2025-02-24T23:07:33","guid":{"rendered":"https:\/\/userpilot.com\/blog\/behavioral-attitudinal-data\/"},"modified":"2026-04-03T10:44:37","modified_gmt":"2026-04-03T10:44:37","slug":"behavioral-attitudinal-data","status":"publish","type":"post","link":"https:\/\/userpilot.com\/blog\/behavioral-attitudinal-data\/","title":{"rendered":"What, Why, and How to Combine Behavioral and Attitudinal Data to Make Objective UX Decisions"},"content":{"rendered":"<p>Ask users what they think about a product, and they\u2019ll give you opinions. Track how they use it, and you\u2019ll see a different story.<\/p>\n<p>Users often struggle to explain what\u2019s wrong with an experience. They might mention obvious frustrations, but deeper issues might go unnoticed. So if you rely only on attitudinal data (what they say) or behavioral data (what they do), you&#8217;ll have a real hard time making smart <a href=\"https:\/\/userpilot.com\/role\/ux-design\/\" target=\"_blank\" rel=\"noopener noreferrer\">UX design<\/a> decisions.<\/p>\n<p>That\u2019s why the best approach is to combine both! In this guide, I will explain attitudinal and behavioral data, why they need to work together, and how to use them to improve the user experience.<\/p>\n<h2 id=\"3f1fj\">What are attitudinal and behavioral data?<\/h2>\n<p>Users experience products in two ways: what they <em>think <\/em>is happening and how they <em>interact<\/em>. Sometimes, these align. Other times, they don\u2019t. That\u2019s why it\u2019s key to understand both perspectives when collecting data:<\/p>\n<ul>\n<li><strong>Attitudinal data:<\/strong> Captures what users say they think or feel about their experience. It comes from surveys, interviews, and <a href=\"https:\/\/userpilot.com\/blog\/customer-feedback-form\/\" target=\"_blank\" rel=\"noopener noreferrer\">feedback forms<\/a>. For example, a user might say they find a dashboard \u201cconfusing\u201d or a feature \u201cuseful.\u201d<\/li>\n<li><strong>Behavioral data:<\/strong> Tracks what users do in a product. It includes <a href=\"https:\/\/userpilot.com\/blog\/glossary-what-is-event-tracking\/\" target=\"_blank\" rel=\"noopener noreferrer\">event tracking<\/a>s and <a href=\"https:\/\/userpilot.com\/blog\/session-recordings\/\" target=\"_blank\" rel=\"noopener noreferrer\">session recordings<\/a> that capture clicks, scrolls, and drop-offs. For example, users might frequently abandon a setup process, even if they never mention it in a survey.<\/li>\n<\/ul>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/attitudinal-behavioral-research-userpilot_c1f1e3a25708456534ff44bae3407162_800.png 1x, https:\/\/images.storychief.com\/account_6827\/attitudinal-behavioral-research-userpilot_c1f1e3a25708456534ff44bae3407162_1600.png 2x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/attitudinal-behavioral-research-userpilot_c1f1e3a25708456534ff44bae3407162_800.png 1x, https:\/\/images.storychief.com\/account_6827\/attitudinal-behavioral-research-userpilot_c1f1e3a25708456534ff44bae3407162_1600.png 2x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/attitudinal-behavioral-research-userpilot_c1f1e3a25708456534ff44bae3407162_800.png\" alt=\"attitudinal vs behavioral data\" \/><\/picture><\/figure>\n<p>Now, let\u2019s explore how they work and what they bring to UX research.<\/p>\n<h3 id=\"34tpq\">Attitudinal research methods: Understand what users say<\/h3>\n<p>Attitudinal research is all about getting inside your users\u2019 heads, so you can understand their thoughts, feelings, and frustrations. It focuses on <em>why <\/em>they act the way they do, rather than just tracking what happens.<\/p>\n<p>Here\u2019s how different methods help you find those insights:<\/p>\n<ul>\n<li><strong><a href=\"https:\/\/userpilot.com\/blog\/user-surveys\/\" target=\"_blank\" rel=\"noopener noreferrer\">Surveys<\/a> <\/strong>\u2013 These are best for gathering structured feedback at scale. For example, an NPS survey asks \u201cHow likely are you to recommend us?