{"id":6855,"date":"2026-03-23T15:14:28","date_gmt":"2026-03-23T15:14:28","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/engagement-time-msec\/"},"modified":"2026-03-23T15:14:28","modified_gmt":"2026-03-23T15:14:28","slug":"engagement-time-msec","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/engagement-time-msec\/","title":{"rendered":"Engagement_time_msec: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Analytics"},"content":{"rendered":"\n

Engagement_time_msec is a measurement field that represents how much time users actively engage<\/strong> with your site or app, recorded in milliseconds<\/strong>. In modern Conversion & Measurement<\/strong>, it helps teams move beyond \u201cpageviews and clicks\u201d to understand whether visitors actually spent meaningful time with content, features, or flows. In Analytics<\/strong>, it\u2019s a foundational ingredient for evaluating traffic quality, diagnosing UX friction, and building audiences that reflect real interest\u2014not just accidental landings.<\/p>\n\n\n\n

Engagement_time_msec matters because many marketing decisions depend on distinguishing attention<\/em> from exposure<\/em>. Two campaigns might drive the same number of sessions, but the one producing higher Engagement_time_msec often delivers more qualified users, stronger downstream conversion potential, and clearer insight into which experiences deserve investment.<\/p>\n\n\n\n

\n\n\n\n

What Is Engagement_time_msec?<\/h2>\n\n\n\n

Engagement_time_msec<\/strong> is a numeric value that quantifies active engagement duration<\/strong> for a user, typically at the event level and commonly aggregated at session, page\/screen, or user levels. \u201cActive\u201d is the key idea: it aims to measure time when the user is meaningfully interacting with the experience (for example, the page is in focus, the app is foregrounded, or interaction signals are present), rather than simply leaving a tab open.<\/p>\n\n\n\n

At its core, Engagement_time_msec answers: \u201cHow long did the user actually engage?\u201d<\/strong> That makes it more actionable than raw time-on-site metrics that can be inflated by idle tabs or background sessions.<\/p>\n\n\n\n

From a business perspective, Engagement_time_msec helps connect marketing effort to outcomes by serving as a leading indicator<\/strong> of intent. In Conversion & Measurement<\/strong>, it supports funnel analysis (top-of-funnel quality), content effectiveness (mid-funnel nurturing), and experience optimization (reducing abandonment). Within Analytics<\/strong>, it is often used to segment users, evaluate campaigns, and interpret conversion rates with context.<\/p>\n\n\n\n

\n\n\n\n

Why Engagement_time_msec Matters in Conversion & Measurement<\/h2>\n\n\n\n

Engagement_time_msec is strategically important because it provides a quality layer<\/strong> on top of volume metrics. In Conversion & Measurement<\/strong>, volume alone can mislead: a spike in traffic that produces low engagement frequently results in poor conversion efficiency, wasted spend, and incorrect optimization decisions.<\/p>\n\n\n\n

Key ways it drives business value:<\/p>\n\n\n\n

    \n
  • More accurate campaign evaluation:<\/strong> If a channel produces many visits but low Engagement_time_msec, it may be attracting unqualified users or mismatching intent.<\/li>\n
  • Better conversion forecasting:<\/strong> Higher engagement time often correlates with deeper consideration\u2014especially for complex products, high-ACV services, or content-led funnels.<\/li>\n
  • Sharper funnel diagnostics:<\/strong> Drops in Engagement_time_msec on key pages can signal confusing messaging, slow performance, or poor UX before conversion rates visibly decline.<\/li>\n
  • Competitive advantage through experience:<\/strong> Teams that use Analytics<\/strong> to optimize for engagement tend to improve relevance, usability, and trust\u2014advantages that compound over time.<\/li>\n<\/ul>\n\n\n\n

    In short, Engagement_time_msec strengthens Conversion & Measurement<\/strong> by revealing whether you\u2019re earning attention, not merely buying clicks.<\/p>\n\n\n\n

    \n\n\n\n

    How Engagement_time_msec Works<\/h2>\n\n\n\n

    Engagement_time_msec is best understood as a practical measurement workflow rather than a single isolated number. The specifics vary by implementation and platform, but the logic typically follows this pattern:<\/p>\n\n\n\n

