{"id":10633,"date":"2026-03-29T17:15:55","date_gmt":"2026-03-29T17:15:55","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/open-measurement-interface-definition\/"},"modified":"2026-03-29T17:15:55","modified_gmt":"2026-03-29T17:15:55","slug":"open-measurement-interface-definition","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/open-measurement-interface-definition\/","title":{"rendered":"Open Measurement Interface Definition: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Programmatic Advertising"},"content":{"rendered":"\n

Modern Paid Marketing<\/strong> depends on trustworthy measurement: was an ad actually viewable, did it run in a brand-safe environment, and can you validate performance across partners without relying on a single platform\u2019s reporting? In Programmatic Advertising<\/strong>, where inventory, bidding, and delivery happen at machine speed across many intermediaries, measurement consistency becomes even more critical.<\/p>\n\n\n\n

Open Measurement Interface Definition<\/strong> (often shortened to OMID<\/strong>) is a standard approach to measurement that helps the industry evaluate ad delivery and quality signals in a more consistent way\u2014especially in environments like mobile apps and embedded web views. Understanding the Open Measurement Interface Definition<\/strong> matters because it sits at the intersection of ad delivery and verification, helping teams reduce ambiguity, improve comparability, and strengthen decision-making across complex Programmatic Advertising<\/strong> supply chains.<\/p>\n\n\n\n

What Is Open Measurement Interface Definition?<\/h2>\n\n\n\n

Open Measurement Interface Definition (OMID)<\/strong> is a standardized interface that defines how ad measurement and verification code can access key signals about an ad impression\u2014such as viewability-related events and ad session context\u2014without requiring every measurement provider to build a separate, proprietary integration for each app or publisher environment.<\/p>\n\n\n\n

At its core, the Open Measurement Interface Definition<\/strong> is about standardization<\/strong>:<\/p>\n\n\n\n

    \n
  • It defines how<\/em> an ad session is described.<\/li>\n
  • It defines what<\/em> signals can be observed (for example, whether an ad is on-screen and for how long).<\/li>\n
  • It defines how<\/em> verification logic can be executed in a controlled way.<\/li>\n<\/ul>\n\n\n\n

    From a business perspective, the Open Measurement Interface Definition<\/strong> reduces fragmentation in measurement. Instead of integrating multiple verification SDKs (which can increase app size, increase latency, and create inconsistent results), publishers and app developers can implement a standardized interface that measurement providers can use.<\/p>\n\n\n\n

    Within Paid Marketing<\/strong>, the Open Measurement Interface Definition<\/strong> supports better quality control and reporting confidence. Within Programmatic Advertising<\/strong>, it enables verification to operate more consistently across a wide range of inventory sources and creative types.<\/p>\n\n\n\n

    Why Open Measurement Interface Definition Matters in Paid Marketing<\/h2>\n\n\n\n

    In Paid Marketing<\/strong>, measurement isn\u2019t just about reporting\u2014it directly influences budgeting, optimization, and partner selection. The Open Measurement Interface Definition<\/strong> matters because it helps make those decisions more defensible.<\/p>\n\n\n\n

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

      \n
    • Comparable quality signals across partners:<\/strong> When measurement is standardized, teams can compare viewability and related quality metrics across exchanges, apps, and publishers with fewer \u201capples vs. oranges\u201d issues.<\/li>\n
    • Reduced dependency on single-platform reporting:<\/strong> Standardized measurement reduces overreliance on any one walled garden or vendor\u2019s interpretation of delivery and quality.<\/li>\n
    • Healthier verification ecosystem:<\/strong> The Open Measurement Interface Definition<\/strong> lowers the barrier for multiple measurement providers to operate in the same environment without forcing publishers to implement many different SDKs.<\/li>\n
    • Improved optimization inputs:<\/strong> In Programmatic Advertising<\/strong>, bidding and optimization are only as good as the signals you feed into them. More consistent measurement can improve supply path decisions, creative optimization, and QA workflows.<\/li>\n<\/ul>\n\n\n\n