\u201d, and gives you a quick read on user satisfaction. The only catch is that because responses are limited to pre-set questions, you might miss unexpected insights.<\/li>\n<li><a href=\"https:\/\/userpilot.com\/blog\/user-research\/\" target=\"_blank\" rel=\"noopener noreferrer\"><strong>User interviews<\/strong> <\/a>\u2013 Want to go deep? Interviews are your go-to. These one-on-one chats let you explore direct user feedback in detail. You can ask open-ended questions (&#8220;Tell me about a time you used this feature&#8230;&#8221;) and follow up on their answers to get the real story. They are more time-consuming than the survey but much more insightful.<\/li>\n<li><strong><a href=\"https:\/\/userpilot.com\/blog\/usability-testing\/\" target=\"_blank\" rel=\"noopener noreferrer\">Usability tests (with verbal feedback)<\/a> &#8211; <\/strong>This is where you watch users actually use your product, and \u201cthink aloud\u201d as they do. It\u2019s one of the best ways to catch usability issues that surveys and interviews might miss. But a big challenge with this is getting people to participate. Especially in B2B, where users are busy and emails can be ignored.<\/li>\n<\/ul>\n<p>Userpilot&#8217;s own UX researcher, Lisa, found this out firsthand. She needed participants for usability testing, but emails weren&#8217;t cutting it. Switching to <a href=\"https:\/\/userpilot.com\/\">Userpilot<\/a> for sending in-app survey invitations solved the problem, boosting her response rate by 4X. This highlights how crucial the right channel is for reaching your target users.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/image8_100e2492fe47e9d25867f26894706554_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/image8_100e2492fe47e9d25867f26894706554_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/image8_100e2492fe47e9d25867f26894706554_800.png\" alt=\"usability test survey in Userpilot for attitudinal research\" \/><\/picture><\/figure>\n<figure class=\"embed strchf-type-embed regular strchf-size-regular strchf-align-center\">\n<div class=\"embed-container\">\n<div class=\"bookmark-container\" style=\"display: flex;\">\n<p>&nbsp;<\/p>\n<div class=\"bookmark-focusable\" style=\"user-select: none; transition: background 20ms ease-in 0s; cursor: pointer; width: 100%; display: flex; flex-wrap: wrap-reverse; align-items: stretch; text-align: left; overflow: hidden; border: 1px solid rgba(55, 53, 47, 0.16); border-radius: 3px; position: relative; color: inherit;\">\n<div style=\"flex: 4 1 180px; padding: 12px 14px 14px; overflow: hidden; text-align: left;\">\n<div class=\"bookmark-title\" style=\"font-size: 14px; line-height: 20px; color: #37352f; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; min-height: 24px; margin-bottom: 2px;\">How UX Researchers Can 4X Their Usability Test Response Rates With Userpilot<\/div>\n<div class=\"bookmark-description\" style=\"font-size: 12px; line-height: 16px; color: rgba(55, 53, 47, 0.6); height: 32px; overflow: hidden;\">Learn how Userpilot helped Lisa, a UX researcher, quadruple usability test response rates by recruiting participants in-app.