{"id":7048,"date":"2026-03-23T22:24:43","date_gmt":"2026-03-23T22:24:43","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/last-non-direct-click\/"},"modified":"2026-03-23T22:24:43","modified_gmt":"2026-03-23T22:24:43","slug":"last-non-direct-click","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/last-non-direct-click\/","title":{"rendered":"Last Non-direct Click: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Attribution"},"content":{"rendered":"\n

Last Non-direct Click is a commonly used concept in Conversion & Measurement that assigns a conversion\u2019s credit to the most recent non-direct<\/em> marketing interaction before the conversion happens. In other words, if a person visits your site directly right before buying (by typing the URL, using a bookmark, or clicking an untagged link), Last Non-direct Click ignores that final direct visit and credits the last identifiable channel such as organic search, paid search, email, referral, or social.<\/p>\n\n\n\n

This idea matters because \u201cdirect\u201d traffic is often a navigation behavior<\/em>, not a true marketing driver. In modern Conversion & Measurement, teams need a consistent, defensible way to connect revenue and leads back to marketing efforts. Last Non-direct Click is a straightforward Attribution approach that helps avoid over-crediting direct visits and under-crediting the campaigns that actually created demand.<\/p>\n\n\n\n

What Is Last Non-direct Click?<\/h2>\n\n\n\n

Last Non-direct Click is an Attribution rule (often used as a default in analytics reporting) that credits the conversion to the most recent touchpoint that is not direct<\/em>. If the last session is direct, the model looks back to the previous known marketing source within a defined lookback window and assigns credit there.<\/p>\n\n\n\n

The core concept is simple: direct is treated as a \u201cno new information\u201d channel<\/strong> when a user has had prior attributable interactions. This makes Last Non-direct Click especially useful in Conversion & Measurement reporting where teams want to understand which channels were most effective at driving measurable outcomes.<\/p>\n\n\n\n

From a business perspective, Last Non-direct Click answers a pragmatic question: Which marketing effort most recently influenced the customer before they returned and converted?<\/em> It\u2019s not claiming to be perfect customer-journey truth\u2014rather, it\u2019s a consistent method for day-to-day optimization and performance reporting.<\/p>\n\n\n\n

Within Conversion & Measurement, Last Non-direct Click typically appears in channel performance reports, campaign summaries, and revenue by source views. Within Attribution, it is one of the most widely discussed \u201clast-touch\u201d variants because it explicitly handles direct traffic differently.<\/p>\n\n\n\n

Why Last Non-direct Click Matters in Conversion & Measurement<\/h2>\n\n\n\n

Last Non-direct Click matters because it shapes the story your data tells. In Conversion & Measurement, the model you choose influences budget decisions, channel strategy, and perceived ROI.<\/p>\n\n\n\n

Key reasons it\u2019s strategically important:<\/p>\n\n\n\n

    \n
  • Prevents direct traffic from absorbing undue credit.<\/strong> Many users convert on a direct return visit after being influenced earlier by SEO, ads, email, or PR.<\/li>\n
  • Supports actionable channel optimization.<\/strong> Last Non-direct Click often aligns better with optimization decisions than pure last-click because it highlights the last marketing source rather than a navigation event.<\/li>\n
  • Improves reporting consistency.<\/strong> Teams need a stable Attribution rule for trending and benchmarking over time, especially across campaigns and quarters.<\/li>\n
  • Creates a defensible starting point.<\/strong> For organizations maturing their Conversion & Measurement practice, Last Non-direct Click is a pragmatic baseline before moving to multi-touch or experiment-based approaches.<\/li>\n<\/ul>\n\n\n\n

    Competitive advantage comes from making better decisions faster. When your Attribution lens over-credits \u201cdirect,\u201d you can mistakenly cut the very channels that create demand. Last Non-direct Click reduces that risk and improves marketing outcomes like efficient CAC, healthier funnel volume, and more reliable pipeline forecasts.<\/p>\n\n\n\n

    How Last Non-direct Click Works<\/h2>\n\n\n\n

    Last Non-direct Click is more conceptual than procedural, but it behaves predictably in practice. Here\u2019s a practical workflow that reflects how it is applied in Conversion & Measurement systems:<\/p>\n\n\n\n

