{"id":20237,"date":"2020-01-29T15:49:15","date_gmt":"2020-01-29T15:49:15","guid":{"rendered":"https:\/\/www.arimetrics.com\/glosario-digital\/online-behavior"},"modified":"2026-09-28T07:10:06","modified_gmt":"2026-09-28T07:10:06","slug":"online-behavior","status":"publish","type":"encyclopedia","link":"https:\/\/www.arimetrics.com\/en\/digital-glossary\/online-behavior","title":{"rendered":"Online Behavior"},"content":{"rendered":"<p><img decoding=\"async\" class=\"boxpad alignright wp-image-23008 size-full\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2021\/11\/online-behavior.jpg\" alt=\"Online Behavior\" width=\"300\" height=\"300\" srcset=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2021\/11\/online-behavior.jpg 300w, https:\/\/www.arimetrics.com\/wp-content\/uploads\/2021\/11\/online-behavior-150x150.jpg 150w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/p>\n<p><strong>Definition:<\/strong><\/p>\n<p><strong>Online behavior<\/strong> is the set of actions, decisions and patterns produced when a person uses websites, apps, search engines, social networks and other digital environments. It includes anything from a search or visit to content interaction, comparison, purchase, support request or abandonment of a process.<\/p>\n<p>Some behavior can be observed through interaction data, while other behavior can only be inferred from several signals. Measurement never reproduces a person&#8217;s full intent: it depends on the available data, technical configuration, consent, device and context in which each action occurs.<\/p>\n\n<h2>What online behavior includes<\/h2>\n<p>The concept covers activities before, during and after a conversion. It is not limited to a website or a purchase process because the same need may develop across several channels and sessions.<\/p>\n<ul>\n<li><strong>Search and discovery:<\/strong> Search queries, category navigation, campaign visits and content discovery on a platform.<\/li>\n<li><strong>Navigation:<\/strong> Pages and screens viewed, sequence, depth, scrolling and time between actions.<\/li>\n<li><strong>Interaction:<\/strong> Clicks, plays, downloads, filters, forms, comments, saves and other actions defined as <a href=\"https:\/\/www.arimetrics.com\/en\/digital-glossary\/event\">events<\/a>.<\/li>\n<li><strong>Evaluation:<\/strong> Product comparisons, feature research, review reading, internal search and repeat visits.<\/li>\n<li><strong>Conversion and abandonment:<\/strong> Purchases, registrations, enquiries, subscriptions or interruptions at any stage.<\/li>\n<li><strong>Subsequent relationship:<\/strong> Product use, support requests, renewals, returns, recommendations and responses to later communications.<\/li>\n<\/ul>\n<p>An isolated action can often support several interpretations. A short visit may indicate a lack of interest, but it may also mean that the answer was found quickly. Behavior should therefore be analysed as a sequence rather than as a collection of independent metrics.<\/p>\n<h2>How online behavior is observed<\/h2>\n<p>Analysis combines quantitative and qualitative sources. Each reveals a different part of the journey and has its own limitations.<\/p>\n<ul>\n<li><strong>Web and app analytics:<\/strong> Records pages, screens, sessions, campaigns, conversions and configured events.<\/li>\n<li><strong>Product and account data:<\/strong> Connects feature use, frequency, repeat use and changes among identified users when there is a legitimate basis for doing so.<\/li>\n<li><strong>Interaction maps and recordings:<\/strong> Help study clicks, scrolling and navigation friction in samples of sessions.<\/li>\n<li><strong>Tests and qualitative research:<\/strong> Interviews, surveys, usability tests and observation explain motives that a technical trace cannot reveal.<\/li>\n<li><strong>Commercial and support data:<\/strong> Sales, returns, incidents and conversations provide the subsequent outcome of a digital interaction.<\/li>\n<\/ul>\n<p>These sources cannot always be connected to the same person. Measurement blocking, device changes, identifier deletion and privacy restrictions produce partial journeys. <strong>The absence of an event does not necessarily prove that the action did not occur.<\/strong><\/p>\n<h2>How online behavior is interpreted<\/h2>\n<p>Analysis starts with a question and a unit of observation. It may examine a session, an identified person, a group, a stage of the <a href=\"https:\/\/www.arimetrics.com\/en\/digital-glossary\/conversion-funnel\">conversion funnel<\/a> or a period. Comparing equivalent groups helps prevent a difference caused by channel, device or user type from being attributed to a design change.