<\/div>\n<div class=\"bookmark-domain\" style=\"display: flex; margin-top: 6px;\">\n<div style=\"font-size: 12px; line-height: 16px; color: #37352f; white-space: nowrap; overflow: hidden; text-overflow: ellipsis;\">userpilot.com<\/div>\n<\/div>\n<\/div>\n<div class=\"bookmark-image\" style=\"flex: 1 1 180px; display: block; position: relative;\">\n<div style=\"position: absolute; top: 0; left: 0; right: 0; bottom: 0;\">\n<div style=\"width: 100%; height: 100%;\"><img decoding=\"async\" style=\"display: block; object-fit: cover; border-radius: 1px; background: white; width: 100%; height: 100%;\" role=\"presentation\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2024\/04\/how-ux-researchers-can-4x-their-usability-test-response-rates-with-userpilot-1_5591b97a32023f52e23f7d1e401a232b_2000.png\" \/><\/div>\n<\/div>\n<\/div>\n<\/div>\n<p>&nbsp;<\/p>\n<\/div>\n<\/div>\n<\/figure>\n<ul>\n<li><strong><a href=\"https:\/\/userpilot.com\/blog\/product-feedback-form\/\" target=\"_blank\" rel=\"noopener noreferrer\">Customer feedback forms<\/a><\/strong> \u2013 Think of these as digital suggestion boxes. A simple <em>\u201cWhat\u2019s one thing we could improve?\u201d<\/em> can uncover surprising issues and ideas you\u2019d never considered. Because they\u2019re open-ended, users can share whatever is on their minds. But that also means you\u2019ll need to sift through a lot of responses to find the gems.<\/li>\n<\/ul>\n<h3 id=\"2ls0r\">Behavioral research methods: <strong>Analyze user behavior data<\/strong><\/h3>\n<p>Users might say they love a feature, but do they actually use it? Behavioral research focuses on answering that question.<\/p>\n<p>From key <a href=\"https:\/\/userpilot.com\/blog\/behavioral-analytics\/\">behavioral analytics insights<\/a> like usage patterns, drop-off points, etc., you can find areas for improvement that surveys alone might miss.<\/p>\n<p>Here are a few ways you can collect <a href=\"https:\/\/userpilot.com\/blog\/behavioral-data-types\/\" target=\"_blank\" rel=\"noopener noreferrer\">different types of behavioral data<\/a>:<\/p>\n<ul>\n<li><a href=\"https:\/\/userpilot.com\/blog\/auto-capture\/\" target=\"_blank\" rel=\"noopener noreferrer\"><strong>Event tracking<\/strong> <strong>(autocapture)<\/strong><\/a> \u2013 With autocapture, you automatically record every user interaction, like button clicks, form submissions, and feature usage. So instead of guessing what users engage with the most, you can quickly spot patterns and focus on what matters.<\/li>\n<li><strong>Session replays<\/strong> \u2013<a href=\"https:\/\/userpilot.com\/blog\/session-replay-for-enterprise\/\" target=\"_blank\" rel=\"noopener noreferrer\"> Playback user sessions<\/a> to watch them navigate your product in real time. It\u2019s like having a usability test running in the background, only with real users, in real situations. Watching where users hesitate, rage-click, or backtrack is a great way to understand their frustrations firsthand.<\/li>\n<\/ul>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/userpilot-session-replay_658cfc75b85cfb4a904986939d5fe655_800.jpg 1x, https:\/\/images.storychief.com\/account_6827\/userpilot-session-replay_658cfc75b85cfb4a904986939d5fe655_1600.jpg 2x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/userpilot-session-replay_658cfc75b85cfb4a904986939d5fe655_800.jpg 1x, https:\/\/images.storychief.com\/account_6827\/userpilot-session-replay_658cfc75b85cfb4a904986939d5fe655_1600.jpg 2x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/userpilot-session-replay_658cfc75b85cfb4a904986939d5fe655_800.jpg\" alt=\"userpilot session replay\" \/><\/picture><\/figure>\n<ul>\n<li><strong><a href=\"https:\/\/userpilot.com\/blog\/funnel-analysis\/\" target=\"_blank\" rel=\"noopener noreferrer\">Funnel analysis<\/a><\/strong> \u2013 Funnels are great for tracking how users move through key workflows and where they abandon a process. If most users abandon a process at the same step, that\u2019s a red flag. Maybe the instructions aren\u2019t clear; maybe there\u2019s too much friction. Either way, <a href=\"https:\/\/userpilot.com\/blog\/funnel-analysis\/\">funnel analysis helps<\/a> you spot the problem before it starts costing you users.