{"id":7130,"date":"2026-03-24T01:24:02","date_gmt":"2026-03-24T01:24:02","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/drop-off-rate\/"},"modified":"2026-03-24T01:24:02","modified_gmt":"2026-03-24T01:24:02","slug":"drop-off-rate","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/drop-off-rate\/","title":{"rendered":"Drop-off Rate: What It Is, Key Features, Benefits, Use Cases, and How It Fits in CRO"},"content":{"rendered":"\n

Drop-off Rate is one of the most actionable concepts in Conversion & Measurement<\/strong> because it pinpoints where prospects stop progressing toward a goal. Whether that goal is a purchase, a lead submission, an account signup, or a key product action, Drop-off Rate turns \u201csomething feels wrong\u201d into a measurable, diagnosable problem.<\/p>\n\n\n\n

In CRO<\/strong>, Drop-off Rate is rarely the final KPI by itself. Instead, it\u2019s a diagnostic lens that tells you where<\/em> the conversion experience breaks and how much<\/em> that break is costing you. Modern Conversion & Measurement<\/strong> strategies rely on this metric to prioritize testing, improve UX, reduce friction, and connect marketing spend to business outcomes.<\/p>\n\n\n\n

What Is Drop-off Rate?<\/h2>\n\n\n\n

Drop-off Rate<\/strong> measures the percentage of users who start a journey or reach a step, but do not continue to the next step or complete the intended action. It is most commonly used in funnels (multi-step sequences), forms, checkouts, onboarding flows, and content-to-conversion paths.<\/p>\n\n\n\n

At its core, Drop-off Rate answers a simple question: \u201cWhere are we losing people, and how many?\u201d<\/strong> In business terms, a high Drop-off Rate means you are paying to acquire traffic or attention but failing to convert that interest into revenue, leads, or activation.<\/p>\n\n\n\n

In Conversion & Measurement<\/strong>, Drop-off Rate is a bridge between behavioral data (what users did) and performance outcomes (what the business earned). In CRO<\/strong>, it helps teams focus optimization efforts on the steps with the highest leverage\u2014where small improvements can produce outsized conversion gains.<\/p>\n\n\n\n

A common way to express it in a step-based funnel is:<\/p>\n\n\n\n

    \n
  • Drop-off Rate (step A \u2192 step B) = (Users at step A \u2212 Users at step B) \/ Users at step A<\/strong><\/li>\n<\/ul>\n\n\n\n

    Why Drop-off Rate Matters in Conversion & Measurement<\/h2>\n\n\n\n

    Drop-off Rate matters because it provides specificity<\/strong>. Overall conversion rate can hide serious issues: you might be converting \u201cokay\u201d while bleeding potential customers at a particular step, device type, or traffic source. Strong Conversion & Measurement<\/strong> practice breaks performance into stages so you can understand why<\/em> outcomes changed.<\/p>\n\n\n\n

    From a business value perspective, Drop-off Rate helps you:<\/p>\n\n\n\n

      \n
    • Protect marketing ROI by reducing wasted clicks and sessions.<\/li>\n
    • Increase revenue without increasing ad spend by improving flow efficiency.<\/li>\n
    • Identify friction points that harm trust (surprise fees, unclear policies, confusing forms).<\/li>\n
    • Prioritize the right fixes by quantifying impact per step.<\/li>\n<\/ul>\n\n\n\n

      In competitive markets, the advantage often comes from execution details: faster pages, clearer value propositions, fewer form fields, better error handling, and smoother checkout experiences. CRO<\/strong> teams use Drop-off Rate to locate these opportunities, validate hypotheses, and measure improvements with confidence in their Conversion & Measurement<\/strong> framework.<\/p>\n\n\n\n

      How Drop-off Rate Works<\/h2>\n\n\n\n

      Drop-off Rate is conceptual, but it becomes practical when you apply a consistent workflow:<\/p>\n\n\n\n

        \n
      1. \n

        Input or trigger: define the journey and the goal<\/strong>\n You start by defining what \u201cprogress\u201d means: a funnel (e.g., product page \u2192 cart \u2192 checkout \u2192 purchase), an onboarding path (signup \u2192 verify email \u2192 first project), or a form (start \u2192 submit). In Conversion & Measurement<\/strong>, clarity here prevents reporting noise and misaligned KPIs.<\/p>\n<\/li>\n

