{"id":10779,"date":"2026-03-29T22:45:00","date_gmt":"2026-03-29T22:45:00","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/omid-signal\/"},"modified":"2026-03-29T22:45:00","modified_gmt":"2026-03-29T22:45:00","slug":"omid-signal","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/omid-signal\/","title":{"rendered":"OMID Signal: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Programmatic Advertising"},"content":{"rendered":"\n

Modern Paid Marketing<\/strong> depends on reliable measurement\u2014especially when ads run inside mobile apps, where browsers, cookies, and traditional pixels don\u2019t work the same way. OMID Signal<\/strong> refers to the standardized measurement signals generated through the Open Measurement framework used by the ad verification ecosystem to determine whether an ad was actually rendered, viewable, and measurable in an in-app environment.<\/p>\n\n\n\n

In Programmatic Advertising<\/strong>, campaigns often flow through multiple intermediaries (DSPs, SSPs, exchanges, SDKs, and publishers). That complexity makes it easy for measurement to become inconsistent. OMID Signal<\/strong> matters because it helps create a more consistent \u201csource of truth\u201d for in-app viewability and verification\u2014supporting better optimization, cleaner reporting, and stronger accountability in Paid Marketing<\/strong>.<\/p>\n\n\n\n

What Is OMID Signal?<\/h2>\n\n\n\n

OMID Signal<\/strong> is the set of measurement events and data points produced when an OMID-enabled ad session runs and a verification script (from an independent measurement provider) observes the ad\u2019s rendering and viewability conditions inside an app.<\/p>\n\n\n\n

At a beginner level, you can think of it like this:<\/p>\n\n\n\n

    \n
  • The app shows an ad.<\/li>\n
  • A standardized measurement layer observes what happens.<\/li>\n
  • The resulting observation data becomes the OMID Signal<\/strong> used for reporting and optimization.<\/li>\n<\/ul>\n\n\n\n

    The core concept<\/h3>\n\n\n\n

    The core idea is standardization<\/strong>. Instead of every SDK or vendor inventing its own in-app measurement approach, OMID provides a common interface for communicating what the ad did on screen (rendered state, geometry, exposure time, and similar viewability-related conditions). The OMID Signal<\/strong> is what measurement and analytics systems ultimately consume.<\/p>\n\n\n\n

    The business meaning<\/h3>\n\n\n\n

    From a business perspective, OMID Signal<\/strong> helps answer questions that directly affect spend:<\/p>\n\n\n\n

      \n
    • Did the ad actually appear on screen?<\/li>\n
    • Was it viewable long enough to count?<\/li>\n
    • Is the inventory behaving normally or suspiciously?<\/li>\n
    • Are reported impressions comparable across supply sources?<\/li>\n<\/ul>\n\n\n\n

      Where it fits in Paid Marketing<\/h3>\n\n\n\n

      In Paid Marketing<\/strong>, especially on mobile, OMID Signal<\/strong> supports measurement integrity\u2014helping marketers compare placements, control waste, and justify investment decisions with higher confidence.<\/p>\n\n\n\n

      Its role inside Programmatic Advertising<\/h3>\n\n\n\n

      In Programmatic Advertising<\/strong>, buying happens at scale and in milliseconds. OMID Signal<\/strong> provides standardized measurement inputs that can be used to evaluate supply quality, inform optimization, and support verification and auditing workflows for in-app impressions.<\/p>\n\n\n\n

      Why OMID Signal Matters in Paid Marketing<\/h2>\n\n\n\n

      OMID Signal<\/strong> is strategically important because it reduces uncertainty in environments where measurement is otherwise fragmented. When you\u2019re optimizing Paid Marketing<\/strong> across multiple apps, ad formats, and supply paths, measurement inconsistencies can lead to the wrong decisions\u2014like over-investing in inventory that looks good on paper but underperforms in reality.<\/p>\n\n\n\n

