{"id":10880,"date":"2026-03-30T02:17:41","date_gmt":"2026-03-30T02:17:41","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/programmatic-dashboard\/"},"modified":"2026-03-30T02:17:41","modified_gmt":"2026-03-30T02:17:41","slug":"programmatic-dashboard","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/programmatic-dashboard\/","title":{"rendered":"Programmatic Dashboard: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Programmatic Advertising"},"content":{"rendered":"\n

A Programmatic Dashboard<\/strong> is the control center where performance, spend, pacing, and quality signals from Paid Marketing<\/strong> campaigns\u2014especially within Programmatic Advertising<\/strong>\u2014are brought together into one decision-ready view. Instead of switching between ad platforms, analytics tools, and spreadsheets, teams use a Programmatic Dashboard to monitor what\u2019s happening, diagnose why it\u2019s happening, and decide what to do next.<\/p>\n\n\n\n

This matters because modern Paid Marketing moves fast: auctions are continuous, budgets shift daily, audiences fragment across devices, and measurement is constrained by privacy changes. In Programmatic Advertising, where campaigns run across multiple exchanges, formats, and data sources, a Programmatic Dashboard helps reduce blind spots, prevent waste, and turn data into action with consistent governance.<\/p>\n\n\n\n

What Is Programmatic Dashboard?<\/h2>\n\n\n\n

A Programmatic Dashboard<\/strong> is a reporting and decision-support interface that consolidates key data from Programmatic Advertising systems\u2014such as demand-side platforms (DSPs), ad servers, verification tools, analytics platforms, and sometimes CRM or commerce systems\u2014into a unified view.<\/p>\n\n\n\n

At a beginner level, think of it as a \u201cmission control\u201d screen for Paid Marketing: it shows how much you\u2019re spending, what you\u2019re getting back, and whether campaigns are on track.<\/p>\n\n\n\n

At a business level, a Programmatic Dashboard translates fragmented campaign signals into operational insights:\n– Are we pacing to budget?\n– Which audiences and placements are driving outcomes?\n– Is inventory quality acceptable?\n– Are we meeting KPIs like ROAS, CPA, or incremental lift proxies?<\/p>\n\n\n\n

Within Paid Marketing<\/strong>, the Programmatic Dashboard sits between execution (buying media) and decision-making (optimization, forecasting, and performance reviews). Inside Programmatic Advertising<\/strong>, it helps align real-time delivery metrics (like win rate and CPM) with business outcomes (like revenue, leads, or retention).<\/p>\n\n\n\n

Why Programmatic Dashboard Matters in Paid Marketing<\/h2>\n\n\n\n

In Paid Marketing, speed and clarity are competitive advantages. A Programmatic Dashboard matters because it reduces decision latency\u2014how long it takes to detect an issue and respond.<\/p>\n\n\n\n

Strategically, it supports:\n– Budget stewardship:<\/strong> identifying overspend, underspend, and inefficient segments before they become expensive.\n– Performance accountability:<\/strong> connecting Programmatic Advertising delivery metrics to outcomes executives care about.\n– Cross-team alignment:<\/strong> giving agencies, in-house marketers, and analysts a shared source of truth.\n– Scalable optimization:<\/strong> enabling repeatable rules and playbooks rather than one-off fixes.<\/p>\n\n\n\n

The business value shows up in better marketing outcomes\u2014more conversions at the same spend, more stable pacing, fewer brand safety incidents, and clearer explanations for why performance changed. When competitors use better instrumentation, they often win not by having \u201csecret tactics,\u201d but by reacting faster with higher confidence.<\/p>\n\n\n\n

How Programmatic Dashboard Works<\/h2>\n\n\n\n

A Programmatic Dashboard is less a single \u201ctool\u201d and more a workflow that turns campaign exhaust into decisions. In practice, it works like this:<\/p>\n\n\n\n