      2. \n

        Analysis: capture events and measure step-to-step movement<\/strong>\n Instrument each step with event tracking (page views, clicks, form starts, form submits, payments completed). Then calculate Drop-off Rate between steps and segment by device, channel, landing page, geo, new vs returning users, and more. In CRO<\/strong>, segmentation is often where the \u201creal problem\u201d is revealed.<\/p>\n<\/li>\n

      3. \n

        Execution: diagnose causes and run improvements<\/strong>\n Drop-off Rate doesn\u2019t tell you why<\/em> users leave; it tells you where to look<\/em>. Teams then use qualitative and technical methods\u2014session replays, user testing, surveys, QA, performance audits\u2014to identify friction and implement changes.<\/p>\n<\/li>\n

      4. \n

        Output: track lift and downstream outcomes<\/strong>\n The outcome isn\u2019t just a lower Drop-off Rate; it\u2019s improved conversions, improved lead quality, better activation, and more efficient acquisition. A mature Conversion & Measurement<\/strong> practice ties reduced drop-off to revenue, CAC, LTV, and retention\u2014especially when CRO<\/strong> work impacts multiple steps.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

        Key Components of Drop-off Rate<\/h2>\n\n\n\n

        To use Drop-off Rate well, you need more than a single number. The following components make it reliable and actionable:<\/p>\n\n\n\n

        Data and instrumentation<\/h3>\n\n\n\n
          \n
        • Clear event definitions (what counts as \u201cstep reached\u201d or \u201cstep completed\u201d)<\/li>\n
        • Consistent naming conventions and documentation<\/li>\n
        • Cross-domain tracking where needed (payment providers, subdomains)<\/li>\n
        • Deduplication logic (avoid counting the same action twice)<\/li>\n<\/ul>\n\n\n\n

          Funnel and journey design<\/h3>\n\n\n\n
            \n
          • A defined funnel model (linear funnel, branching flow, optional steps)<\/li>\n
          • Clear success criteria for each step (e.g., \u201caddress submitted\u201d vs \u201caddress page viewed\u201d)<\/li>\n<\/ul>\n\n\n\n

            Segmentation and context<\/h3>\n\n\n\n
              \n
            • Channel\/source segmentation (paid search vs organic vs email)<\/li>\n
            • Device and browser segmentation (mobile issues often spike Drop-off Rate)<\/li>\n
            • New vs returning users<\/li>\n
            • Geography and language<\/li>\n<\/ul>\n\n\n\n

              Governance and responsibilities<\/h3>\n\n\n\n
                \n
              • Marketing owns messaging and traffic quality<\/li>\n
              • Product\/UX owns interaction design and clarity<\/li>\n
              • Engineering owns performance, tracking reliability, and bug fixes<\/li>\n
              • Analytics owns measurement standards within Conversion & Measurement<\/strong><\/li>\n
              • CRO<\/strong> owns hypothesis creation, experimentation, and prioritization<\/li>\n<\/ul>\n\n\n\n

                Types of Drop-off Rate<\/h2>\n\n\n\n

                Drop-off Rate can be measured in multiple contexts. These aren\u2019t \u201cofficial\u201d types in a strict taxonomy, but they are the most useful distinctions in Conversion & Measurement<\/strong> and CRO<\/strong>.<\/p>\n\n\n\n

                Step-to-step funnel Drop-off Rate<\/h3>\n\n\n\n

                Measures loss between sequential steps (e.g., checkout shipping \u2192 payment). This is the most common usage in CRO<\/strong>.<\/p>\n\n\n\n

                Page or screen Drop-off Rate<\/h3>\n\n\n\n

                Focuses on users who view a page\/screen but do not continue to the next intended action (e.g., landing page \u2192 CTA click). It\u2019s especially useful for campaign landing pages within Conversion & Measurement<\/strong>.<\/p>\n\n\n\n

                Form Drop-off Rate (field-level and submit-level)<\/h3>\n\n\n\n

                Tracks where users abandon a form: after starting, at certain fields, or after validation errors. This is high-impact for lead gen and checkout optimization.<\/p>\n\n\n\n