<\/li>\n<\/ul>\n<p>Behavioral data is important because it gives you hard evidence of how people interact with your product. It makes it so much easier to know exactly which <a href=\"https:\/\/userpilot.com\/blog\/feature-prioritization\/\" target=\"_blank\" rel=\"noopener noreferrer\">features to prioritize<\/a>, what obstacles to remove, and what parts of the experience need your attention first.<\/p>\n<h2 id=\"6chc4\">Why should you combine behavioral and attitudinal customer data?<\/h2>\n<p>It&#8217;s simple: you need both to truly understand your users. Here are the concrete reasons why you should do so:<\/p>\n<ul>\n<li><strong><a href=\"https:\/\/userpilot.com\/blog\/root-cause-analysis\/\" target=\"_blank\" rel=\"noopener noreferrer\">Find the root cause<\/a>:<\/strong> Imagine users report that a feature is confusing (attitudinal). Behavioral data, like session replays, can then pinpoint exactly where the confusion arises \u2013 a poorly placed button, unclear instructions, etc. You get the full story, not just a symptom. As our customers put it:<\/li>\n<\/ul>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/userpilot-session-replay-testimonial_ec07c1949ea60d3bd15c65f59f05de95_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/userpilot-session-replay-testimonial_ec07c1949ea60d3bd15c65f59f05de95_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/userpilot-session-replay-testimonial_ec07c1949ea60d3bd15c65f59f05de95_800.png\" alt=\"userpilot-session-replay-testimonial\" \/><\/picture><\/figure>\n<ul>\n<li><strong>Validate your assumptions:<\/strong> Don&#8217;t assume you know why users behave a certain way. If users say they don&#8217;t use a feature (attitudinal), check if that&#8217;s true by looking at the <a href=\"https:\/\/userpilot.com\/blog\/product-usage\/\" target=\"_blank\" rel=\"noopener noreferrer\">product usage<\/a> data (behavioral). Maybe they just haven&#8217;t discovered it yet! This prevents costly misinterpretations.<\/li>\n<li><strong>Improve decision-making for product development, UX design<\/strong>,<strong> etc.:<\/strong> Want to prioritize the right features and improvements? When <a href=\"https:\/\/userpilot.com\/blog\/user-feedback\/\" target=\"_blank\" rel=\"noopener noreferrer\">user feedback<\/a> and <a href=\"https:\/\/userpilot.com\/blog\/quantitative-data\/\">quantitative data like<\/a> usage patterns align, you have solid evidence to guide your decisions. This reduces risk and increases your chances of building something users will use and love.<\/li>\n<\/ul>\n<p>That\u2019s exactly how Cyberbiz used Userpilot to redesign their admin panel. Instead of just guessing which features to improve, they focused on analyzing product usage trends to see which ones customers found most valuable.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/image9_71c25ff2ff47ef7b5f792e0c634b7f75_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/image9_71c25ff2ff47ef7b5f792e0c634b7f75_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/image9_71c25ff2ff47ef7b5f792e0c634b7f75_800.png\" alt=\"using product usage on Userpilot for combining Behavioral and Attitudinal Data\" \/><\/picture><\/figure>\n<p>They also paired these insights with attitudinal research: <a href=\"https:\/\/userpilot.com\/blog\/in-app-surveys\/\" target=\"_blank\" rel=\"noopener noreferrer\">in-app surveys to collect customer feedback<\/a>. By combining what they learned from both <a href=\"https:\/\/userpilot.com\/blog\/product-usage-metrics\/\" target=\"_blank\" rel=\"noopener noreferrer\">product usage data<\/a> (behavioral) and surveys (attitudinal), the team knew exactly where to focus their efforts. The result: a smart redesign of their admin panel that made those key features more accessible and engaging for users.