      \n
    1. \n

      Input \/ trigger (user activity signals)<\/strong>\n The system observes signals such as page visibility (in-focus vs. background), foreground app usage, scrolling, clicks, navigation, and event activity. The goal is to approximate \u201cactive time\u201d rather than elapsed clock time.<\/p>\n<\/li>\n

    2. \n

      Processing (accumulation and attribution)<\/strong>\n Engagement time is accumulated in short intervals and attributed to a page\/screen, session, or event stream. Many setups attach Engagement_time_msec to events (for example, a page view or other interaction event) so that engagement can be aggregated later in Analytics<\/strong> reporting.<\/p>\n<\/li>\n

    3. \n

      Application (aggregation and segmentation)<\/strong>\n Analysts aggregate Engagement_time_msec by campaign, landing page, content category, device type, geography, or audience segment. In Conversion & Measurement<\/strong>, you might compare engaged time for converting vs. non-converting users to identify what \u201chealthy engagement\u201d looks like.<\/p>\n<\/li>\n

    4. \n

      Output \/ outcome (insights and optimization)<\/strong>\n The output is more than a number: it\u2019s a decision input. You use it to refine targeting, adjust creative, improve page UX, prioritize content updates, and create more accurate reporting models.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

      Because it is recorded in milliseconds, Engagement_time_msec is precise and flexible for roll-ups (seconds, minutes) and for weighting analyses (for example, engagement-weighted conversion rate).<\/p>\n\n\n\n

      \n\n\n\n

      Key Components of Engagement_time_msec<\/h2>\n\n\n\n

      Engagement_time_msec is not just a metric; it depends on a measurement ecosystem. The major components typically include:<\/p>\n\n\n\n

      Data collection and instrumentation<\/h3>\n\n\n\n
        \n
      • Event tagging plan:<\/strong> Defines what events exist and where engagement time is attached.<\/li>\n
      • Client-side tracking:<\/strong> Web or app instrumentation that can observe focus\/visibility and interaction patterns.<\/li>\n
      • Consent and privacy controls:<\/strong> Ensures engagement tracking aligns with policy, user consent, and regulatory requirements.<\/li>\n<\/ul>\n\n\n\n

        Analytics processing and reporting<\/h3>\n\n\n\n
          \n
        • Data model:<\/strong> Whether engagement is stored per event, session, page\/screen, or user impacts how it is interpreted in Analytics<\/strong>.<\/li>\n
        • Aggregation rules:<\/strong> Standardizes how you calculate \u201caverage engagement time,\u201d \u201ctotal engaged time,\u201d or \u201cengaged sessions.\u201d<\/li>\n<\/ul>\n\n\n\n

          Governance and responsibilities<\/h3>\n\n\n\n
            \n
          • Marketing:<\/strong> Uses Engagement_time_msec for campaign optimization and creative testing within Conversion & Measurement<\/strong>.<\/li>\n
          • Analytics\/BI:<\/strong> Validates definitions, builds dashboards, and ensures consistent interpretation.<\/li>\n
          • Product\/UX:<\/strong> Uses engagement insights to improve flows, readability, performance, and feature adoption.<\/li>\n
          • Engineering:<\/strong> Maintains tag performance, data integrity, and release-safe instrumentation.<\/li>\n<\/ul>\n\n\n\n
            \n\n\n\n

            Types of Engagement_time_msec<\/h2>\n\n\n\n

            Engagement_time_msec is a field name rather than a universal standard with formal \u201ctypes,\u201d but in practice there are important contexts and levels<\/strong> that function like variants:<\/p>\n\n\n\n

              \n
            1. \n

              Event-level Engagement_time_msec<\/strong>\n Engagement time attached to a particular event payload. Useful for detailed analysis and custom aggregation.<\/p>\n<\/li>\n

            2. \n

              Page\/screen-level engaged time<\/strong>\n Engagement attributed to a specific page or app screen. Ideal for content performance and UX diagnostics in Conversion & Measurement<\/strong>.<\/p>\n<\/li>\n