      Done well, the Open Measurement Interface Definition<\/strong> becomes a quiet enabler of better outcomes in Paid Marketing<\/strong>: fewer wasted impressions, cleaner reporting, and more confidence when scaling spend.<\/p>\n\n\n\n

      How Open Measurement Interface Definition Works<\/h2>\n\n\n\n

      The Open Measurement Interface Definition<\/strong> is best understood as a practical workflow that connects three parties: the ad environment (app\/site), the ad creative, and the measurement\/verification logic.<\/p>\n\n\n\n

        \n
      1. \n

        Input \/ Trigger: an ad session starts<\/strong>\n When an ad is about to render (display, video, or rich media), the environment initiates an \u201cad session\u201d concept. This session provides the context measurement needs\u2014such as what is being shown and where.<\/p>\n<\/li>\n

      2. \n

        Processing: measurement code is granted standardized access to signals<\/strong>\n Verification logic (often provided as standardized scripts or modules) is allowed to observe specific signals via the interface. The Open Measurement Interface Definition<\/strong> focuses on enabling measurement while limiting uncontrolled access\u2014supporting consistency and reducing integration chaos.<\/p>\n<\/li>\n

      3. \n

        Execution: events and signals are collected during rendering<\/strong>\n As the ad is displayed, the interface exposes events and state changes (for example, whether the ad is considered viewable, how long it stayed in view, and whether key playback milestones occurred for video).<\/p>\n<\/li>\n

      4. \n

        Output \/ Outcome: reporting and optimization inputs<\/strong>\n Measurement providers aggregate these signals into metrics and logs that marketers and analysts use for Paid Marketing<\/strong> reporting, verification, and optimization in Programmatic Advertising<\/strong>.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

        In practice, OMID is often associated with an \u201cOM SDK\u201d implementation in mobile environments, where standard web measurement tags aren\u2019t always sufficient due to app rendering complexities.<\/p>\n\n\n\n

        Key Components of Open Measurement Interface Definition<\/h2>\n\n\n\n

        While implementations vary by environment, the Open Measurement Interface Definition<\/strong> generally involves the following building blocks:<\/p>\n\n\n\n

          \n
        • Ad session model:<\/strong> A standardized way to represent an impression and its lifecycle (start, events during playback\/display, completion).<\/li>\n
        • Signal exposure rules:<\/strong> Clear definitions of what signals can be accessed and under what conditions (helping keep measurement consistent and controlled).<\/li>\n
        • Verification logic container:<\/strong> A way to run verification code in a predictable manner, so measurement providers can observe ad behavior without custom integrations for every app.<\/li>\n
        • Creative and container compatibility:<\/strong> Support for different creative formats and rendering contexts (e.g., in-app web views, native placements, video players).<\/li>\n
        • Governance and integration responsibilities:<\/strong> <\/li>\n
        • Publishers\/app developers typically implement the interface\/SDK layer. <\/li>\n
        • Measurement providers implement verification logic compatible with the standard. <\/li>\n
        • Advertisers\/agencies define verification requirements and interpret results within Paid Marketing<\/strong> goals.<\/li>\n<\/ul>\n\n\n\n

          This component view is especially relevant in Programmatic Advertising<\/strong>, where multiple stakeholders need aligned definitions to reduce discrepancies.<\/p>\n\n\n\n

          Types of Open Measurement Interface Definition<\/h2>\n\n\n\n

          The Open Measurement Interface Definition<\/strong> is a standard interface rather than a single campaign setting, so \u201ctypes\u201d are better explained as common contexts and implementation distinctions<\/strong>:<\/p>\n\n\n\n

          1) In-app vs. mobile web measurement contexts<\/h3>\n\n\n\n
            \n
          • In-app environments<\/strong> often need OMID-style standardization because ads may render in embedded views and players where traditional browser-only measurement is limited.<\/li>\n
          • Mobile web<\/strong> may rely more heavily on standard web measurement approaches, but OMID concepts still inform how verification can be made consistent across containers.<\/li>\n<\/ul>\n\n\n\n