                Onboarding or activation Drop-off Rate<\/h3>\n\n\n\n

                Measures users who sign up but fail to reach a meaningful activation milestone (first project created, first message sent, first report generated). This connects CRO<\/strong> with product-led growth and lifecycle Conversion & Measurement<\/strong>.<\/p>\n\n\n\n

                Real-World Examples of Drop-off Rate<\/h2>\n\n\n\n

                Example 1: Ecommerce checkout friction<\/h3>\n\n\n\n

                An ecommerce brand sees strong add-to-cart rates, but a sharp Drop-off Rate between \u201cshipping\u201d and \u201cpayment.\u201d Segmentation shows mobile Safari is disproportionately affected. Investigation reveals a validation bug on the address field and slow loading on the payment step. Fixing the bug and improving performance reduces Drop-off Rate and increases completed purchases\u2014classic CRO<\/strong> driven by precise Conversion & Measurement<\/strong>.<\/p>\n\n\n\n

                Example 2: Lead-gen form optimization<\/h3>\n\n\n\n

                A B2B campaign generates traffic, but the Drop-off Rate from \u201cform start\u201d to \u201cform submit\u201d is high. Field-level analysis shows drop-offs spike at \u201cphone number\u201d and \u201ccompany size.\u201d The team tests optional fields, better microcopy (\u201cUsed only for scheduling\u201d), and progressive profiling. Result: lower Drop-off Rate, more leads, and improved lead-to-meeting rate\u2014proving that Conversion & Measurement<\/strong> must include quality signals, not just volume.<\/p>\n\n\n\n

                Example 3: SaaS onboarding activation<\/h3>\n\n\n\n

                A SaaS product has good signup volume but a high Drop-off Rate before users complete \u201cfirst successful integration.\u201d Funnel analysis shows users stall at the API key step. The team adds guided setup, clearer error messages, and a fallback no-code option. Activation improves and downstream retention rises. This demonstrates how Drop-off Rate supports CRO<\/strong> beyond landing pages\u2014into product experience and lifecycle Conversion & Measurement<\/strong>.<\/p>\n\n\n\n

                Benefits of Using Drop-off Rate<\/h2>\n\n\n\n

                Using Drop-off Rate consistently delivers benefits that compound over time:<\/p>\n\n\n\n

                  \n
                • Performance improvements:<\/strong> You find the highest-impact steps to optimize instead of guessing.<\/li>\n
                • Cost savings:<\/strong> Lower Drop-off Rate means less wasted spend on traffic that never converts.<\/li>\n
                • Efficiency gains:<\/strong> Teams prioritize fixes and tests based on measurable friction.<\/li>\n
                • Better user experience:<\/strong> Reduced confusion, fewer errors, and faster task completion.<\/li>\n
                • Stronger decision-making:<\/strong> A clear Conversion & Measurement<\/strong> story about where users struggle supports better planning across marketing, product, and engineering.<\/li>\n
                • Faster CRO iteration:<\/strong> Drop-off hot spots become your testing roadmap, improving experiment velocity and relevance.<\/li>\n<\/ul>\n\n\n\n

                  Challenges of Drop-off Rate<\/h2>\n\n\n\n

                  Drop-off Rate is powerful, but it can mislead if measurement is weak or interpretation is simplistic.<\/p>\n\n\n\n

                  Technical and data challenges<\/h3>\n\n\n\n
                    \n
                  • Missing events or inconsistent tracking creates false drop-off spikes.<\/li>\n
                  • Cross-device journeys may look like drop-offs if identity isn\u2019t stitched.<\/li>\n
                  • Consent and privacy constraints can reduce observability, impacting Conversion & Measurement<\/strong> completeness.<\/li>\n
                  • Single-page apps can misreport steps without proper event design.<\/li>\n<\/ul>\n\n\n\n