      Key value drivers include:<\/p>\n\n\n\n

        \n
      • More dependable viewability measurement<\/strong> for in-app inventory, enabling smarter budget allocation.<\/li>\n
      • Stronger verification consistency<\/strong> across publishers and SDK implementations.<\/li>\n
      • Better governance<\/strong>: clearer definitions of what \u201cmeasured\u201d means and fewer vendor-specific interpretations.<\/li>\n
      • Competitive advantage<\/strong>: teams that can trust their measurement can iterate faster and negotiate supply more effectively in Programmatic Advertising<\/strong>.<\/li>\n<\/ul>\n\n\n\n

        How OMID Signal Works<\/h2>\n\n\n\n

        While implementations differ by platform and stack, the practical workflow of OMID Signal<\/strong> in Programmatic Advertising<\/strong> typically looks like this:<\/p>\n\n\n\n

          \n
        1. \n

          Input \/ Trigger: An ad session begins<\/strong>\n – An in-app ad is served (often via a mediation layer or programmatic supply path).\n – The app and ad SDK initialize an OMID ad session that can be measured.<\/p>\n<\/li>\n

        2. \n

          Analysis \/ Processing: Verification observes rendering and viewability<\/strong>\n – A verification component (often a script executed in a controlled environment) reads standardized information such as whether the ad is on screen, its size, and its exposure conditions.\n – The observed data forms the OMID Signal<\/strong>\u2014a consistent set of measurement outputs.<\/p>\n<\/li>\n

        3. \n

          Execution \/ Application: Measurement is recorded and used<\/strong>\n – The collected OMID Signal<\/strong> is used to compute viewability metrics and support verification reporting.\n – These outputs flow into reporting dashboards or analytics pipelines used by Paid Marketing<\/strong> teams.<\/p>\n<\/li>\n

        4. \n

          Output \/ Outcome: Decisions and optimization<\/strong>\n – Buyers compare performance across apps, placements, formats, and supply paths.\n – Teams optimize bids, block poor-performing inventory, or adjust creative and placement strategies based on what the OMID Signal<\/strong> indicates.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

          In practice, OMID Signal<\/strong> is less about \u201cone metric\u201d and more about a standardized measurement layer that makes downstream metrics more comparable.<\/p>\n\n\n\n

          Key Components of OMID Signal<\/h2>\n\n\n\n

          To operationalize OMID Signal<\/strong> in Paid Marketing<\/strong>, you typically need several moving parts working together:<\/p>\n\n\n\n

          Technical components<\/h3>\n\n\n\n
            \n
          • App environment (publisher app)<\/strong> where the ad is rendered.<\/li>\n
          • Ad SDK \/ rendering layer<\/strong> capable of supporting OMID measurement sessions.<\/li>\n
          • Verification logic<\/strong> that interprets standardized OMID measurement outputs.<\/li>\n
          • Measurement pipeline<\/strong> that stores, aggregates, and reports the resulting data.<\/li>\n<\/ul>\n\n\n\n

            Processes and governance<\/h3>\n\n\n\n
              \n
            • Implementation QA<\/strong>: validating that OMID measurement sessions start correctly and that signals are emitted consistently.<\/li>\n
            • Measurement policy alignment<\/strong>: agreeing on definitions (for example, which viewability threshold you optimize toward).<\/li>\n
            • Cross-team ownership<\/strong>: marketing, analytics, and development need a shared understanding of how OMID Signal<\/strong> is generated and consumed.<\/li>\n<\/ul>\n\n\n\n

              Data inputs and outputs<\/h3>\n\n\n\n
                \n
              • Inputs: ad session initialization, placement metadata, creative type, environment details.<\/li>\n
              • Outputs: viewability-related telemetry and verification outputs derived from the OMID Signal<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                Types of OMID Signal<\/h2>\n\n\n\n

                OMID Signal<\/strong> isn\u2019t usually presented as a formal taxonomy, but in real Programmatic Advertising<\/strong> operations, it\u2019s useful to think about it in these practical categories:<\/p>\n\n\n\n

                  \n
                1. \n

                  Ad session and lifecycle signals<\/strong>\n – Whether a measurable session started successfully\n – Session timing and state changes during rendering<\/p>\n<\/li>\n