<\/p>\n<figure class=\"embed strchf-type-embed regular strchf-size-regular strchf-align-center\">\n<div class=\"embed-container\">\n<div class=\"bookmark-container\" style=\"display: flex;\">\n<p>&nbsp;<\/p>\n<div class=\"bookmark-focusable\" style=\"user-select: none; transition: background 20ms ease-in 0s; cursor: pointer; width: 100%; display: flex; flex-wrap: wrap-reverse; align-items: stretch; text-align: left; overflow: hidden; border: 1px solid rgba(55, 53, 47, 0.16); border-radius: 3px; position: relative; color: inherit;\">\n<div style=\"flex: 4 1 180px; padding: 12px 14px 14px; overflow: hidden; text-align: left;\">\n<div class=\"bookmark-title\" style=\"font-size: 14px; line-height: 20px; color: #37352f; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; min-height: 24px; margin-bottom: 2px;\">How CYBERBIZ Revamped Their Admin Panel With Userpilot<\/div>\n<div class=\"bookmark-description\" style=\"font-size: 12px; line-height: 16px; color: rgba(55, 53, 47, 0.6); height: 32px; overflow: hidden;\">Learn how CYBERBIZ used <a href=\"https:\/\/userpilot.com\/blog\/introducing-userpilot-analytics\/\">Userpilot analytics<\/a>, feedback, and engagement features to redesign their key functionality and improve its adoption.<\/div>\n<div class=\"bookmark-domain\" style=\"display: flex; margin-top: 6px;\">\n<div style=\"font-size: 12px; line-height: 16px; color: #37352f; white-space: nowrap; overflow: hidden; text-overflow: ellipsis;\">userpilot.com<\/div>\n<\/div>\n<\/div>\n<div class=\"bookmark-image\" style=\"flex: 1 1 180px; display: block; position: relative;\">\n<div style=\"position: absolute; top: 0; left: 0; right: 0; bottom: 0;\">\n<div style=\"width: 100%; height: 100%;\"><img decoding=\"async\" style=\"display: block; object-fit: cover; border-radius: 1px; background: white; width: 100%; height: 100%;\" role=\"presentation\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2024\/09\/how-cyberbiz-revamped-their-admin-panel-with-userpilot-1_56b9d502fbf1f1696f2ce3e4dd462a29_2000.png\" \/><\/div>\n<\/div>\n<\/div>\n<\/div>\n<p>&nbsp;<\/p>\n<\/div>\n<\/div>\n<\/figure>\n<h2 id=\"75urd\">How to combine attitudinal and behavioral research methods to make UX decisions?<\/h2>\n<p>Now that we know why both types of data matter, the next step is figuring out how to use them together effectively. The key is to use each type of data to inform and refine the other, <a href=\"https:\/\/userpilot.com\/blog\/how-to-create-a-feedback-loop\/\" target=\"_blank\" rel=\"noopener noreferrer\">creating a continuous feedback loop<\/a>.<\/p>\n<h3 id=\"2ahrl\">Leverage user behavioral data to guide attitudinal research<\/h3>\n<p>Our UX researcher, Lisa Ballantyne, and the team find that analyzing behavioral data is invaluable for framing attitudinal research questions. We start by digging into what users are doing before we try to understand why.<\/p>\n<p>For example, we have various dashboard templates. Using features like trend analysis, we can see which templates are hits, which ones are only used by a few power users, and which ones gather dust.<\/p>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/trend-analysis-to-see-feature-usage-trend-of-users-across-different-plans_602aaf9a6d58e25e382070aa992d26be_800.png 1x, https:\/\/images.storychief.com\/account_6827\/trend-analysis-to-see-feature-usage-trend-of-users-across-different-plans_602aaf9a6d58e25e382070aa992d26be_1600.png 2x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/trend-analysis-to-see-feature-usage-trend-of-users-across-different-plans_602aaf9a6d58e25e382070aa992d26be_800.png 1x, https:\/\/images.storychief.com\/account_6827\/trend-analysis-to-see-feature-usage-trend-of-users-across-different-plans_602aaf9a6d58e25e382070aa992d26be_1600.png 2x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/trend-analysis-to-see-feature-usage-trend-of-users-across-different-plans_602aaf9a6d58e25e382070aa992d26be_800.png\" alt=\"Userpilot trend analysis dashboard for behavioral data\" \/><\/picture><\/figure>\n<p>This behavioral data shapes our questions and helps us uncover user preferences. Let&#8217;s say the &#8220;Expansion Revenue &amp; Upgrades&#8221; template is underused; we don&#8217;t just generally ask about dashboards.