            2) Display vs. video vs. rich media<\/h3>\n\n\n\n
              \n
            • Display:<\/strong> Focus tends to be viewability time-in-view and on-screen presence.<\/li>\n
            • Video:<\/strong> Adds playback milestones (quartiles), completion, and sometimes audibility signals depending on environment capabilities.<\/li>\n
            • Rich media:<\/strong> Requires careful handling of interactive states and expanded\/collapsed behavior.<\/li>\n<\/ul>\n\n\n\n

              3) Direct integrations vs. programmatic supply chain usage<\/h3>\n\n\n\n
                \n
              • In direct<\/strong> deals, teams may coordinate measurement requirements more tightly.<\/li>\n
              • In Programmatic Advertising<\/strong>, OMID-aligned measurement helps maintain consistency even when inventory is sourced through multiple intermediaries.<\/li>\n<\/ul>\n\n\n\n

                Real-World Examples of Open Measurement Interface Definition<\/h2>\n\n\n\n

                Example 1: Mobile app prospecting with viewability-based optimization<\/h3>\n\n\n\n

                A performance team runs app-install campaigns across multiple exchanges. Using Open Measurement Interface Definition<\/strong>-supported inventory, they can compare viewability rates more consistently across supply sources. They then downweight placements with low viewability and reallocate spend to higher-quality inventory, improving effective CPA in Paid Marketing<\/strong>.<\/p>\n\n\n\n

                Example 2: Brand campaign requiring verification across diverse app inventory<\/h3>\n\n\n\n

                A brand runs high-reach video ads via Programmatic Advertising<\/strong> and sets a verification requirement (e.g., minimum viewability threshold and fraud monitoring). With Open Measurement Interface Definition<\/strong> compatibility, measurement providers can observe standardized signals across many apps without each app needing separate vendor SDKs, reducing coverage gaps and discrepancies.<\/p>\n\n\n\n

                Example 3: Publisher reduces SDK bloat while supporting multiple verification partners<\/h3>\n\n\n\n

                A large app publisher wants to work with several measurement providers to satisfy advertiser demands. Instead of integrating multiple proprietary SDKs (which can slow release cycles and affect app performance), the publisher implements the Open Measurement Interface Definition<\/strong> once. Verification partners then plug into the standardized interface, lowering ongoing maintenance costs while keeping the publisher competitive in Programmatic Advertising<\/strong> demand.<\/p>\n\n\n\n

                Benefits of Using Open Measurement Interface Definition<\/h2>\n\n\n\n

                When adopted well, the Open Measurement Interface Definition<\/strong> can create tangible improvements across performance, operational efficiency, and user experience:<\/p>\n\n\n\n

                  \n
                • More reliable measurement for optimization:<\/strong> Better confidence in viewability and related quality metrics can improve bidding strategies and placement selection in Paid Marketing<\/strong>.<\/li>\n
                • Reduced integration complexity:<\/strong> Publishers and app developers can avoid maintaining many parallel measurement SDK integrations.<\/li>\n
                • Lower technical overhead:<\/strong> Fewer SDKs can mean less app bloat, fewer conflicts, and simpler QA cycles.<\/li>\n
                • Improved buyer confidence:<\/strong> Standardization makes it easier for agencies and advertisers to justify spend and scale campaigns in Programmatic Advertising<\/strong>.<\/li>\n
                • Better end-user experience:<\/strong> Leaner integrations and fewer competing background processes can reduce performance issues that sometimes come with heavy ad tech stacks.<\/li>\n<\/ul>\n\n\n\n

                  Challenges of Open Measurement Interface Definition<\/h2>\n\n\n\n

                  The Open Measurement Interface Definition<\/strong> is not a magic switch. Teams should be aware of practical limitations:<\/p>\n\n\n\n