    \n
  1. \n

    Inputs (data capture)<\/strong>\n – Delivery data from DSPs and ad servers (impressions, clicks, spend, win rate, frequency).\n – Conversion and revenue signals from analytics, app measurement, or server-side events.\n – Quality signals from verification (viewability, invalid traffic, brand safety).\n – Audience and contextual metadata (geo, device, creative, placement, deal IDs).<\/p>\n<\/li>\n

  2. \n

    Processing (normalization and modeling)<\/strong>\n – Standardizing naming conventions (campaign, ad group, creative IDs).\n – De-duplicating or reconciling discrepancies between platforms (DSP vs analytics).\n – Applying attribution logic or proxy KPIs where direct attribution is limited.\n – Calculating derived metrics like eCPA, ROAS, margin, or effective CPM.<\/p>\n<\/li>\n

  3. \n

    Application (analysis and decision support)<\/strong>\n – Highlighting anomalies (spend spikes, conversion drops, viewability declines).\n – Segmenting performance by audience, inventory, creative, and geography.\n – Enabling pacing controls and alerts for Paid Marketing operations.\n – Supporting experimentation analysis (A\/B creative tests, audience splits).<\/p>\n<\/li>\n

  4. \n

    Outputs (actions and outcomes)<\/strong>\n – Recommendations for reallocation (shift budget to higher-performing deals).\n – Risk flags (brand safety thresholds exceeded, frequency too high).\n – Stakeholder reporting (weekly performance, QBR insights, forecasting).\n – Operational queues for optimizations in Programmatic Advertising platforms.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

    A strong Programmatic Dashboard doesn\u2019t just display numbers\u2014it guides decisions and makes the \u201cnext best action\u201d easier to find.<\/p>\n\n\n\n

    Key Components of Programmatic Dashboard<\/h2>\n\n\n\n

    A reliable Programmatic Dashboard typically includes these building blocks:<\/p>\n\n\n\n

    Data sources and connectors<\/h3>\n\n\n\n

    You need consistent ingestion from Programmatic Advertising platforms, measurement systems, and business data sources. The practical challenge isn\u2019t \u201cgetting data,\u201d it\u2019s keeping it consistent over time as campaign structures evolve.<\/p>\n\n\n\n

    Data model and taxonomy<\/h3>\n\n\n\n

    A shared taxonomy (naming conventions, IDs, hierarchies) is essential. Without it, filters break, rollups become inaccurate, and Paid Marketing reporting becomes a debate.<\/p>\n\n\n\n

    Core views and drill-downs<\/h3>\n\n\n\n

    Most Programmatic Dashboard designs include:\n– Executive summary (KPIs, pacing, budget utilization)\n– Channel or DSP views\n– Audience, placement, and creative performance breakdowns\n– Quality and compliance view (brand safety, viewability, fraud)<\/p>\n\n\n\n

    Monitoring and alerting<\/h3>\n\n\n\n

    Alerts turn dashboards from passive reports into operational tools. Common alerts include pacing variance, CPA spikes, frequency caps, and sudden drops in conversion rate.<\/p>\n\n\n\n

    Governance and responsibilities<\/h3>\n\n\n\n

    A Programmatic Dashboard needs owners:\n– Who defines KPIs and \u201cofficial\u201d metrics?\n– Who validates data pipelines?\n– Who responds to alerts?\n– Who approves structural changes that affect reporting?<\/p>\n\n\n\n

    In Programmatic Advertising, where multiple partners are involved, governance prevents reporting fragmentation and inconsistent conclusions.<\/p>\n\n\n\n

    Types of Programmatic Dashboard<\/h2>\n\n\n\n

    \u201cTypes\u201d are usually defined by purpose and audience rather than formal categories:<\/p>\n\n\n\n

    Operational (real-time) dashboards<\/h3>\n\n\n\n

    Designed for traders and campaign managers in Paid Marketing. They emphasize pacing, delivery, and immediate action: spend by hour\/day, win rate shifts, frequency, and deal performance.<\/p>\n\n\n\n

    Performance and outcome dashboards<\/h3>\n\n\n\n

    Built for growth teams and analysts. They focus on KPIs like CPA, ROAS, leads, revenue, and retention signals\u2014often blended with analytics and CRM outcomes.<\/p>\n\n\n\n