            3. \n

              Session-level engaged time<\/strong>\n Total engaged time across a session. Useful for traffic quality comparisons across channels in Analytics<\/strong>.<\/p>\n<\/li>\n

            4. \n

              User-level engaged time (cumulative)<\/strong>\n Total engaged time over a date range. Helpful for lifecycle analysis, retention, and audience building (for example, \u201chighly engaged users\u201d).<\/p>\n<\/li>\n<\/ol>\n\n\n\n

              These distinctions matter because the same raw Engagement_time_msec can tell different stories depending on the level you analyze.<\/p>\n\n\n\n

              \n\n\n\n

              Real-World Examples of Engagement_time_msec<\/h2>\n\n\n\n

              Example 1: Landing page quality for paid search<\/h3>\n\n\n\n

              A B2B SaaS team sees rising CPCs and flat conversions. In Analytics<\/strong>, they compare campaigns by Engagement_time_msec and find one keyword cluster drives high sessions but very low engaged time. The insight: the ad copy promises a feature the landing page doesn\u2019t explain well. They update messaging and add a product walkthrough section; Engagement_time_msec rises, and lead form completion improves. This is Conversion & Measurement<\/strong> in action: engagement validates message-match.<\/p>\n\n\n\n

              Example 2: Content-led funnel optimization<\/h3>\n\n\n\n

              A publisher runs two newsletter signup CTAs across articles. Variant A increases clicks, but Variant B produces higher Engagement_time_msec and better downstream subscription confirmation. They keep Variant B because it aligns with a reader\u2019s intent and doesn\u2019t interrupt reading. Engagement_time_msec helps choose the CTA that supports both experience and conversion efficiency.<\/p>\n\n\n\n

              Example 3: App onboarding friction detection<\/h3>\n\n\n\n

              A mobile app team notices a drop in trial-to-paid conversion. Engagement_time_msec by screen shows users spend unusually long time on a permissions screen, indicating confusion or hesitation. The team simplifies copy and adds a \u201cwhy we ask\u201d explanation. Engagement_time_msec on that screen decreases (less confusion), while completion and purchase increase\u2014showing how Analytics<\/strong> and Conversion & Measurement<\/strong> connect.<\/p>\n\n\n\n

              \n\n\n\n

              Benefits of Using Engagement_time_msec<\/h2>\n\n\n\n

              Engagement_time_msec can improve performance and decision quality across teams:<\/p>\n\n\n\n

                \n
              • Better targeting and budget allocation:<\/strong> Prioritize channels and audiences that generate meaningful attention, not just visits.<\/li>\n
              • Higher conversion efficiency:<\/strong> Engaged users are more likely to progress through funnels; optimizing for engagement often lifts conversion rate indirectly.<\/li>\n
              • Cost savings:<\/strong> Reduce spend on low-engagement placements, misleading traffic sources, or mismatched creative.<\/li>\n
              • Improved content and UX:<\/strong> Identify which pages, screens, or features earn time and which lose attention quickly.<\/li>\n
              • Stronger measurement clarity:<\/strong> Adds depth to Analytics<\/strong> reporting by separating \u201carrived\u201d from \u201cengaged.\u201d<\/li>\n<\/ul>\n\n\n\n
                \n\n\n\n

                Challenges of Engagement_time_msec<\/h2>\n\n\n\n

                Despite its usefulness, Engagement_time_msec has real limitations that teams must manage carefully:<\/p>\n\n\n\n

                  \n
                • Implementation differences:<\/strong> \u201cEngaged time\u201d depends on how tracking defines activity (focus, visibility, interaction). Different setups can yield different values.<\/li>\n
                • Idle time and false engagement:<\/strong> Some users may leave a page open while still in focus, inflating time without true attention.<\/li>\n
                • Cross-device and cross-domain complexity:<\/strong> Engagement may be fragmented if users switch devices or traverse domains without consistent identity and measurement design.<\/li>\n
                • Privacy and consent constraints:<\/strong> Reduced tracking or consent denial can create biased samples in Analytics<\/strong>.<\/li>\n
                • Misinterpretation risk:<\/strong> High Engagement_time_msec isn\u2019t always good; it can indicate confusion, slow performance, or difficulty finding information\u2014especially on support pages.<\/li>\n<\/ul>\n\n\n\n