      \n
    1. \n

      Input \/ trigger: a conversion event occurs<\/strong>\n A user completes a conversion (purchase, lead form, subscription, demo request). The system captures the session\u2019s traffic source (direct, organic, paid, email, referral, etc.) and any campaign parameters available.<\/p>\n<\/li>\n

    2. \n

      Processing: evaluate the last session\u2019s source<\/strong>\n – If the last session is non-direct<\/strong>, the conversion is credited to that source.\n – If the last session is direct<\/strong>, the system looks back to find the most recent non-direct<\/strong> source tied to that user within a lookback window.<\/p>\n<\/li>\n

    3. \n

      Application: assign the conversion credit<\/strong>\n The conversion is attributed to that last non-direct channel (and often to the associated campaign, medium, and source) for reporting in Conversion & Measurement dashboards.<\/p>\n<\/li>\n

    4. \n

      Output \/ outcome: channel performance reporting<\/strong>\n Your reports show conversions and revenue credited to channels that likely drove the user back\u2014supporting optimization decisions, budget allocation, and campaign evaluation within Attribution.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

      Two nuances are essential:\n– Lookback windows matter.<\/strong> If the earlier non-direct touchpoint falls outside the window, direct may get credit (or the conversion may be treated differently depending on the system).\n– Identification matters.<\/strong> The ability to \u201clook back\u201d depends on how users are recognized across sessions (cookies, login state, device IDs, etc.).<\/p>\n\n\n\n

      Key Components of Last Non-direct Click<\/h2>\n\n\n\n

      Although Last Non-direct Click is a concept, implementing it reliably depends on several tangible components in your Conversion & Measurement stack:<\/p>\n\n\n\n

      Data inputs<\/h3>\n\n\n\n
        \n
      • Traffic source and medium classification<\/strong> (organic, paid, email, referral, social, etc.)<\/li>\n
      • Campaign parameters<\/strong> (e.g., consistent tagging conventions)<\/li>\n
      • Referrers and landing pages<\/strong> to help validate channel grouping<\/li>\n
      • User\/session identifiers<\/strong> that connect multiple visits to the same person or device<\/li>\n<\/ul>\n\n\n\n

        Systems and processes<\/h3>\n\n\n\n
          \n
        • Analytics configuration<\/strong> that defines channel groupings and how \u201cdirect\u201d is detected<\/li>\n
        • Tagging governance<\/strong> (UTM or equivalent rules, naming standards, QA)<\/li>\n
        • Conversion definitions<\/strong> (what counts as a conversion, how it\u2019s deduplicated)<\/li>\n
        • Cross-domain and subdomain tracking<\/strong> where applicable to avoid false direct sessions<\/li>\n<\/ul>\n\n\n\n

          Team responsibilities<\/h3>\n\n\n\n
            \n
          • Marketing operations and analytics teams typically own implementation and QA<\/strong><\/li>\n
          • Channel owners own campaign tagging discipline<\/strong><\/li>\n
          • Data teams support identity resolution, pipelines, and validation<\/strong><\/li>\n
          • Leadership aligns on how Last Non-direct Click fits into Attribution decision-making<\/li>\n<\/ul>\n\n\n\n

            Types of Last Non-direct Click<\/h2>\n\n\n\n

            Last Non-direct Click doesn\u2019t have \u201ctypes\u201d in the same way as multi-touch models, but there are important variations and contexts<\/strong> that change how it behaves:<\/p>\n\n\n\n

            1) Default vs customized channel definitions<\/h3>\n\n\n\n

            Two organizations can both say they use Last Non-direct Click but get different results if:\n– one classifies certain sources as referral vs social,\n– one breaks out paid social vs organic social,\n– one treats partner links as referrals vs campaigns.<\/p>\n\n\n\n

            2) Different lookback windows<\/h3>\n\n\n\n

            A shorter window tends to increase the share of conversions credited to direct (because prior non-direct touches expire). A longer window increases the share credited to earlier marketing sources.<\/p>\n\n\n\n

            3) Session-based vs user-based evaluation<\/h3>\n\n\n\n

            Some setups focus on session history, while others use more robust user stitching (login-based). Better identity resolution generally makes Last Non-direct Click more accurate in Conversion & Measurement.<\/p>\n\n\n\n