    Quality and compliance dashboards<\/h3>\n\n\n\n

    Centered on brand safety, viewability, invalid traffic, and policy compliance. These are common in Programmatic Advertising for brands with strict safeguards.<\/p>\n\n\n\n

    Executive and forecasting dashboards<\/h3>\n\n\n\n

    A higher-level Programmatic Dashboard that summarizes performance against goals, budget forecasts, and scenario planning\u2014often used in leadership meetings.<\/p>\n\n\n\n

    Real-World Examples of Programmatic Dashboard<\/h2>\n\n\n\n

    1) Ecommerce prospecting with multi-DSP spend<\/h3>\n\n\n\n

    A retailer runs Programmatic Advertising across two DSPs for prospecting and retargeting. Their Programmatic Dashboard blends:\n– DSP spend and delivery\n– Analytics conversions and revenue\n– Product category performance\nThis allows Paid Marketing managers to spot that one DSP is driving higher click volume but lower revenue per session, leading to a budget shift and creative refresh focused on higher-margin categories.<\/p>\n\n\n\n

    2) B2B lead generation with quality filtering<\/h3>\n\n\n\n

    A SaaS company uses Programmatic Advertising to drive demo requests. The Programmatic Dashboard tracks:\n– CPL and qualified lead rate\n– Viewability and invalid traffic\n– Frequency by account segment\nThey identify placements producing low-quality leads (high form fills, low sales acceptance) and tighten inventory targeting while adding quality thresholds. Outcome: fewer leads, higher pipeline efficiency.<\/p>\n\n\n\n

    3) Brand campaign with attention and safety guardrails<\/h3>\n\n\n\n

    A consumer brand runs a large awareness campaign. Their Programmatic Dashboard focuses on:\n– Reach and frequency management\n– Viewability and brand safety incidents\n– Geo and device distribution\nPaid Marketing teams use alerts to catch frequency spikes in a single region and adjust caps, protecting experience while maintaining reach goals.<\/p>\n\n\n\n

    Benefits of Using Programmatic Dashboard<\/h2>\n\n\n\n

    A well-implemented Programmatic Dashboard can deliver tangible gains:<\/p>\n\n\n\n

      \n
    • Faster optimization cycles:<\/strong> quicker detection of pacing issues and performance drops in Paid Marketing.<\/li>\n
    • Reduced wasted spend:<\/strong> better control over low-quality inventory and ineffective audience segments in Programmatic Advertising.<\/li>\n
    • Clearer attribution conversations:<\/strong> even when attribution is imperfect, consistent reporting reduces internal disagreement.<\/li>\n
    • Improved operational efficiency:<\/strong> less time building manual reports, more time analyzing and improving.<\/li>\n
    • Better customer and audience experience:<\/strong> frequency controls and quality monitoring reduce ad fatigue and brand risk.<\/li>\n<\/ul>\n\n\n\n

      The biggest benefit is consistency: teams make fewer decisions based on partial data or outdated exports.<\/p>\n\n\n\n

      Challenges of Programmatic Dashboard<\/h2>\n\n\n\n

      A Programmatic Dashboard is powerful, but it can fail if these realities aren\u2019t managed:<\/p>\n\n\n\n

        \n
      • Data discrepancies:<\/strong> DSP-reported conversions rarely match analytics perfectly due to attribution windows, deduplication, and tracking loss.<\/li>\n
      • Identity and privacy constraints:<\/strong> signal loss reduces determinism; dashboards must adapt with modeled or aggregated metrics where appropriate.<\/li>\n
      • Fragmented taxonomy:<\/strong> inconsistent naming breaks rollups and makes Paid Marketing reporting unreliable.<\/li>\n
      • Latency vs accuracy trade-offs:<\/strong> near-real-time data may be incomplete; daily finalized data may be too slow for operations.<\/li>\n
      • Over-monitoring:<\/strong> too many charts create noise; teams miss what matters.<\/li>\n
      • Metric misalignment:<\/strong> optimizing to proxies (CTR, viewability) without outcome context can distort Programmatic Advertising strategy.<\/li>\n<\/ul>\n\n\n\n