                  In Conversion & Measurement<\/strong>, the goal is not \u201cmaximize time at any cost,\u201d but \u201cmeasure time to understand intent and experience.\u201d<\/p>\n\n\n\n

                  \n\n\n\n

                  Best Practices for Engagement_time_msec<\/h2>\n\n\n\n

                  To use Engagement_time_msec well, focus on consistency, context, and actionable interpretation:<\/p>\n\n\n\n

                    \n
                  1. \n

                    Define what \u201cgood engagement\u201d means by page type<\/strong>\n Product pages, blog posts, pricing pages, and checkout screens naturally have different expected engaged times. Benchmark within categories.<\/p>\n<\/li>\n

                  2. \n

                    Pair engaged time with outcomes<\/strong>\n In Analytics<\/strong>, evaluate Engagement_time_msec alongside conversions, scroll depth, key events, and retention to avoid optimizing for time alone.<\/p>\n<\/li>\n

                  3. \n

                    Use segmentation to uncover intent<\/strong>\n Compare Engagement_time_msec by:\n – channel \/ campaign\n – landing page\n – device type\n – new vs. returning users\n – geo and language<\/p>\n<\/li>\n

                  4. \n

                    Watch for \u201cconfusion time\u201d<\/strong>\n If Engagement_time_msec is high but conversions drop, inspect UX: unclear pricing, slow load, weak CTA hierarchy, or form errors.<\/p>\n<\/li>\n

                  5. \n

                    Create engagement-based audiences thoughtfully<\/strong>\n Engagement thresholds should be tested and periodically reviewed. A \u201chigh engagement\u201d audience should consistently outperform baseline on business outcomes.<\/p>\n<\/li>\n

                  6. \n

                    Standardize reporting windows and aggregation<\/strong>\n Decide whether you\u2019ll report averages (which can be skewed by outliers) or medians\/percentiles where possible. Document methodology for Conversion & Measurement<\/strong> stakeholders.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                    \n\n\n\n

                    Tools Used for Engagement_time_msec<\/h2>\n\n\n\n

                    Engagement_time_msec is typically operationalized through a stack of measurement and activation tools:<\/p>\n\n\n\n

                      \n
                    • Analytics tools:<\/strong> Collect events, attach engagement fields, and provide exploration reports for segmentation and funnels.<\/li>\n
                    • Tag management systems:<\/strong> Deploy and manage tracking logic consistently across pages and environments.<\/li>\n
                    • Product Analytics platforms:<\/strong> Especially useful in apps and SaaS products for screen-level engagement and cohort analysis.<\/li>\n
                    • Reporting dashboards and BI tools:<\/strong> Combine Engagement_time_msec with revenue, pipeline, and retention to support Conversion & Measurement<\/strong> governance.<\/li>\n
                    • A\/B testing tools:<\/strong> Validate whether changes that increase engagement also improve conversion outcomes.<\/li>\n
                    • CRM and marketing automation systems:<\/strong> Use engagement-based segments to tailor nurturing, lead scoring, and lifecycle messaging.<\/li>\n<\/ul>\n\n\n\n

                      The key is interoperability: Engagement_time_msec becomes most valuable when it flows from collection into Analytics<\/strong>, then into reporting and activation.<\/p>\n\n\n\n

                      \n\n\n\n

                      Metrics Related to Engagement_time_msec<\/h2>\n\n\n\n

                      Engagement_time_msec is best interpreted with a supporting cast of metrics:<\/p>\n\n\n\n