                    \n
                  • Coverage isn\u2019t universal:<\/strong> Not every placement or environment supports OMID-style measurement equally. Some inventory may still have limited verification capabilities.<\/li>\n
                  • Discrepancies can still occur:<\/strong> Even with a standard, differences in interpretation, sampling, latency, or environment behavior can produce mismatches between platforms.<\/li>\n
                  • Implementation quality varies:<\/strong> A weak or outdated integration by an app\/publisher can reduce measurement accuracy and create confusing results for Paid Marketing<\/strong> teams.<\/li>\n
                  • Privacy and platform constraints:<\/strong> Mobile OS changes, consent frameworks, and sandboxing can limit what can be measured or shared.<\/li>\n
                  • Operational complexity remains:<\/strong> In Programmatic Advertising<\/strong>, measurement is only one part of the system\u2014supply path optimization, fraud defenses, and creative QA still require disciplined processes.<\/li>\n<\/ul>\n\n\n\n

                    Best Practices for Open Measurement Interface Definition<\/h2>\n\n\n\n

                    To get meaningful value from the Open Measurement Interface Definition<\/strong>, focus on operational rigor\u2014not just \u201cturning it on.\u201d<\/p>\n\n\n\n

                      \n
                    • Define measurement objectives before picking thresholds:<\/strong> Decide whether you\u2019re optimizing for viewability, completed views, brand safety, fraud reduction, or a balanced scorecard.<\/li>\n
                    • Use measurement as a decision input, not a vanity metric:<\/strong> Tie OMID-derived signals to actions (exclude placements, adjust bids, change creative rotation, refine deal lists).<\/li>\n
                    • Monitor discrepancies and investigate root causes:<\/strong> Track deltas between ad server, DSP, and verification reporting; document known causes and acceptable ranges.<\/li>\n
                    • Segment by environment and format:<\/strong> Evaluate results separately for in-app vs. mobile web, display vs. video, and different app categories to avoid misleading averages.<\/li>\n
                    • Create a QA checklist for new launches:<\/strong> Validate that measurement signals are flowing and consistent early in the campaign to prevent weeks of unusable data.<\/li>\n
                    • Align stakeholders:<\/strong> Media buyers, analysts, and dev\/ops teams should agree on how measurement will be interpreted in Paid Marketing<\/strong> reporting and Programmatic Advertising<\/strong> optimization.<\/li>\n<\/ul>\n\n\n\n

                      Tools Used for Open Measurement Interface Definition<\/h2>\n\n\n\n

                      The Open Measurement Interface Definition<\/strong> typically appears inside broader measurement and ad operations workflows. Common tool categories include:<\/p>\n\n\n\n

                        \n
                      • Ad platforms (DSPs and ad servers):<\/strong> Where impressions are bought, delivered, and logged; also where you apply targeting, bids, and pacing in Paid Marketing<\/strong>.<\/li>\n
                      • Verification and measurement platforms:<\/strong> Systems that read standardized signals to produce viewability, fraud, and brand safety indicators.<\/li>\n
                      • Analytics tools:<\/strong> Used to connect quality metrics to outcomes like conversions, retention, and revenue\u2014especially when optimizing Programmatic Advertising<\/strong> spend.<\/li>\n
                      • Mobile measurement and attribution tools (where applicable):<\/strong> Helpful for tying campaign exposure to app installs and post-install events.<\/li>\n
                      • Reporting dashboards \/ BI layers:<\/strong> To unify metrics across partners and track trends, discrepancies, and segment performance.<\/li>\n
                      • Data warehouses and governance workflows:<\/strong> To store logs, document metric definitions, and maintain consistent reporting logic across teams.<\/li>\n<\/ul>\n\n\n\n

                        Even though OMID is a standard interface, you still need a strong measurement stack around it to turn signals into decisions.<\/p>\n\n\n\n

                        Metrics Related to Open Measurement Interface Definition<\/h2>\n\n\n\n

                        The Open Measurement Interface Definition<\/strong> supports measurement signals that commonly roll up into metrics such as:<\/p>\n\n\n\n

