{"id":6754,"date":"2026-03-23T11:13:06","date_gmt":"2026-03-23T11:13:06","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/retail-media-benchmark\/"},"modified":"2026-03-23T11:13:06","modified_gmt":"2026-03-23T11:13:06","slug":"retail-media-benchmark","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/retail-media-benchmark\/","title":{"rendered":"Retail Media Benchmark: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Commerce & Retail Media"},"content":{"rendered":"\n

Retail media has become a core growth lever for brands and retailers, but performance data is only useful when you can interpret it in context. A Retail Media Benchmark<\/strong> is the reference point you use to judge whether a retail media campaign, ad format, keyword strategy, or onsite\/offsite placement is performing \u201cwell\u201d relative to expectations or peers. In Commerce & Retail Media<\/strong>, benchmarks turn raw metrics into actionable decisions: what to scale, what to fix, and what \u201cgood\u201d looks like for your category, retailer, and objectives.<\/p>\n\n\n\n

Because the retail media landscape is fragmented\u2014different retailers, different ad products, different measurement rules\u2014Retail Media Benchmark<\/strong> practices help bring consistency to planning and optimization. Used correctly, benchmarks prevent overreacting to noisy data, highlight real opportunity, and align stakeholders across Commerce & Retail Media<\/strong> strategy and execution.<\/p>\n\n\n\n

What Is Retail Media Benchmark?<\/h2>\n\n\n\n

A Retail Media Benchmark<\/strong> is a baseline or standard used to compare retail media performance. It can be:<\/p>\n\n\n\n

    \n
  • Historical<\/strong> (your own past results)<\/li>\n
  • Goal-based<\/strong> (targets tied to margin, growth, or efficiency)<\/li>\n
  • Peer\/market-based<\/strong> (category averages or competitive norms, when available)<\/li>\n<\/ul>\n\n\n\n

    The core concept is simple: performance is relative. A 3% click-through rate might be excellent for one placement and weak for another. A 4x ROAS might be profitable for one brand and unprofitable for another depending on margins, repeat rate, and halo effects.<\/p>\n\n\n\n

    From a business perspective, a Retail Media Benchmark<\/strong> is a decision tool. It helps you answer practical questions such as:<\/p>\n\n\n\n

      \n
    • Are we under-investing or overpaying for this audience?<\/li>\n
    • Which retailer is most efficient for incremental growth?<\/li>\n
    • Is our sponsored search strategy improving efficiency over time?<\/li>\n<\/ul>\n\n\n\n

      In Commerce & Retail Media<\/strong>, benchmarks sit at the intersection of media buying, merchandising, pricing, and operations. They also play a role inside Commerce & Retail Media<\/strong> measurement, where different attribution windows and reporting methods can otherwise make performance hard to compare.<\/p>\n\n\n\n

      Why Retail Media Benchmark Matters in Commerce & Retail Media<\/h2>\n\n\n\n

      A strong Retail Media Benchmark<\/strong> approach matters because retail media decisions often happen fast and at scale. Without benchmarks, teams can optimize toward the wrong goal or misread normal volatility as success or failure.<\/p>\n\n\n\n

      Key strategic reasons benchmarks matter in Commerce & Retail Media<\/strong> include:<\/p>\n\n\n\n

        \n
      • Budget allocation:<\/strong> Benchmarks help decide how much to invest by retailer, category, format, and funnel stage.<\/li>\n
      • Performance diagnosis:<\/strong> When results dip, benchmarks indicate whether the issue is conversion rate, CPC inflation, content readiness, or competition.<\/li>\n
      • Expectation management:<\/strong> Benchmarks create shared definitions of \u201cefficient\u201d and \u201cprofitable\u201d across marketing, finance, and sales.<\/li>\n
      • Competitive advantage:<\/strong> Brands that benchmark well detect shifts in auction pressure, share-of-voice changes, and category dynamics earlier.<\/li>\n<\/ul>\n\n\n\n

        In mature Commerce & Retail Media<\/strong> programs, benchmarks are not only retrospective; they shape planning, forecasting, and test design.<\/p>\n\n\n\n

        How Retail Media Benchmark Works<\/h2>\n\n\n\n

        A Retail Media Benchmark<\/strong> is more of a practical operating system than a single metric. In real teams, it typically works like this:<\/p>\n\n\n\n

          \n
        1. \n

          Input \/ trigger: define context<\/strong>\n – Retailer and ad product (sponsored products, sponsored brands, display, offsite)\n – Objective (profitability, growth, new-to-brand, awareness)\n – Constraints (inventory, margin, promotions, seasonality, compliance)<\/p>\n<\/li>\n