                2. \n

                  Geometry and on-screen exposure signals<\/strong>\n – Ad size and position\n – Whether the ad is within the visible area\n – Exposure duration needed to compute viewability outcomes<\/p>\n<\/li>\n

                3. \n

                  Creative and container context signals<\/strong>\n – Whether the ad is video or display\n – Where and how it\u2019s rendered within the app environment<\/p>\n<\/li>\n

                4. \n

                  Quality and anomaly indicators (derived)<\/strong>\n – Not a single \u201cflag,\u201d but patterns in the OMID Signal<\/strong> that may suggest measurement issues, unusual placement behavior, or invalid traffic risk<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                  These distinctions help Paid Marketing<\/strong> teams troubleshoot performance and interpret results without assuming every underperforming placement is simply \u201cbad creative.\u201d<\/p>\n\n\n\n

                  Real-World Examples of OMID Signal<\/h2>\n\n\n\n

                  Example 1: Mobile app awareness campaign optimizing for viewability<\/h3>\n\n\n\n

                  A consumer brand runs a high-reach in-app campaign via Programmatic Advertising<\/strong>. Early reporting shows strong impression delivery but weak downstream engagement. The team reviews viewability and notices that placements in certain apps have low measurable viewability outcomes based on OMID Signal<\/strong>.<\/p>\n\n\n\n

                  Action taken:\n– Reduce bids or exclude those placements.\n– Reallocate spend to app categories and placements with stronger viewability as indicated by the OMID Signal<\/strong>.<\/p>\n\n\n\n

                  Result:\n– Improved effective reach and more consistent performance in Paid Marketing<\/strong> reporting.<\/p>\n\n\n\n

                  Example 2: Creative format troubleshooting (video vs. display)<\/h3>\n\n\n\n

                  An agency sees that video completion rates are inconsistent across supply sources. By comparing measurements grounded in OMID Signal<\/strong>, they find that certain placements frequently fail to establish a stable measurable session (suggesting rendering or integration issues).<\/p>\n\n\n\n

                  Action taken:\n– Separate line items by app SDK environment or placement type.\n– Coordinate with publishers to confirm OMID compatibility and correct integration.<\/p>\n\n\n\n

                  Result:\n– Higher measurement reliability and fewer \u201cmystery\u201d gaps in Programmatic Advertising<\/strong> performance reports.<\/p>\n\n\n\n

                  Example 3: Supply path evaluation and inventory quality checks<\/h3>\n\n\n\n

                  A performance marketer suspects they are paying for low-quality inventory despite acceptable CTR. They use OMID Signal<\/strong>-driven viewability and measurability rates to compare supply paths.<\/p>\n\n\n\n

                  Action taken:\n– Favor supply paths that consistently produce measurable, viewable impressions.\n– Negotiate terms or block sources with poor measurability.<\/p>\n\n\n\n

                  Result:\n– Less wasted spend and better confidence in Paid Marketing<\/strong> ROI analysis.<\/p>\n\n\n\n

                  Benefits of Using OMID Signal<\/h2>\n\n\n\n

                  When implemented well, OMID Signal<\/strong> can produce tangible improvements in both efficiency and decision quality:<\/p>\n\n\n\n

                    \n
                  • Performance improvements<\/strong>: better optimization inputs for in-app inventory, especially when viewability is a key KPI.<\/li>\n
                  • Cost savings<\/strong>: reduced spend on low-measurability or low-viewability placements.<\/li>\n
                  • Operational efficiency<\/strong>: fewer measurement discrepancies across partners, reducing time spent reconciling reports.<\/li>\n
                  • Better audience experience<\/strong>: optimizing toward viewable impressions can reduce wasted frequency and improve perceived ad quality\u2014important for sustainable Paid Marketing<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                    Challenges of OMID Signal<\/h2>\n\n\n\n

                    OMID Signal<\/strong> is powerful, but it doesn\u2019t remove every measurement problem. Common challenges include:<\/p>\n\n\n\n