                        \n
                      • Engaged sessions \/ engagement rate:<\/strong> Indicates how often sessions meet an engagement threshold.<\/li>\n
                      • Average engaged time per session or per page:<\/strong> Useful for benchmarking content and landing pages.<\/li>\n
                      • Scroll depth or content consumption signals:<\/strong> Helps validate whether time reflects actual reading\/usage.<\/li>\n
                      • Key event completion rate:<\/strong> Adds behavioral confirmation to engagement (e.g., video play, add-to-cart, form step completion).<\/li>\n
                      • Conversion rate (macro and micro):<\/strong> The main Conversion & Measurement<\/strong> outcomes to correlate with engagement.<\/li>\n
                      • Cost per engaged session:<\/strong> A practical paid media efficiency metric that blends spend and quality.<\/li>\n
                      • Retention \/ repeat visit rate:<\/strong> Engaged time often predicts future visits and long-term value.<\/li>\n<\/ul>\n\n\n\n

                        In Analytics<\/strong>, combining these creates a more reliable view of user intent than any single metric.<\/p>\n\n\n\n

                        \n\n\n\n

                        Future Trends of Engagement_time_msec<\/h2>\n\n\n\n

                        Engagement_time_msec is evolving as measurement shifts toward privacy-aware, model-assisted analysis:<\/p>\n\n\n\n

                          \n
                        • AI-assisted insight generation:<\/strong> Analytics<\/strong> platforms and BI layers increasingly use machine learning to spot engagement anomalies, predict conversion likelihood, and recommend segments based on engaged behavior.<\/li>\n
                        • More event-driven measurement:<\/strong> As cookies and identifiers become less reliable, event quality and on-site signals like Engagement_time_msec become more central in Conversion & Measurement<\/strong>.<\/li>\n
                        • Personalization tied to engagement signals:<\/strong> Websites and apps will increasingly tailor experiences based on real-time engagement patterns (e.g., showing help prompts when engagement suggests friction).<\/li>\n
                        • Privacy and consent-by-design:<\/strong> Expect more emphasis on first-party data governance, minimizing unnecessary tracking, and designing engagement measurement that respects consent choices.<\/li>\n
                        • Attention quality metrics:<\/strong> Teams will look beyond time to blended \u201cattention\u201d models that incorporate interaction, depth, and task completion\u2014using Engagement_time_msec as a core input.<\/li>\n<\/ul>\n\n\n\n
                          \n\n\n\n

                          Engagement_time_msec vs Related Terms<\/h2>\n\n\n\n

                          Engagement_time_msec vs session duration<\/h3>\n\n\n\n

                          Session duration often measures elapsed time between the first and last hit\/event, which can undercount (single-page sessions) or overcount (idle tabs). Engagement_time_msec aims to reflect active<\/strong> time, making it more meaningful for Analytics<\/strong> quality analysis.<\/p>\n\n\n\n

                          Engagement_time_msec vs time on page<\/h3>\n\n\n\n

                          Time on page typically relies on timestamp differences and can be unreliable on exit pages. Engagement_time_msec is usually collected as an explicit engagement value and can be aggregated more consistently\u2014especially for single-page visits.<\/p>\n\n\n\n

                          Engagement_time_msec vs engagement rate<\/h3>\n\n\n\n

                          Engagement rate is a ratio<\/strong> describing how many sessions are considered engaged. Engagement_time_msec is a duration<\/strong> value describing how much engagement occurred. In Conversion & Measurement<\/strong>, use engagement rate to gauge breadth and Engagement_time_msec to gauge depth.<\/p>\n\n\n\n

                          \n\n\n\n

                          Who Should Learn Engagement_time_msec<\/h2>\n\n\n\n
                            \n
                          • Marketers:<\/strong> To evaluate traffic quality, improve landing page relevance, and optimize budgets using Conversion & Measurement<\/strong> signals that go beyond clicks.<\/li>\n
                          • Analysts:<\/strong> To build more nuanced Analytics<\/strong> reporting, define meaningful segments, and reduce misinterpretation of top-line volume metrics.<\/li>\n
                          • Agencies:<\/strong> To prove performance with quality indicators, diagnose landing page issues faster, and communicate value to clients with clearer measurement narratives.<\/li>\n
                          • Business owners and founders:<\/strong> To understand whether growth is driven by real interest and to prioritize investment in content, UX, and channels that produce engaged users.<\/li>\n
                          • Developers:<\/strong> To implement robust event collection, validate data integrity, and support governance for Engagement_time_msec across environments.<\/li>\n<\/ul>\n\n\n\n
                            \n\n\n\n