        Addressing these challenges is as much about process and governance as it is about technology.<\/p>\n\n\n\n

        Best Practices for Programmatic Dashboard<\/h2>\n\n\n\n

        Design around decisions, not data availability<\/h3>\n\n\n\n

        Start with the actions your team needs to take (budget shifts, creative swaps, inventory exclusions), then ensure the Programmatic Dashboard supports those decisions.<\/p>\n\n\n\n

        Standardize naming and campaign structure<\/h3>\n\n\n\n

        Enforce consistent taxonomy for campaigns, ad groups, creatives, audiences, and deals. This single step often improves Paid Marketing reporting more than adding new charts.<\/p>\n\n\n\n

        Separate operational metrics from business outcomes<\/h3>\n\n\n\n

        Keep pacing and delivery views distinct from outcome analysis. Programmatic Advertising teams need both, but mixing them in one view can cause confusion.<\/p>\n\n\n\n

        Build trustworthy definitions for KPIs<\/h3>\n\n\n\n

        Define attribution windows, conversion definitions, and how deduplication works. Document \u201csource of truth\u201d rules so stakeholders interpret the Programmatic Dashboard consistently.<\/p>\n\n\n\n

        Use alerts with thresholds and owners<\/h3>\n\n\n\n

        Alerts should have:\n– clear thresholds (e.g., CPA +30% day-over-day)\n– an owner (who responds)\n– an escalation path (when it becomes urgent)<\/p>\n\n\n\n

        Make drill-downs predictable<\/h3>\n\n\n\n

        Users should be able to move from a KPI drop to the segment causing it: DSP \u2192 campaign \u2192 ad group \u2192 creative \u2192 placement\/deal \u2192 device\/geo.<\/p>\n\n\n\n

        Review and refactor regularly<\/h3>\n\n\n\n

        Programmatic Advertising changes constantly. Revisit dashboard structure quarterly to remove unused views and incorporate new measurement constraints.<\/p>\n\n\n\n

        Tools Used for Programmatic Dashboard<\/h2>\n\n\n\n

        A Programmatic Dashboard typically sits on top of several tool categories:<\/p>\n\n\n\n

          \n
        • Ad platforms (execution):<\/strong> DSPs and ad servers provide delivery, auction, and creative data central to Programmatic Advertising.<\/li>\n
        • Analytics tools (measurement):<\/strong> web\/app analytics and event pipelines connect Paid Marketing activity to onsite behavior and conversions.<\/li>\n
        • Data warehouses and ETL\/ELT pipelines:<\/strong> store, normalize, and join data across platforms; critical for scalable reporting.<\/li>\n
        • Reporting and BI dashboards:<\/strong> visualization layers used to build the Programmatic Dashboard views and permission models.<\/li>\n
        • Verification and measurement vendors:<\/strong> viewability, brand safety, and invalid traffic signals used to protect quality.<\/li>\n
        • CRM and revenue systems:<\/strong> lead status, pipeline, purchases, or LTV signals to connect Programmatic Advertising to business outcomes.<\/li>\n
        • Project management and governance systems:<\/strong> documentation, change logs, and QA workflows to keep reporting consistent.<\/li>\n<\/ul>\n\n\n\n

          The key is interoperability: the more your stack can share IDs and consistent dimensions, the more useful the Programmatic Dashboard becomes.<\/p>\n\n\n\n

          Metrics Related to Programmatic Dashboard<\/h2>\n\n\n\n

          A Programmatic Dashboard commonly tracks a blend of delivery, efficiency, outcome, and quality metrics:<\/p>\n\n\n\n

          Delivery and auction metrics (Programmatic Advertising)<\/h3>\n\n\n\n
            \n
          • Impressions, reach (where measurable), frequency<\/li>\n
          • Spend, CPM, effective CPM<\/li>\n
          • Win rate, bid rate, match rate (platform-dependent)<\/li>\n
          • Pacing vs plan (daily\/weekly\/monthly)<\/li>\n<\/ul>\n\n\n\n