                      \n
                    • Integration variability<\/strong>: not every app environment or SDK integration behaves the same, and implementation quality matters.<\/li>\n
                    • Measurement gaps<\/strong>: some impressions may be delivered but not measurable due to session failures, restricted environments, or rendering constraints.<\/li>\n
                    • Interpretation risk<\/strong>: treating viewability outcomes as the only success metric can distort optimization in Paid Marketing<\/strong> (for example, optimizing for viewability at the expense of conversion efficiency).<\/li>\n
                    • Data consistency across partners<\/strong>: even with standardization, reporting pipelines, thresholds, and aggregation logic can differ.<\/li>\n
                    • Privacy and platform constraints<\/strong>: mobile platforms continue to evolve, influencing what can be observed and how signals are processed in Programmatic Advertising<\/strong> measurement.<\/li>\n<\/ul>\n\n\n\n

                      Best Practices for OMID Signal<\/h2>\n\n\n\n

                      To get dependable value from OMID Signal<\/strong>, focus on implementation discipline and measurement governance:<\/p>\n\n\n\n

                        \n
                      1. \n

                        Validate measurability before optimizing<\/strong>\n – Ensure you have stable measurable rates across key supply sources before making budget decisions based on viewability.<\/p>\n<\/li>\n

                      2. \n

                        Segment reporting to find root causes<\/strong>\n – Break down results by app, placement, creative type, and supply path.\n – Use OMID Signal<\/strong> outcomes to distinguish creative problems from placement or integration problems.<\/p>\n<\/li>\n

                      3. \n

                        Align KPIs to campaign goals<\/strong>\n – For awareness, viewability may be central.\n – For performance, treat viewability as a quality constraint, not the sole optimization target in Paid Marketing<\/strong>.<\/p>\n<\/li>\n

                      4. \n

                        Set thresholds and document them<\/strong>\n – Define what \u201cgood\u201d measurability\/viewability looks like for your business and keep it consistent over time.<\/p>\n<\/li>\n

                      5. \n

                        Operationalize monitoring<\/strong>\n – Track anomalies (sudden drops in measurable rate, unusual shifts by app version, or placement-level outliers).\n – Use a change log so teams know when SDK updates or creative changes could affect OMID Signal<\/strong> patterns.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                        Tools Used for OMID Signal<\/h2>\n\n\n\n

                        OMID Signal<\/strong> is usually consumed through broader measurement and activation tooling rather than a single standalone tool. Common tool categories in Paid Marketing<\/strong> and Programmatic Advertising<\/strong> include:<\/p>\n\n\n\n

                          \n
                        • Ad platforms and programmatic buying tools<\/strong><\/li>\n
                        • \n

                          DSP reporting interfaces that ingest verification and viewability outcomes for line-item analysis<\/p>\n<\/li>\n

                        • \n

                          Analytics tools<\/strong><\/p>\n<\/li>\n

                        • \n

                          Mobile analytics and product analytics platforms used to correlate campaign quality with downstream behavior<\/p>\n<\/li>\n

                        • \n

                          Verification and measurement workflows<\/strong><\/p>\n<\/li>\n

                        • \n

                          Independent measurement reporting environments that use OMID-based instrumentation to provide viewability and verification outputs<\/p>\n<\/li>\n

                        • \n

                          Data warehouses and reporting dashboards<\/strong><\/p>\n<\/li>\n

                        • Centralized storage for joining campaign delivery, cost data, and OMID-derived metrics<\/li>\n
                        • \n

                          BI dashboards for trend monitoring and anomaly detection<\/p>\n<\/li>\n

                        • \n

                          Automation and governance systems<\/strong><\/p>\n<\/li>\n

                        • Rule-based optimization, alerting, and spend controls triggered when measurability or viewability drops below defined standards<\/li>\n<\/ul>\n\n\n\n

                          Metrics Related to OMID Signal<\/h2>\n\n\n\n

                          Because OMID Signal<\/strong> is foundational measurement telemetry, the most useful metrics are the ones you compute from it and use to steer Paid Marketing<\/strong> decisions:<\/p>\n\n\n\n

