{"id":1432,"date":"2021-04-04T10:24:21","date_gmt":"2021-04-04T07:24:21","guid":{"rendered":"https:\/\/persona.qcri.org\/blog\/?p=1432"},"modified":"2021-10-17T18:04:41","modified_gmt":"2021-10-17T15:04:41","slug":"three-data-types-for-personas","status":"publish","type":"post","link":"https:\/\/persona.qcri.org\/blog\/three-data-types-for-personas\/","title":{"rendered":"Three Data Types for Personas"},"content":{"rendered":"<h2>The Basics of Data-Driven Personas<\/h2>\n<p><a href=\"https:\/\/www.amazon.com\/Data-driven-Personas-Synthesis-Human-centered-Informatics\/dp\/1636390684\">Data-driven personas<\/a> can be generated from almost any data. Essentially, the generation consists of two steps: (1) pattern seeking, and (2) enrichment.<\/p>\n<p>The first part &#8211; <strong>pattern seeking<\/strong> &#8211; means that we need to identify some regularities (i.e., patterns) from the dataset. This is typically done using <a href=\"https:\/\/persona.qcri.org\/blog\/making-better-decisions-with-big-data-personas\/\">dimensionality reduction<\/a>, e.g., clustering, principal component analysis, or matrix factorization.<\/p>\n<p>The second part &#8211; <strong>enrichment<\/strong> &#8211; focuses on findings statistically robust associations between the patterns identified in the first step and secondary variables, such as <a href=\"https:\/\/persona.qcri.org\/blog\/elements-of-a-persona-profile\/\">demographics<\/a>. These variables are then shown as representative information in the finalized <em>persona profiles<\/em>.<\/p>\n<h2>Three Data Types for Personas<\/h2>\n<p>The three main sources of data for persona generation are:<\/p>\n<ul>\n<li><strong>survey-based data:<\/strong> this is data collected via a <a href=\"https:\/\/persona.qcri.org\/blog\/how-to-create-personas-a-list-of-common-interview-questions\/\">questionnaire<\/a> from users or customers. According to our <a href=\"https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3313831.3376502\">study<\/a>, it is the most popular source of persona data in the literature.<\/li>\n<li><strong>online and web analytics data:<\/strong> this is <a href=\"https:\/\/dl.acm.org\/doi\/10.1145\/3265986\">behavioral and demographic data<\/a> collected from online analytics or social media platforms, typically using <em>application programming interfaces<\/em> (APIs). It is, in our opinion, the most potential data for persona generation at the moment.<\/li>\n<li><strong>sensor-based data:<\/strong> this is data collected using hardware, such as GPS devices or medical sensors (e.g., FitBit). It is the most rarely used for of data. However, as Internet-of-Things (IOT) and medical\/wellness sensors are becoming more popular, this data source will also increase in potential.<\/li>\n<\/ul>\n<p>The data from these three sources is typically in <a href=\"https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3377325.3377492\">numerical format<\/a>. For surveys, Likert Scale (1-5) is often used. Online analytics platforms typically output count data (e.g., number of visits \/ views \/ clicks \/ purchases). Sensors typically output time-series data with commonly high frequency (sampling rate).<\/p>\n<p>But, it is also possible to make use of textual data. More specifically, one can analyze <a href=\"https:\/\/persona.qcri.org\/blog\/pain-points-and-personas\/\">social media comments<\/a> for persona generation. In these efforts, <em>natural language processing<\/em> (NLP) techniques can be useful, e.g., to infer the persona&#8217;s topics of interest. In addition, researchers have applied\u00a0<a href=\"https:\/\/www.researchgate.net\/profile\/Nalini-Kotamraju\/publication\/200086136_Data-driven_persona_development\/links\/55ff761108aec948c4f9b2bf\/Data-driven-persona-development.pdf\">quantification of qualitative data<\/a> (e.g., interviews) by manually coding \/ labeling the data and then using the counts as the input for quantitative analysis.<\/p>\n<h2>Want to Learn More?<\/h2>\n<p>I hope this article provided useful information for you regarding the three main data types for personas. If you are interested in learning more, I suggest you check out our <a href=\"https:\/\/persona.qcri.org\/persona-research\">persona research<\/a> for peer-reviewed research papers.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Basics of Data-Driven Personas Data-driven personas can be generated from almost any data. Essentially, the generation consists of two steps: (1) pattern seeking, and (2) enrichment. The first part &#8211; pattern seeking &#8211; means that we need to identify some regularities (i.e., patterns) from the dataset. This is typically done using dimensionality reduction, e.g., [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"default","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[3,16,7,2],"tags":[522],"class_list":["post-1432","post","type-post","status-publish","format-standard","hentry","category-data-driven-personas","category-persona-creation","category-persona-research","category-personas","tag-data-types"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Three Data Types for Personas &#8211; The Persona Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/persona.qcri.org\/blog\/three-data-types-for-personas\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Three Data Types for Personas &#8211; The Persona Blog\" \/>\n<meta property=\"og:description\" content=\"The Basics of Data-Driven Personas Data-driven personas can be generated from almost any data. 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