            Performance and outcome metrics (Paid Marketing)<\/h3>\n\n\n\n
              \n
            • Clicks, CTR (use cautiously)<\/li>\n
            • Conversions, conversion rate<\/li>\n
            • CPA \/ CPL, ROAS, revenue, profit or contribution margin (when available)<\/li>\n
            • New customer rate, repeat purchase rate (when integrated)<\/li>\n<\/ul>\n\n\n\n

              Quality metrics<\/h3>\n\n\n\n
                \n
              • Viewability rate<\/li>\n
              • Invalid traffic or fraud indicators<\/li>\n
              • Brand safety incidents or risk scores<\/li>\n
              • Landing page performance indicators (bounce rate, engagement proxies)<\/li>\n<\/ul>\n\n\n\n

                Efficiency and operations metrics<\/h3>\n\n\n\n
                  \n
                • Cost per incremental outcome (where lift testing exists)<\/li>\n
                • Time to detect issues (operational KPI)<\/li>\n
                • Budget utilization and forecast accuracy<\/li>\n<\/ul>\n\n\n\n

                  Good dashboards show context: trends, benchmarks, and variance-to-target\u2014not just raw numbers.<\/p>\n\n\n\n

                  Future Trends of Programmatic Dashboard<\/h2>\n\n\n\n

                  Several shifts are changing what a Programmatic Dashboard needs to do in Paid Marketing:<\/p>\n\n\n\n

                    \n
                  • More modeled and aggregated measurement:<\/strong> as deterministic tracking declines, dashboards increasingly rely on blended attribution, incrementality tests, and modeled conversions.<\/li>\n
                  • Automation and decisioning:<\/strong> dashboards will integrate more alerting, anomaly detection, and guided recommendations (with humans still accountable).<\/li>\n
                  • Privacy-first reporting:<\/strong> stronger permissioning, data minimization, and aggregated views by default\u2014especially for cross-team access.<\/li>\n
                  • Creative and attention analytics:<\/strong> more emphasis on creative fatigue, frequency impact, and quality of exposure rather than clicks alone.<\/li>\n
                  • Real-time business signals:<\/strong> tighter integration with inventory, pricing, and CRM stages to connect Programmatic Advertising directly to operational outcomes.<\/li>\n
                  • Standardization across partners:<\/strong> agencies and brands will demand consistent definitions and auditability in Paid Marketing reporting.<\/li>\n<\/ul>\n\n\n\n

                    The Programmatic Dashboard is evolving from a reporting surface into an operating system for programmatic decision-making.<\/p>\n\n\n\n

                    Programmatic Dashboard vs Related Terms<\/h2>\n\n\n\n

                    Programmatic Dashboard vs DSP reporting<\/h3>\n\n\n\n

                    DSP reporting is platform-specific and optimized for executing Programmatic Advertising within that DSP. A Programmatic Dashboard is broader: it consolidates multiple sources, aligns definitions, and ties delivery to business outcomes across Paid Marketing.<\/p>\n\n\n\n

                    Programmatic Dashboard vs marketing dashboard<\/h3>\n\n\n\n

                    A general marketing dashboard may cover SEO, email, organic social, and sales KPIs. A Programmatic Dashboard is specialized for programmatic media buying, including auction dynamics, pacing, inventory quality, and deal-level insights.<\/p>\n\n\n\n

                    Programmatic Dashboard vs attribution dashboard<\/h3>\n\n\n\n

                    An attribution dashboard focuses on credit assignment across touchpoints. A Programmatic Dashboard may include attribution views, but also covers operational control (pacing, quality, and spend governance) essential to Programmatic Advertising execution.<\/p>\n\n\n\n