                            \n
                          • Measurable rate<\/strong>: the share of delivered impressions that produced usable measurement outcomes.<\/li>\n
                          • Viewability rate<\/strong>: the share of measured impressions that met your viewability criteria.<\/li>\n
                          • Viewable CPM (vCPM)<\/strong>: cost normalized to viewable impressions, useful in Programmatic Advertising<\/strong> comparisons.<\/li>\n
                          • Time-in-view \/ exposure duration<\/strong>: how long the ad was viewable, which can matter for brand impact.<\/li>\n
                          • Placement-level variance<\/strong>: dispersion of measurability\/viewability across placements, helpful for diagnosing integration issues.<\/li>\n
                          • Outcome tie-ins (contextual)<\/strong><\/li>\n
                          • For awareness: brand lift proxies, reach\/frequency quality<\/li>\n
                          • For performance: conversion rate, CPA\/ROAS segmented by measurability\/viewability cohorts<\/li>\n<\/ul>\n\n\n\n

                            Future Trends of OMID Signal<\/h2>\n\n\n\n

                            Several forces are shaping how OMID Signal<\/strong> is used in Paid Marketing<\/strong>:<\/p>\n\n\n\n

                              \n
                            • More automation in optimization<\/strong><\/li>\n
                            • \n

                              As buying platforms automate more decisions, standardized measurement inputs become more important to prevent \u201coptimizing on noise.\u201d<\/p>\n<\/li>\n

                            • \n

                              AI-assisted anomaly detection<\/strong><\/p>\n<\/li>\n

                            • \n

                              AI can flag unusual OMID Signal<\/strong> patterns (sudden shifts in measurability by app version, suspiciously consistent viewability, or outlier placements) faster than manual reviews.<\/p>\n<\/li>\n

                            • \n

                              Privacy-centric measurement<\/strong><\/p>\n<\/li>\n

                            • \n

                              With ongoing privacy changes, marketers will rely more on aggregated, standardized signals and less on user-level identifiers\u2014making consistent in-app measurement in Programmatic Advertising<\/strong> even more valuable.<\/p>\n<\/li>\n

                            • \n

                              Stronger supply path scrutiny<\/strong><\/p>\n<\/li>\n

                            • As supply paths are evaluated for efficiency and quality, OMID Signal<\/strong>-based metrics will increasingly support decisions about where to buy, not just how much to bid.<\/li>\n<\/ul>\n\n\n\n

                              OMID Signal vs Related Terms<\/h2>\n\n\n\n

                              OMID Signal vs Viewability pixel<\/h3>\n\n\n\n

                              A viewability pixel is traditionally associated with browser-based measurement methods. OMID Signal<\/strong> is designed for in-app environments where pixels and browser mechanics may not apply cleanly. Practically, OMID-based measurement is often the more consistent path for mobile in-app Programmatic Advertising<\/strong> viewability.<\/p>\n\n\n\n

                              OMID Signal vs MRAID<\/h3>\n\n\n\n

                              MRAID is an API focused on rich media ad behavior and interactions in mobile environments. OMID Signal<\/strong> is focused on standardized measurement and verification signals. You can use rich media functionality without robust measurement; OMID addresses measurement consistency for Paid Marketing<\/strong> reporting.<\/p>\n\n\n\n

                              OMID Signal vs VAST<\/h3>\n\n\n\n

                              VAST is primarily a video ad serving specification (metadata, tracking events, and delivery). OMID Signal<\/strong> is about measurement of rendering and viewability conditions, especially in-app. Many stacks use VAST for serving video while relying on OMID-based telemetry for comparable measurement in Programmatic Advertising<\/strong>.<\/p>\n\n\n\n

                              Who Should Learn OMID Signal<\/h2>\n\n\n\n

                              OMID Signal<\/strong> is worth learning if you touch in-app advertising measurement or decision-making:<\/p>\n\n\n\n