                            Summary of Engagement_time_msec<\/h2>\n\n\n\n

                            Engagement_time_msec measures active user engagement time in milliseconds<\/strong>, providing a practical way to quantify attention and interaction quality. It plays a critical role in Conversion & Measurement<\/strong> by helping teams judge whether campaigns and experiences attract qualified users, not just traffic. In Analytics<\/strong>, Engagement_time_msec strengthens segmentation, funnel diagnostics, UX optimization, and performance reporting when paired with conversion and behavior metrics. Used thoughtfully, it becomes a reliable bridge between marketing activity and meaningful user outcomes.<\/p>\n\n\n\n

                            \n\n\n\n

                            Frequently Asked Questions (FAQ)<\/h2>\n\n\n\n

                            1) What does Engagement_time_msec actually measure?<\/h3>\n\n\n\n

                            Engagement_time_msec measures the amount of active engagement time<\/strong> a user spends, recorded in milliseconds. It\u2019s designed to reflect meaningful interaction or attention rather than just elapsed time.<\/p>\n\n\n\n

                            2) Is higher Engagement_time_msec always better?<\/h3>\n\n\n\n

                            Not always. Higher Engagement_time_msec can indicate interest and consideration, but it can also signal confusion, slow load times, or difficulty completing tasks. In Conversion & Measurement<\/strong>, interpret it alongside conversions and key events.<\/p>\n\n\n\n

                            3) How should I use Engagement_time_msec in campaign reporting?<\/h3>\n\n\n\n

                            Use it as a quality metric in Analytics<\/strong>: compare engaged time by channel, campaign, ad group, and landing page. Consider \u201ccost per engaged session\u201d or \u201cengaged time per dollar\u201d to balance spend and attention.<\/p>\n\n\n\n

                            4) What\u2019s the difference between Engagement_time_msec and time on page?<\/h3>\n\n\n\n

                            Time on page is often a derived metric and can be unreliable on exits or single-page sessions. Engagement_time_msec is typically collected more directly as engaged time and can provide a more consistent quality signal.<\/p>\n\n\n\n

                            5) Can Engagement_time_msec help improve SEO performance?<\/h3>\n\n\n\n

                            Yes, indirectly. If organic landing pages have low Engagement_time_msec, it may indicate poor intent match, thin content, or UX issues. Improving those can raise satisfaction and conversions, strengthening overall Conversion & Measurement<\/strong> outcomes (even if engagement time itself isn\u2019t a direct ranking factor).<\/p>\n\n\n\n

                            6) How do privacy and consent affect Engagement_time_msec in Analytics?<\/h3>\n\n\n\n

                            If users decline tracking or data is modeled\/aggregated, your Engagement_time_msec reporting may reflect a partial sample. That can bias comparisons unless you apply consistent consent-aware reporting and note coverage limitations.<\/p>\n\n\n\n

                            7) What\u2019s a practical way to set engagement benchmarks?<\/h3>\n\n\n\n

                            Benchmark Engagement_time_msec by page type and intent (blog vs. pricing vs. checkout). Use historical distributions (medians\/percentiles where possible) and track changes after experiments to ensure improvements translate into Conversion & Measurement<\/strong> results.<\/p>\n","protected":false},"excerpt":{"rendered":"

                            Engagement_time_msec is a measurement field that represents **how much time users actively engage** with your site or app, recorded in **milliseconds**. In modern **Conversion & Measurement**, it helps teams move beyond \u201cpageviews and clicks\u201d to understand whether visitors actually spent meaningful time with content, features, or flows. In **Analytics**, it\u2019s a foundational ingredient for evaluating traffic quality, diagnosing UX friction, and building audiences that reflect real interest\u2014not just accidental landings.<\/p>\n","protected":false},"author":10235,"featured_media":0,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1887],"tags":[],"class_list":["post-6855","post","type-post","status-publish","format-standard","hentry","category-analytics"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/6855","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/users\/10235"}],"replies":[{"embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/comments?post=6855"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/6855\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=6855"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=6855"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=6855"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}