<\/p>\n<p>Metrics need to be connected to specific actions. Completion rate can describe a process, repeat use reflects recurrence, and an event sequence shows the order of steps. Aggregated values summarise trends but may hide minority journeys or problems affecting a particular segment.<\/p>\n<p>Observation can reveal associations, but not always causes. If people who use a feature convert more often, the relationship does not prove that the feature causes conversion. Experiments, controlled tests or qualitative research may be needed to assess causality.<\/p>\n<h2>Applications in digital marketing<\/h2>\n<p>Understanding journeys helps identify which content, processes and messages need attention. Applications include:<\/p>\n<ul>\n<li><strong>Finding friction:<\/strong> Locating errors, abandonment and repeated steps that make a task harder to complete.<\/li>\n<li><strong>Improving experiences:<\/strong> Comparing actual journeys with the intended <a href=\"https:\/\/www.arimetrics.com\/en\/digital-glossary\/ux\">user experience<\/a> and prioritising navigation or content changes.<\/li>\n<li><strong>Segmenting by action:<\/strong> Creating groups based on frequency, recurrence, feature use or journey stage through <a href=\"https:\/\/www.arimetrics.com\/en\/digital-glossary\/behavioral-segmentation\">behavioral segmentation<\/a>.<\/li>\n<li><strong>Evaluating campaigns and content:<\/strong> Analysing which sources and assets participate in visits, interactions and subsequent outcomes.<\/li>\n<li><strong>Adapting communications:<\/strong> Changing messages or sequences according to recent actions within the applicable permissions and preferences.<\/li>\n<\/ul>\n<p>The analysis is only as useful as the definitions of its events, objectives and segments. A dashboard containing many metrics cannot compensate for incomplete implementation or a misconfigured conversion.<\/p>\n<h2>Differences from related concepts<\/h2>\n<p>Online behavior is related to several disciplines but is not equivalent to them:<\/p>\n<ul>\n<li><strong>Consumer behavior:<\/strong> Studies how people select, purchase, use and evaluate products or services both online and offline.<\/li>\n<li><strong>Digital analytics:<\/strong> Covers the methods and systems used to collect, organise and interpret digital data. Online behavior is one of its subjects.<\/li>\n<li><strong>User experience:<\/strong> Concerns the perception and usability of a product or service. Behavior provides evidence but does not describe the complete experience by itself.<\/li>\n<li><strong>Behavioral segmentation:<\/strong> Groups people according to selected actions or patterns in order to analyse or adapt a strategy.<\/li>\n<li><strong>Behavioral marketing:<\/strong> Uses behavioral signals to decide on communications, content or advertising; it is an application rather than the behavior itself.<\/li>\n<\/ul>\n<p><strong>Online behavior describes what people do in digital environments; its analysis seeks to explain patterns and connect them with an objective.<\/strong> Observed activity, the tool that measures it and the strategy that uses its data are different elements.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Definition: Online behavior is the set of actions, decisions and patterns produced when a person uses websites, apps, search engines, social networks and other digital environments. It includes anything from a search or visit to content interaction, comparison, purchase, support request or abandonment of a process. Some behavior can be observed through interaction data, while [&hellip;]<\/p>\n","protected":false},"author":6,"featured_media":0,"template":"","encyclopedia-tag":[1409],"class_list":["post-20237","encyclopedia","type-encyclopedia","status-publish","hentry","encyclopedia-tag-audience-behavior"],"_links":{"self":[{"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/encyclopedia\/20237","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/encyclopedia"}],"about":[{"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/types\/encyclopedia"}],"author":[{"embeddable":true,"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/users\/6"}],"wp:attachment":[{"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/media?parent=20237"}],"wp:term":[{"taxonomy":"encyclopedia-tag","embeddable":true,"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/encyclopedia-tag?post=20237"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}