                    Who Should Learn Programmatic Dashboard<\/h2>\n\n\n\n
                      \n
                    • Marketers and growth leads:<\/strong> to understand how Programmatic Advertising performance connects to outcomes and how to manage Paid Marketing budgets responsibly.<\/li>\n
                    • Analysts:<\/strong> to build reliable definitions, data models, and insight workflows that stakeholders trust.<\/li>\n
                    • Agencies:<\/strong> to standardize reporting across clients and prove value beyond platform screenshots.<\/li>\n
                    • Business owners and founders:<\/strong> to get clarity on where spend is going, what it returns, and what risks exist.<\/li>\n
                    • Developers and data engineers:<\/strong> to design pipelines, permissions, and data quality checks that make the Programmatic Dashboard accurate and scalable.<\/li>\n<\/ul>\n\n\n\n

                      This is a high-leverage skill because it affects every decision downstream of media buying.<\/p>\n\n\n\n

                      Summary of Programmatic Dashboard<\/h2>\n\n\n\n

                      A Programmatic Dashboard<\/strong> is a centralized system for monitoring, analyzing, and acting on campaign data in Paid Marketing<\/strong>, with a strong focus on the operational realities of Programmatic Advertising<\/strong>. It consolidates platform, analytics, and quality signals into decision-ready views, enabling faster optimization, better governance, and clearer performance accountability. When designed around decisions, standardized definitions, and trustworthy data, a Programmatic Dashboard becomes essential infrastructure for scaling programmatic media effectively.<\/p>\n\n\n\n

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

                      1) What is a Programmatic Dashboard used for?<\/h3>\n\n\n\n

                      A Programmatic Dashboard is used to track spend, pacing, performance, and quality across Programmatic Advertising campaigns so teams can optimize Paid Marketing quickly and consistently.<\/p>\n\n\n\n

                      2) Does a Programmatic Dashboard replace DSP reports?<\/h3>\n\n\n\n

                      No. DSP reports are still needed for platform-specific details and execution. A Programmatic Dashboard complements them by unifying data across systems and aligning KPIs to business outcomes.<\/p>\n\n\n\n

                      3) Which KPIs should be on a Programmatic Dashboard first?<\/h3>\n\n\n\n

                      Start with pacing (spend vs plan), primary outcome KPI (CPA\/ROAS\/CPL), conversion volume, and key quality metrics (viewability, invalid traffic). Add deeper segmentation after the basics are stable.<\/p>\n\n\n\n

                      4) How do you handle attribution differences between analytics and Programmatic Advertising platforms?<\/h3>\n\n\n\n

                      Define a \u201creporting truth\u201d for each use case: use DSP attribution for in-platform optimization, and analytics\/CRM for business reporting. Your Programmatic Dashboard should show both with clear labels and consistent windows.<\/p>\n\n\n\n

                      5) What\u2019s the biggest mistake teams make with a Programmatic Dashboard?<\/h3>\n\n\n\n

                      Building it as a collection of charts instead of a decision tool. If it doesn\u2019t help someone take a clear action in Paid Marketing, it\u2019s reporting noise.<\/p>\n\n\n\n

                      6) How often should a Programmatic Dashboard update?<\/h3>\n\n\n\n

                      Operational views often update multiple times per day, while outcome and finance-aligned reporting may finalize daily. The right cadence depends on data latency, conversion cycles, and how frequently you make changes in Programmatic Advertising.<\/p>\n\n\n\n

                      7) How is a Programmatic Dashboard changing as privacy rules evolve?<\/h3>\n\n\n\n

                      It\u2019s shifting toward aggregated reporting, modeled conversions, stronger governance, and more emphasis on incrementality and quality signals\u2014so Paid Marketing teams can remain effective without relying on fragile user-level tracking.<\/p>\n","protected":false},"excerpt":{"rendered":"

                      A **Programmatic Dashboard** is the control center where performance, spend, pacing, and quality signals from **Paid Marketing** campaigns\u2014especially within **Programmatic Advertising**\u2014are brought together into one decision-ready view. Instead of switching between ad platforms, analytics tools, and spreadsheets, teams use a Programmatic Dashboard to monitor what\u2019s happening, diagnose why it\u2019s happening, and decide what to do next.<\/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-10880","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\/10880","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=10880"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/10880\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=10880"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=10880"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=10880"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}