                    Strategic and interpretation risks<\/h3>\n\n\n\n
                      \n
                    • Not all drop-off is \u201cbad\u201d: some users are unqualified or simply browsing.<\/li>\n
                    • Forcing users down a funnel can reduce drop-off but harm trust and long-term value.<\/li>\n
                    • Optimizing only for lower Drop-off Rate can increase low-quality conversions if incentives are misaligned\u2014an important nuance for CRO<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                      Implementation barriers<\/h3>\n\n\n\n
                        \n
                      • Step definitions differ across teams, making results hard to compare.<\/li>\n
                      • Funnel complexity (branching paths) can complicate measurement.<\/li>\n
                      • Limited traffic can make step-level insights noisy, especially for small sites.<\/li>\n<\/ul>\n\n\n\n

                        Best Practices for Drop-off Rate<\/h2>\n\n\n\n

                        These practices make Drop-off Rate more accurate and more useful in Conversion & Measurement<\/strong> and CRO<\/strong> programs:<\/p>\n\n\n\n

                          \n
                        1. \n

                          Define steps based on intent, not just page views<\/strong>\n Track meaningful events (e.g., \u201ccheckout started,\u201d \u201cpayment submitted\u201d) rather than relying only on pages.<\/p>\n<\/li>\n

                        2. \n

                          Use consistent funnel definitions and documentation<\/strong>\n Maintain a measurement spec so everyone reports Drop-off Rate the same way.<\/p>\n<\/li>\n

                        3. \n

                          Segment before you optimize<\/strong>\n Always review Drop-off Rate by device, channel, landing page, and user type. Many \u201csite-wide\u201d problems are actually segment-specific.<\/p>\n<\/li>\n

                        4. \n

                          Pair quantitative with qualitative signals<\/strong>\n Use surveys (\u201cWhat stopped you?\u201d), session analysis, support tickets, and user tests to identify causes behind drop-offs.<\/p>\n<\/li>\n

                        5. \n

                          Prioritize fixes by impact and effort<\/strong>\n Focus on steps with high traffic and high Drop-off Rate. A 5% improvement at the busiest step often beats a 30% improvement at a rarely used step.<\/p>\n<\/li>\n

                        6. \n

                          Validate changes with experimentation when feasible<\/strong>\n In CRO<\/strong>, run controlled tests for messaging and UX changes; use staged rollouts for technical fixes while monitoring Drop-off Rate and downstream KPIs.<\/p>\n<\/li>\n

                        7. \n

                          Monitor both immediate and downstream outcomes<\/strong>\n A reduced Drop-off Rate should ideally improve revenue, lead quality, activation, and retention\u2014not just the next-step completion.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                          Tools Used for Drop-off Rate<\/h2>\n\n\n\n

                          Drop-off Rate is typically measured and improved through a toolkit that supports both analysis and action:<\/p>\n\n\n\n

                            \n
                          • Analytics tools:<\/strong> Funnel reports, event tracking, segmentation, cohort views, and path analysis to quantify Drop-off Rate within Conversion & Measurement<\/strong>.<\/li>\n
                          • Tag management systems:<\/strong> Controlled deployment of tracking events, versioning, and governance to reduce measurement errors.<\/li>\n
                          • Product analytics \/ event pipelines:<\/strong> Reliable event capture for apps and multi-step flows; critical when CRO<\/strong> extends into onboarding and activation.<\/li>\n
                          • Experimentation platforms:<\/strong> A\/B and multivariate testing to validate improvements and prevent regressions.<\/li>\n
                          • UX research tools:<\/strong> Heatmaps, scroll maps, session replays, and on-page surveys to uncover friction driving drop-off.<\/li>\n
                          • CRM and marketing automation:<\/strong> Connect funnel step completion to lead quality, pipeline progression, and lifecycle outcomes\u2014closing the loop in Conversion & Measurement<\/strong>.<\/li>\n
                          • Reporting dashboards:<\/strong> Shared visibility for stakeholders, with segmented Drop-off Rate and supporting KPIs.<\/li>\n<\/ul>\n\n\n\n

                            Metrics Related to Drop-off Rate<\/h2>\n\n\n\n

                            Drop-off Rate is most meaningful when interpreted alongside supporting metrics:<\/p>\n\n\n\n