                                \n
                              • Marketers<\/strong>: to interpret viewability and measurability reports correctly and avoid optimizing to misleading metrics in Paid Marketing<\/strong>.<\/li>\n
                              • Analysts<\/strong>: to design clean reporting, segment issues by supply path, and build trustworthy performance narratives.<\/li>\n
                              • Agencies<\/strong>: to standardize client reporting and troubleshoot cross-publisher inconsistencies in Programmatic Advertising<\/strong> buys.<\/li>\n
                              • Business owners and founders<\/strong>: to understand whether in-app spend is producing real exposure or just delivery volume.<\/li>\n
                              • Developers and ad ops<\/strong>: to support correct SDK integration, QA measurable sessions, and resolve discrepancies that affect reporting.<\/li>\n<\/ul>\n\n\n\n

                                Summary of OMID Signal<\/h2>\n\n\n\n

                                OMID Signal<\/strong> is the standardized measurement telemetry produced by OMID-enabled ad sessions in mobile app environments, commonly used to support viewability and verification reporting. It matters because it improves measurement consistency, which leads to better optimization and stronger accountability in Paid Marketing<\/strong>. Within Programmatic Advertising<\/strong>, OMID Signal<\/strong> helps buyers compare inventory quality across apps and supply paths, reduce waste, and make performance decisions grounded in more reliable in-app measurement.<\/p>\n\n\n\n

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

                                What does OMID Signal actually tell me?<\/h3>\n\n\n\n

                                OMID Signal<\/strong> provides standardized evidence about in-app ad rendering and exposure conditions that can be used to calculate measurability and viewability outcomes. It\u2019s a foundation for comparing inventory quality across placements and publishers.<\/p>\n\n\n\n

                                Is OMID Signal only for mobile apps?<\/h3>\n\n\n\n

                                It\u2019s most commonly discussed in the context of in-app environments where traditional browser-based measurement is limited. The practical value is strongest for mobile app Paid Marketing<\/strong> and in-app Programmatic Advertising<\/strong>.<\/p>\n\n\n\n

                                How does OMID Signal affect optimization in Paid Marketing?<\/h3>\n\n\n\n

                                It improves the reliability of quality metrics (like measurable rate and viewability rate). That helps you shift spend away from placements that deliver impressions but don\u2019t produce dependable measurement outcomes.<\/p>\n\n\n\n

                                What should I do if my measurable rate drops suddenly?<\/h3>\n\n\n\n

                                Treat it like an instrumentation issue until proven otherwise. Check changes in app versions, SDK updates, creative formats, and supply paths. Segment by publisher\/app\/placement to identify where the OMID Signal<\/strong> degradation is concentrated.<\/p>\n\n\n\n

                                How is OMID Signal used in Programmatic Advertising buying decisions?<\/h3>\n\n\n\n

                                In Programmatic Advertising<\/strong>, it supports inventory quality evaluation at scale. Buyers use OMID-derived measurability and viewability outcomes to adjust bids, block placements, and prioritize supply paths with more consistent measurement.<\/p>\n\n\n\n

                                Does a high viewability rate guarantee better performance?<\/h3>\n\n\n\n

                                Not necessarily. High viewability can improve the chance of impact for awareness goals, but conversions depend on many other factors (audience, offer, landing experience, frequency, and creative). Use OMID Signal<\/strong> as a quality input, not the only success metric for Paid Marketing<\/strong>.<\/p>\n\n\n\n

                                Can OMID Signal help detect ad fraud?<\/h3>\n\n\n\n

                                It can contribute signals that support fraud investigation (for example, unusual measurement patterns or consistently low measurability), but it\u2019s not a complete fraud solution by itself. Combine OMID-based outcomes with broader traffic quality and conversion validation.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                Modern **Paid Marketing** depends on reliable measurement\u2014especially when ads run inside mobile apps, where browsers, cookies, and traditional pixels don\u2019t work the same way. **OMID Signal** refers to the standardized measurement signals generated through the Open Measurement framework used by the ad verification ecosystem to determine whether an ad was actually rendered, viewable, and measurable in an in-app environment.<\/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-10779","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\/10779","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=10779"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/10779\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=10779"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=10779"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=10779"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}