            4) \u201cNon-direct\u201d exceptions due to tracking gaps<\/h3>\n\n\n\n

            If email links aren\u2019t tagged or some apps strip referrers, those sessions may appear as direct. This makes Last Non-direct Click sensitive to tagging and technical consistency.<\/p>\n\n\n\n

            Real-World Examples of Last Non-direct Click<\/h2>\n\n\n\n

            Example 1: SEO discovery \u2192 direct return \u2192 purchase<\/h3>\n\n\n\n
              \n
            • Day 1: User finds a blog post via organic search<\/strong>, reads, leaves. <\/li>\n
            • Day 4: User returns via direct<\/strong> and buys.\nLast Non-direct Click Attribution:<\/strong> organic search gets the conversion credit.\nConversion & Measurement value:<\/strong> SEO performance is reflected more accurately instead of being overshadowed by direct traffic.<\/li>\n<\/ul>\n\n\n\n

              Example 2: Paid search click \u2192 direct checkout later<\/h3>\n\n\n\n
                \n
              • Morning: User clicks a paid search<\/strong> ad, views product, abandons cart. <\/li>\n
              • Evening: User types the site name and completes checkout via direct<\/strong>.\nLast Non-direct Click Attribution:<\/strong> paid search gets credit.\nOutcome:<\/strong> the paid campaign looks more profitable and aligns better with how people actually shop across multiple sessions.<\/li>\n<\/ul>\n\n\n\n

                Example 3: Email campaign \u2192 direct login \u2192 subscription upgrade<\/h3>\n\n\n\n
                  \n
                • Week 1: User clicks a newsletter email<\/strong>, reads feature update. <\/li>\n
                • Week 2: User logs in directly and upgrades.\nLast Non-direct Click Attribution:<\/strong> email gets the credit (assuming tracking and lookback support it).\nAttribution insight:<\/strong> lifecycle marketing impact is visible, supporting better retention-focused budget allocation in Conversion & Measurement.<\/li>\n<\/ul>\n\n\n\n

                  Benefits of Using Last Non-direct Click<\/h2>\n\n\n\n

                  Last Non-direct Click remains popular because the benefits are practical:<\/p>\n\n\n\n

                    \n
                  • More realistic credit assignment than pure last click<\/strong> in journeys where users return directly to complete an action.<\/li>\n
                  • Better channel ROI visibility<\/strong> for SEO, email, and paid media that drive initial interest and consideration.<\/li>\n
                  • Simpler to explain than multi-touch models<\/strong>, making it useful for stakeholder alignment.<\/li>\n
                  • Improved operational efficiency<\/strong>: faster decisions when you need a consistent rule for weekly reporting.<\/li>\n
                  • Better customer understanding<\/strong>: highlights the marketing touchpoint that re-engaged the user most recently, which can inform messaging and timing.<\/li>\n<\/ul>\n\n\n\n

                    In many organizations, Last Non-direct Click is the \u201cworkhorse\u201d Attribution view used for day-to-day optimization, even if more advanced models are used for strategic analysis.<\/p>\n\n\n\n

                    Challenges of Last Non-direct Click<\/h2>\n\n\n\n

                    Despite its usefulness, Last Non-direct Click can mislead if used without context.<\/p>\n\n\n\n

                    Measurement limitations<\/h3>\n\n\n\n
                      \n
                    • Overemphasis on lower-funnel channels<\/strong>: it credits the final marketing source, often undervaluing early awareness drivers.<\/li>\n
                    • Cross-device gaps<\/strong>: if a user discovers you on mobile and converts on desktop, Last Non-direct Click may fail without identity stitching.<\/li>\n
                    • Cookie restrictions and consent<\/strong>: privacy controls can reduce your ability to connect sessions, impacting Conversion & Measurement accuracy.<\/li>\n<\/ul>\n\n\n\n