                              \n
                            • Conversion rate:<\/strong> The ultimate outcome; Drop-off Rate explains where<\/em> conversion is lost.<\/li>\n
                            • Step completion rate:<\/strong> The complement to Drop-off Rate for each step.<\/li>\n
                            • Abandonment rate:<\/strong> Often used for carts, checkouts, or forms; closely related but may be defined differently.<\/li>\n
                            • Bounce rate and engagement:<\/strong> Useful for diagnosing top-of-funnel drop-offs on landing pages.<\/li>\n
                            • Exit rate:<\/strong> Helpful for identifying last pages before sessions end, especially on content-heavy sites.<\/li>\n
                            • Time to complete step:<\/strong> Longer times often correlate with confusion or technical issues.<\/li>\n
                            • Error rate \/ validation failures:<\/strong> Essential for form and checkout diagnosis.<\/li>\n
                            • Page speed and performance metrics:<\/strong> Slow experiences can directly increase Drop-off Rate, especially on mobile.<\/li>\n
                            • Revenue per visitor (RPV) and average order value (AOV):<\/strong> Ensure CRO<\/strong> efforts improve value, not just completion.<\/li>\n
                            • Lead-to-opportunity and opportunity-to-close rates:<\/strong> For B2B, validates that reduced Drop-off Rate produces qualified pipeline.<\/li>\n
                            • Customer acquisition cost (CAC) and ROAS:<\/strong> Demonstrate the financial impact of fixing drop-offs within Conversion & Measurement<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                              Future Trends of Drop-off Rate<\/h2>\n\n\n\n

                              Drop-off Rate is evolving as measurement, privacy, and personalization change:<\/p>\n\n\n\n

                                \n
                              • AI-assisted diagnosis and prioritization:<\/strong> Pattern detection across segments can highlight where Drop-off Rate shifts and suggest likely drivers (performance, UX, traffic quality), speeding up CRO<\/strong> triage.<\/li>\n
                              • Personalized journeys:<\/strong> As experiences adapt by user intent and lifecycle stage, Drop-off Rate will be tracked across dynamic paths rather than one fixed funnel.<\/li>\n
                              • Privacy-first measurement:<\/strong> Consent limitations and reduced third-party tracking push teams toward first-party data, modeled insights, and stronger instrumentation discipline in Conversion & Measurement<\/strong>.<\/li>\n
                              • Server-side and event-based tracking:<\/strong> More robust event capture reduces false drop-offs caused by blocked scripts, improving reliability.<\/li>\n
                              • Quality-focused optimization:<\/strong> Teams will increasingly pair Drop-off Rate improvements with quality and retention metrics to avoid \u201chollow conversions,\u201d aligning CRO<\/strong> with long-term value.<\/li>\n<\/ul>\n\n\n\n

                                Drop-off Rate vs Related Terms<\/h2>\n\n\n\n

                                Drop-off Rate vs Bounce Rate<\/h3>\n\n\n\n

                                Bounce rate<\/strong> typically describes sessions that leave after viewing a single page (or without a second interaction, depending on measurement). Drop-off Rate<\/strong> is broader and step-based: users can interact, browse multiple pages, and still drop off before the next funnel step. In Conversion & Measurement<\/strong>, bounce rate is top-of-funnel, while Drop-off Rate can occur anywhere.<\/p>\n\n\n\n

                                Drop-off Rate vs Exit Rate<\/h3>\n\n\n\n

                                Exit rate<\/strong> is the percentage of pageviews that end on a specific page. It is page-centric. Drop-off Rate<\/strong> is journey-centric: it measures failure to progress in a defined path. Exit rate can hint at where users leave; Drop-off Rate quantifies loss between intended steps\u2014often more actionable for CRO<\/strong>.<\/p>\n\n\n\n

                                Drop-off Rate vs Churn<\/h3>\n\n\n\n

                                Churn<\/strong> measures customers leaving over time (subscription cancellations, inactivity). Drop-off Rate<\/strong> typically measures abandonment within a conversion or activation flow. Both are loss metrics, but they operate at different lifecycle stages. Strong Conversion & Measurement<\/strong> connects them: reducing activation drop-off can reduce later churn.<\/p>\n\n\n\n