                          \n
                        • Viewability rate:<\/strong> Share of impressions that meet a defined viewability criterion.<\/li>\n
                        • Time-in-view \/ viewable duration:<\/strong> How long the ad remained viewable (often more informative than a binary viewable\/not viewable).<\/li>\n
                        • Video completion rate and quartiles:<\/strong> Especially relevant for video-heavy Programmatic Advertising<\/strong>.<\/li>\n
                        • Invalid traffic (IVT) rate \/ fraud indicators:<\/strong> Signals that help filter low-quality or suspicious inventory.<\/li>\n
                        • Measurable rate \/ measurement coverage:<\/strong> The percentage of impressions that could be measured successfully\u2014critical for interpreting any metric honestly.<\/li>\n
                        • Discrepancy rate:<\/strong> Differences between ad server counts, DSP logs, and verification counts.<\/li>\n
                        • Cost efficiency tied to quality:<\/strong> eCPM, CPA, or CPC segmented by viewability\/fraud buckets to guide Paid Marketing<\/strong> optimization.<\/li>\n<\/ul>\n\n\n\n

                          Future Trends of Open Measurement Interface Definition<\/h2>\n\n\n\n

                          Several trends will shape how the Open Measurement Interface Definition<\/strong> is used in Paid Marketing<\/strong> going forward:<\/p>\n\n\n\n

                            \n
                          • Privacy-driven measurement constraints:<\/strong> As platforms restrict identifiers and tracking, standardized on-device signals become more important, but also more constrained. Expect continued emphasis on consent-aware measurement and aggregated reporting.<\/li>\n
                          • Automation in quality optimization:<\/strong> More DSPs will automate supply decisions using quality signals (viewability, IVT, attention proxies) as inputs to bidding and supply path optimization in Programmatic Advertising<\/strong>.<\/li>\n
                          • Attention and outcome-based measurement:<\/strong> Teams are moving beyond \u201cviewable\u201d toward \u201cmeaningful exposure,\u201d blending OMID-enabled signals with lift studies and conversion modeling.<\/li>\n
                          • Growth of in-app and CTV ecosystems:<\/strong> As budgets shift, standardization pressure increases. OMID-style approaches may remain most visible in mobile, while adjacent standards evolve for other environments.<\/li>\n
                          • AI-assisted anomaly detection:<\/strong> Machine learning will increasingly spot measurement anomalies, fraud patterns, and reporting inconsistencies\u2014turning OMID-derived signals into faster operational actions for Paid Marketing<\/strong> teams.<\/li>\n<\/ul>\n\n\n\n

                            Open Measurement Interface Definition vs Related Terms<\/h2>\n\n\n\n

                            Open Measurement Interface Definition vs Viewability<\/h3>\n\n\n\n
                              \n
                            • Viewability<\/strong> is the metric\/outcome (was the ad actually viewable, and for how long?).<\/li>\n
                            • Open Measurement Interface Definition<\/strong> is the standardized way measurement providers can access the signals needed to calculate viewability more consistently across environments.<\/li>\n<\/ul>\n\n\n\n

                              Open Measurement Interface Definition vs Ad Verification<\/h3>\n\n\n\n
                                \n
                              • Ad verification<\/strong> is the broader discipline covering viewability, fraud\/IVT, and brand safety checks.<\/li>\n
                              • The Open Measurement Interface Definition<\/strong> is an enabling standard that can make parts of verification easier to implement and more consistent, particularly in Programmatic Advertising<\/strong> mobile contexts.<\/li>\n<\/ul>\n\n\n\n

                                Open Measurement Interface Definition vs MRAID (Mobile Rich Media Ad Interface Definitions)<\/h3>\n\n\n\n
                                  \n
                                • MRAID<\/strong> focuses on how rich media ads interact with the mobile app environment (expand, resize, open browser, etc.).<\/li>\n
                                • Open Measurement Interface Definition<\/strong> focuses on measurement and verification signals. In practice, both may appear in mobile ad stacks, but they solve different problems.<\/li>\n<\/ul>\n\n\n\n

                                  Who Should Learn Open Measurement Interface Definition<\/h2>\n\n\n\n

                                  The Open Measurement Interface Definition<\/strong> is useful knowledge for multiple roles:<\/p>\n\n\n\n