                      Tracking and implementation risks<\/h3>\n\n\n\n
                        \n
                      • Untagged campaigns inflate \u201cdirect.\u201d<\/strong> If email or social links aren\u2019t tagged, they may appear as direct and distort Attribution.<\/li>\n
                      • Referrer loss<\/strong>: apps, redirects, and some browsers can strip referrer data, turning non-direct visits into direct.<\/li>\n
                      • Cross-domain issues<\/strong>: payment providers, booking engines, and separate checkout domains can cause self-referrals or false direct sessions if not configured.<\/li>\n<\/ul>\n\n\n\n

                        Strategic risk<\/h3>\n\n\n\n
                          \n
                        • False confidence<\/strong>: teams may treat Last Non-direct Click as \u201cthe truth\u201d rather than one lens. It\u2019s best used alongside additional reporting and experimentation.<\/li>\n<\/ul>\n\n\n\n

                          Best Practices for Last Non-direct Click<\/h2>\n\n\n\n

                          To get reliable insights from Last Non-direct Click in Conversion & Measurement, focus on discipline and validation:<\/p>\n\n\n\n

                            \n
                          1. \n

                            Standardize campaign tagging<\/strong>\n – Define naming conventions for source\/medium\/campaign.\n – Enforce tagging in email, paid social, influencer, affiliate, and partner links.\n – QA links before launch.<\/p>\n<\/li>\n

                          2. \n

                            Fix cross-domain and subdomain tracking<\/strong>\n – Ensure sessions persist through checkout, booking, and authentication flows.\n – Prevent self-referrals that can disrupt Attribution.<\/p>\n<\/li>\n

                          3. \n

                            Define conversions clearly<\/strong>\n – Separate micro conversions (newsletter signup) from macro conversions (purchase).\n – Deduplicate conversions and align them with business reporting.<\/p>\n<\/li>\n

                          4. \n

                            Use multiple views for decision-making<\/strong>\n – Pair Last Non-direct Click with first-touch or position-based perspectives to understand both demand creation and demand capture.\n – Use experiments (incrementality tests) where possible to validate channel impact.<\/p>\n<\/li>\n

                          5. \n

                            Monitor \u201cdirect\u201d and investigate spikes<\/strong>\n – Sudden increases in direct traffic often signal broken tagging, referrer loss, or tracking changes.\n – Create alerts and annotations for measurement changes.<\/p>\n<\/li>\n

                          6. \n

                            Document your Attribution logic<\/strong>\n – Write down channel grouping rules, lookback assumptions, and known limitations so stakeholders interpret results correctly.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                            Tools Used for Last Non-direct Click<\/h2>\n\n\n\n

                            Last Non-direct Click is typically implemented and analyzed through a combination of systems rather than a single tool. Common tool categories in Conversion & Measurement and Attribution include:<\/p>\n\n\n\n

                              \n
                            • Analytics tools<\/strong>: session\/source tracking, channel grouping, conversion reporting, cohort analysis.<\/li>\n
                            • Tag management systems<\/strong>: consistent deployment of tracking tags, event definitions, consent logic, and QA.<\/li>\n
                            • Ad platforms<\/strong>: campaign parameters, click identifiers, and cost data needed to compute ROI under Last Non-direct Click.<\/li>\n
                            • CRM and marketing automation<\/strong>: tying leads and revenue back to acquisition sources and lifecycle interactions.<\/li>\n
                            • Data warehouses and ETL\/ELT pipelines<\/strong>: unifying cost, web analytics, and CRM outcomes for more robust Attribution reporting.<\/li>\n
                            • Reporting dashboards<\/strong>: standardized views of conversions, revenue, and CAC by channel using the Last Non-direct Click lens.<\/li>\n
                            • SEO tools<\/strong>: supporting analysis of organic channel performance that is frequently credited under Last Non-direct Click.<\/li>\n<\/ul>\n\n\n\n

                              The key is consistency: your tools must agree on channel definitions and conversion events, or Attribution becomes fragmented.<\/p>\n\n\n\n

                              Metrics Related to Last Non-direct Click<\/h2>\n\n\n\n

                              The most relevant metrics are the ones you use to judge channel performance under this Attribution approach:<\/p>\n\n\n\n