                                Who Should Learn Drop-off Rate<\/h2>\n\n\n\n
                                  \n
                                • Marketers:<\/strong> To diagnose landing page and campaign funnel friction, protect ROAS, and improve Conversion & Measurement<\/strong> reporting.<\/li>\n
                                • Analysts:<\/strong> To design reliable funnel definitions, ensure event integrity, and translate Drop-off Rate into business impact.<\/li>\n
                                • Agencies:<\/strong> To prioritize optimization roadmaps, communicate opportunities clearly, and deliver measurable CRO<\/strong> outcomes.<\/li>\n
                                • Business owners and founders:<\/strong> To understand where growth is constrained and where investment (UX, engineering, messaging) will yield the highest return.<\/li>\n
                                • Developers:<\/strong> To implement accurate event tracking, fix technical sources of drop-off, and support experimentation\u2014key enablers of CRO<\/strong> and trustworthy Conversion & Measurement<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                                  Summary of Drop-off Rate<\/h2>\n\n\n\n

                                  Drop-off Rate<\/strong> measures the share of users who fail to progress from one step to the next in a defined journey. It matters because it reveals where you are losing revenue, leads, or activation\u2014often more clearly than overall conversion rate alone. Within Conversion & Measurement<\/strong>, Drop-off Rate provides step-level visibility and segmentation insights. Within CRO<\/strong>, it guides prioritization, testing, and improvements that reduce friction and increase meaningful outcomes.<\/p>\n\n\n\n

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

                                  1) What is Drop-off Rate and how is it calculated?<\/h3>\n\n\n\n

                                  Drop-off Rate is the percentage of users who reach a step but don\u2019t continue to the next step or complete the goal. A common calculation is: (Users at step A \u2212 Users at step B) \/ Users at step A.<\/p>\n\n\n\n

                                  2) Is a high Drop-off Rate always a problem?<\/h3>\n\n\n\n

                                  Not always. Some users are unqualified or researching. In Conversion & Measurement<\/strong>, treat high Drop-off Rate as a signal to investigate\u2014then confirm the cause with segmentation and qualitative research.<\/p>\n\n\n\n

                                  3) How does Drop-off Rate support CRO?<\/h3>\n\n\n\n

                                  In CRO<\/strong>, Drop-off Rate identifies the steps with the biggest leaks, helping you prioritize tests and fixes. It also helps you measure whether changes improved the flow, not just vanity engagement.<\/p>\n\n\n\n

                                  4) What\u2019s the difference between Drop-off Rate and abandonment rate?<\/h3>\n\n\n\n

                                  They\u2019re closely related. Abandonment rate is often used for carts, checkouts, or forms, while Drop-off Rate is a broader step-to-step funnel metric. The key is to define terms consistently in your Conversion & Measurement<\/strong> documentation.<\/p>\n\n\n\n

                                  5) How do I reduce Drop-off Rate in a checkout or form?<\/h3>\n\n\n\n

                                  Focus on clarity, speed, and trust: simplify fields, reduce surprises (fees, shipping), improve error messages, support autofill, and remove distractions. Validate improvements through CRO<\/strong> experiments when possible.<\/p>\n\n\n\n

                                  6) Why does Drop-off Rate vary so much by device or channel?<\/h3>\n\n\n\n

                                  Different devices introduce usability and performance differences, while channels bring different intent levels. Segmenting Drop-off Rate by device and source is a foundational Conversion & Measurement<\/strong> practice.<\/p>\n\n\n\n

                                  7) What should I track alongside Drop-off Rate?<\/h3>\n\n\n\n

                                  Track step completion rate, overall conversion rate, time to complete, error rate, revenue per visitor, and downstream quality metrics (lead-to-close, retention). This keeps CRO<\/strong> aligned with business outcomes rather than superficial funnel gains.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                  Drop-off Rate is one of the most actionable concepts in **Conversion & Measurement** because it pinpoints where prospects stop progressing toward a goal. Whether that goal is a purchase, a lead submission, an account signup, or a key product action, Drop-off Rate turns \u201csomething feels wrong\u201d into a measurable, diagnosable problem.<\/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":[1889],"tags":[],"class_list":["post-7130","post","type-post","status-publish","format-standard","hentry","category-cro"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7130","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=7130"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7130\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=7130"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=7130"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=7130"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}