<\/p>\n<p>We get specific:<\/p>\n<ul>\n<li>Use analytics to pinpoint specific user behaviors (e.g., low usage of a feature, high drop-off rates on a page).<\/li>\n<li>Craft survey and interview questions directly related to those observed behaviors: &#8220;Why haven&#8217;t you used this feature?&#8221; &#8220;What difficulties did you encounter on this page?&#8221;<\/li>\n<\/ul>\n<h3 id=\"bvqpr\">Use attitudinal research to identify problem areas and guide behavioral testing<\/h3>\n<p>At Userpilot, we don&#8217;t just use behavioral data to guide our attitudinal research\u2014we also use attitudinal research to guide our behavioral testing. It&#8217;s a two-way street!<\/p>\n<p>Here&#8217;s how our <a href=\"https:\/\/userpilot.com\/blog\/what-is-a-product-designer\/\">product designer Sean<\/a> Cummins put it into practice:<\/p>\n<ul>\n<li><strong>Start with attitudinal research:<\/strong> I use surveys, interviews, and usability testing to gather feedback on user experience. This helps us pinpoint potential problem areas, like features that users find difficult to use or pages with high drop-off rates. For example, via <a href=\"https:\/\/userpilot.com\/blog\/types-of-nps-surveys\/\" target=\"_blank\" rel=\"noopener noreferrer\">NPS surveys<\/a>, I can segment distractors to identify common issues among them.<\/li>\n<\/ul>\n<figure class=\"image strchf-type-image regular strchf-size-regular strchf-align-center\"><picture><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/nps-responses_f4b4a58334e77e0d5acf213bf1e81e9d_800.png 1x\" media=\"(max-width: 768px)\" \/><source srcset=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/nps-responses_f4b4a58334e77e0d5acf213bf1e81e9d_800.png 1x\" media=\"(min-width: 769px)\" \/><img decoding=\"async\" src=\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2026\/04\/nps-responses_f4b4a58334e77e0d5acf213bf1e81e9d_800.png\" alt=\"Userpilot NPS dashboard with user feedback for attitudinal research\" \/><\/picture><\/figure>\n<ul>\n<li><strong>Use those insights to design behavioral tests:<\/strong> I use the feedback from our attitudinal research to design targeted behavioral tests. For example, if users report struggling with a specific task, I might create a usability test to observe how they interact with that task in a real-world setting.<\/li>\n<li><strong>Combine the data to get the full picture:<\/strong> By combining attitudinal and behavioral data, I can get a more complete understanding of user needs and pain points. This helps us make more informed design decisions and create products that are both user-friendly and effective.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Get the full picture of your users. Learn how to combine behavioral and attitudinal data for better UX research and smarter product decisions.<\/p>\n","protected":false},"author":68,"featured_media":260906,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"categories":[770],"tags":[7024,429,201,236,536],"class_list":["post-260904","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ux-analytics","tag-behavioral-data","tag-user-behavior","tag-user-experience","tag-user-feedback","tag-ux-design"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.2 (Yoast SEO v27.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>How to Combine Behavioral and Attitudinal Data for UX Decisions<\/title>\n<meta name=\"description\" content=\"Get the full picture of your users. 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