                                \n
                              • Conversions by channel (Last Non-direct Click)<\/strong>: core outcome volume by source\/medium.<\/li>\n
                              • Revenue by channel<\/strong>: attributed revenue for ecommerce or subscription upgrades.<\/li>\n
                              • Cost per acquisition (CPA) and customer acquisition cost (CAC)<\/strong>: when paired with cost data.<\/li>\n
                              • Return on ad spend (ROAS)<\/strong>: for paid channels credited by Last Non-direct Click.<\/li>\n
                              • Conversion rate by channel<\/strong>: helps evaluate traffic quality and landing page alignment.<\/li>\n
                              • Assisted conversion indicators<\/strong> (if available in your reporting): to counterbalance last-touch bias.<\/li>\n
                              • Share of direct traffic<\/strong>: diagnostic metric; changes often signal measurement issues.<\/li>\n
                              • Time lag to conversion<\/strong>: informs lookback windows and expectations for channel influence.<\/li>\n<\/ul>\n\n\n\n

                                Using these metrics consistently is central to strong Conversion & Measurement practice and helps keep Attribution debates grounded in evidence.<\/p>\n\n\n\n

                                Future Trends of Last Non-direct Click<\/h2>\n\n\n\n

                                Last Non-direct Click is evolving as measurement becomes more privacy-aware and more modeled.<\/p>\n\n\n\n

                                  \n
                                • Privacy and consent constraints<\/strong>: reduced tracking persistence can make \u201clook back to the last non-direct\u201d harder, increasing uncertainty in Conversion & Measurement.<\/li>\n
                                • Modeled and aggregated reporting<\/strong>: systems increasingly use statistical methods to fill gaps; Last Non-direct Click may be applied to modeled paths rather than fully observed ones.<\/li>\n
                                • Incrementality and experimentation<\/strong>: more teams are validating Attribution outputs with holdouts and geo tests, treating Last Non-direct Click as a reporting view\u2014not the final truth.<\/li>\n
                                • Better identity resolution<\/strong>: where compliant and appropriate, first-party data strategies (logins, customer IDs) improve cross-device understanding, making Last Non-direct Click more accurate.<\/li>\n
                                • AI-assisted insights<\/strong>: anomaly detection, tagging QA, and channel classification are becoming more automated, reducing the operational errors that distort Last Non-direct Click.<\/li>\n<\/ul>\n\n\n\n

                                  In practice, Last Non-direct Click will likely remain a widely used baseline in Conversion & Measurement, complemented by stronger experimentation and multi-model Attribution.<\/p>\n\n\n\n

                                  Last Non-direct Click vs Related Terms<\/h2>\n\n\n\n

                                  Last Non-direct Click vs Last Click Attribution<\/h3>\n\n\n\n
                                    \n
                                  • Last Click<\/strong> credits the final interaction even if it\u2019s direct. <\/li>\n
                                  • Last Non-direct Click<\/strong> ignores direct if there was a previous non-direct touchpoint.\nPractical difference:<\/strong> Last Non-direct Click typically credits SEO, email, and paid media more often, especially when customers return directly to convert.<\/li>\n<\/ul>\n\n\n\n

                                    Last Non-direct Click vs First Click (First Touch)<\/h3>\n\n\n\n
                                      \n
                                    • First Click<\/strong> credits the first known marketing interaction. <\/li>\n
                                    • Last Non-direct Click<\/strong> credits the most recent non-direct interaction.\nUse case:<\/strong> First Click is better for understanding demand creation; Last Non-direct Click is better for understanding demand capture and re-engagement within Attribution.<\/li>\n<\/ul>\n\n\n\n

                                      Last Non-direct Click vs Multi-touch Attribution<\/h3>\n\n\n\n
                                        \n
                                      • Multi-touch<\/strong> splits credit across multiple interactions using rules (linear, position-based) or data-driven methods. <\/li>\n
                                      • Last Non-direct Click<\/strong> assigns 100% of credit to one channel (the last non-direct).\nTradeoff:<\/strong> multi-touch can represent journeys better but requires more data, governance, and stakeholder buy-in; Last Non-direct Click is simpler and more operational.<\/li>\n<\/ul>\n\n\n\n