                                    \n
                                  • Marketers and media buyers:<\/strong> To interpret viewability\/verification reporting and make better optimization choices in Paid Marketing<\/strong>.<\/li>\n
                                  • Analysts:<\/strong> To evaluate measurement coverage, discrepancies, and how quality signals correlate with outcomes in Programmatic Advertising<\/strong>.<\/li>\n
                                  • Agencies:<\/strong> To set measurement requirements, compare supply partners, and explain reporting to clients with confidence.<\/li>\n
                                  • Business owners and founders:<\/strong> To understand what \u201cquality inventory\u201d means and how measurement affects wasted spend and brand risk.<\/li>\n
                                  • Developers and ad ops engineers:<\/strong> To implement, validate, and troubleshoot OMID-related measurement flows in apps and ad delivery environments.<\/li>\n<\/ul>\n\n\n\n

                                    Summary of Open Measurement Interface Definition<\/h2>\n\n\n\n

                                    Open Measurement Interface Definition (OMID)<\/strong> is a standardized approach that defines how ad measurement and verification can access consistent signals about ad sessions\u2014especially in environments like mobile apps\u2014without requiring many proprietary integrations. It matters because Paid Marketing<\/strong> teams need reliable, comparable quality metrics to optimize spend, manage risk, and scale confidently. In Programmatic Advertising<\/strong>, the Open Measurement Interface Definition<\/strong> supports more consistent verification across complex supply paths, helping reduce discrepancies and improve decision-making.<\/p>\n\n\n\n

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

                                    1) What is Open Measurement Interface Definition (OMID) used for?<\/h3>\n\n\n\n

                                    Open Measurement Interface Definition<\/strong> is used to standardize how verification and measurement logic can access signals (such as viewability-related events) during ad delivery, improving consistency across environments like mobile apps.<\/p>\n\n\n\n

                                    2) Does OMID replace ad verification providers?<\/h3>\n\n\n\n

                                    No. Open Measurement Interface Definition<\/strong> is an interface\/standard that enables measurement; verification providers still apply their methodologies to produce metrics like viewability and fraud indicators.<\/p>\n\n\n\n

                                    3) How does Open Measurement Interface Definition help Programmatic Advertising?<\/h3>\n\n\n\n

                                    In Programmatic Advertising<\/strong>, inventory comes from many sources and is delivered in many environments. Open Measurement Interface Definition<\/strong> helps measurement work more consistently across that fragmentation, improving comparability and trust in reporting.<\/p>\n\n\n\n

                                    4) Is Open Measurement Interface Definition only for mobile apps?<\/h3>\n\n\n\n

                                    It\u2019s most commonly associated with in-app measurement challenges, but the concepts apply more broadly to standardized measurement across different ad rendering contexts.<\/p>\n\n\n\n

                                    5) What should a Paid Marketing team look at first when using OMID-based reporting?<\/h3>\n\n\n\n

                                    Start with measurement coverage (measurable rate)<\/strong> and discrepancy checks, then analyze viewability\/time-in-view by supply source. Without coverage context, viewability rates can be misleading for Paid Marketing<\/strong> optimization.<\/p>\n\n\n\n

                                    6) Will OMID eliminate discrepancies between DSP and verification numbers?<\/h3>\n\n\n\n

                                    It can reduce some causes of inconsistency, but it won\u2019t eliminate discrepancies entirely. Differences in counting rules, latency, sampling, and environment behavior can still create gaps.<\/p>\n\n\n\n

                                    7) How do I operationalize OMID metrics without over-optimizing for viewability?<\/h3>\n\n\n\n

                                    Use OMID-enabled quality metrics as guardrails and segmentation inputs, then optimize toward business outcomes (CPA, ROAS, lift) within Paid Marketing<\/strong>. Treat viewability as a quality filter\u2014not the sole success metric.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                    Modern **Paid Marketing** depends on trustworthy measurement: was an ad actually viewable, did it run in a brand-safe environment, and can you validate performance across partners without relying on a single platform\u2019s reporting? In **Programmatic Advertising**, where inventory, bidding, and delivery happen at machine speed across many intermediaries, measurement consistency becomes even more critical.<\/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":[1911],"tags":[],"class_list":["post-10633","post","type-post","status-publish","format-standard","hentry","category-programmatic-advertising"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/10633","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=10633"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/10633\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=10633"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=10633"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=10633"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}