                                        Who Should Learn Last Non-direct Click<\/h2>\n\n\n\n
                                          \n
                                        • Marketers and channel managers<\/strong> need it to interpret performance reports correctly and avoid optimizing toward misleading \u201cdirect-heavy\u201d outcomes.<\/li>\n
                                        • Analysts and marketing ops teams<\/strong> need it to set up consistent Conversion & Measurement definitions, diagnose tracking issues, and communicate Attribution assumptions.<\/li>\n
                                        • Agencies<\/strong> need it to explain reporting methodology, defend results, and align clients on how credit is assigned.<\/li>\n
                                        • Business owners and founders<\/strong> benefit by understanding why \u201cdirect\u201d isn\u2019t always a marketing win and how Last Non-direct Click affects ROI decisions.<\/li>\n
                                        • Developers and data teams<\/strong> need it to implement tracking, identity resolution, cross-domain flows, and reliable data pipelines that keep Attribution accurate.<\/li>\n<\/ul>\n\n\n\n

                                          Summary of Last Non-direct Click<\/h2>\n\n\n\n

                                          Last Non-direct Click is an Attribution approach used in Conversion & Measurement that credits conversions to the most recent non-direct<\/em> marketing interaction, ignoring a final direct visit when earlier attributable sessions exist. It\u2019s valuable because it reduces the tendency to over-credit direct traffic and helps teams see which channels most recently influenced customers before conversion. While it\u2019s not a complete representation of the customer journey, it is a practical, widely used framework for performance reporting and ongoing optimization.<\/p>\n\n\n\n

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

                                          1) What does Last Non-direct Click mean in plain language?<\/h3>\n\n\n\n

                                          It means the conversion is credited to the most recent marketing-driven visit (like organic search, paid ads, or email). If the final visit is direct, the credit goes to the previous non-direct visit instead.<\/p>\n\n\n\n

                                          2) Why does Last Non-direct Click ignore direct traffic?<\/h3>\n\n\n\n

                                          Direct traffic often indicates the user already knows your brand and is simply returning to complete an action. In Conversion & Measurement, ignoring direct helps avoid giving \u201cnavigation\u201d the credit that belongs to earlier marketing influence.<\/p>\n\n\n\n

                                          3) Is Last Non-direct Click the same as last-touch Attribution?<\/h3>\n\n\n\n

                                          It\u2019s a form of last-touch Attribution, but with a specific rule: it treats direct as non-influential when another identifiable channel existed before it.<\/p>\n\n\n\n

                                          4) When should I not rely on Last Non-direct Click?<\/h3>\n\n\n\n

                                          Avoid relying on it alone when you need to understand upper-funnel impact (brand, video, PR) or when you have heavy cross-device behavior. Pair it with additional models and, ideally, incrementality testing.<\/p>\n\n\n\n

                                          5) How do tagging mistakes affect Last Non-direct Click?<\/h3>\n\n\n\n

                                          Untagged email, social, or partner links can be misclassified as direct. That causes Last Non-direct Click to assign credit incorrectly, weakening your Conversion & Measurement reporting and leading to poor budget decisions.<\/p>\n\n\n\n

                                          6) Can Last Non-direct Click work for lead generation, not just ecommerce?<\/h3>\n\n\n\n

                                          Yes. It can attribute form fills, demo requests, trials, and other lead events to the last non-direct source, which helps evaluate channel performance in B2B and service businesses.<\/p>\n\n\n\n

                                          7) How do I use Last Non-direct Click alongside other Attribution views?<\/h3>\n\n\n\n

                                          Use Last Non-direct Click for operational reporting and optimization, and compare it with first-touch or multi-touch views to understand the full funnel. Where decisions are high-stakes, validate with experiments to confirm true channel lift.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                          Last Non-direct Click is a commonly used concept in Conversion & Measurement that assigns a conversion\u2019s credit to the most recent *non-direct* marketing interaction before the conversion happens. In other words, if a person visits your site directly right before buying (by typing the URL, using a bookmark, or clicking an untagged link), Last Non-direct Click ignores that final direct visit and credits the last identifiable channel such as organic search, paid search, email, referral, or social.<\/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":[1888],"tags":[],"class_list":["post-7048","post","type-post","status-publish","format-standard","hentry","category-attribution"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7048","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=7048"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7048\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=7048"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=7048"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=7048"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}