        2. \n

          Analysis: build the comparison set<\/strong>\n – Pull performance by segment (category, SKU, keyword type, placement, audience)\n – Normalize where possible (time period, attribution window, spend level)\n – Separate \u201calways-on\u201d from campaign bursts to avoid mixing baselines<\/p>\n<\/li>\n

        3. \n

          Application: translate to decisions<\/strong>\n – Set targets (e.g., CPC ceiling, ROAS floor, impression share goal)\n – Identify outliers (best\/worst performers) and root causes\n – Prioritize experiments (creative test, bid strategy, PDP improvements)<\/p>\n<\/li>\n

        4. \n

          Output \/ outcome: continuous improvement<\/strong>\n – Updated benchmark ranges by segment\n – Reporting that flags meaningful changes (not noise)\n – Better forecasts and clearer accountability in Commerce & Retail Media<\/strong><\/p>\n<\/li>\n<\/ol>\n\n\n\n

          Done well, benchmarking is iterative: your Retail Media Benchmark<\/strong> becomes more accurate as your data quality improves and your strategy matures.<\/p>\n\n\n\n

          Key Components of Retail Media Benchmark<\/h2>\n\n\n\n

          A reliable Retail Media Benchmark<\/strong> depends on several building blocks:<\/p>\n\n\n\n

          Data inputs<\/h3>\n\n\n\n
            \n
          • Ad platform performance data (impressions, clicks, spend, sales)<\/li>\n
          • Product and margin data (COGS, promo funding, shipping, fees)<\/li>\n
          • Catalog and content quality signals (availability, price index, ratings)<\/li>\n
          • Retailer context (category seasonality, event calendars, onsite placement rules)<\/li>\n<\/ul>\n\n\n\n

            Metrics framework<\/h3>\n\n\n\n
              \n
            • KPI definitions (e.g., what \u201csales\u201d means in each retailer\u2019s reporting)<\/li>\n
            • Segmentation rules (brand vs non-brand keywords, new vs returning customers)<\/li>\n
            • Time windows and attribution assumptions<\/li>\n<\/ul>\n\n\n\n

              Processes<\/h3>\n\n\n\n
                \n
              • Monthly\/weekly benchmark refresh cadence<\/li>\n
              • Test-and-learn governance (what counts as a valid experiment)<\/li>\n
              • Change logs for major shifts (promo periods, assortment changes)<\/li>\n<\/ul>\n\n\n\n

                Ownership and governance<\/h3>\n\n\n\n
                  \n
                • Who sets benchmark ranges (media, analytics, finance)?<\/li>\n
                • Who approves exceptions (e.g., paying higher CPC to win conquest terms)?<\/li>\n
                • Documentation so benchmarks remain consistent across teams and agencies<\/li>\n<\/ul>\n\n\n\n

                  In Commerce & Retail Media<\/strong>, the quality of your benchmark is often limited by inconsistent definitions and incomplete profitability context\u2014so governance matters as much as the math.<\/p>\n\n\n\n

                  Types of Retail Media Benchmark<\/h2>\n\n\n\n

                  There aren\u2019t universally standardized \u201cofficial types,\u201d but in practice, Retail Media Benchmark<\/strong> programs usually fall into a few useful categories:<\/p>\n\n\n\n

                    \n
                  1. \n

                    Internal (historical) benchmarks<\/strong>\n – Based on your own performance trends\n – Best for accountability and continuous improvement<\/p>\n<\/li>\n

                  2. \n

                    External (market) benchmarks<\/strong>\n – Based on category norms or third-party aggregates\n – Useful for sanity checks, but often less precise due to differences in mix and methodology<\/p>\n<\/li>\n

                  3. \n

                    Retailer-specific benchmarks<\/strong>\n – Separate ranges per retailer because ad products, shoppers, and attribution differ\n – Essential in Commerce & Retail Media<\/strong> when comparing networks is otherwise misleading<\/p>\n<\/li>\n

                  4. \n

                    Objective-based benchmarks<\/strong>\n – Profit-focused (ROAS, contribution margin)\n – Growth-focused (incremental sales, new-to-brand rate)\n – Visibility-focused (share of voice, impression share)<\/p>\n<\/li>\n

                  5. \n

                    Granular segment benchmarks<\/strong>\n – By category, SKU tier, keyword intent, placement type, or audience\n – Most actionable, but requires clean data and enough volume<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                    Real-World Examples of Retail Media Benchmark<\/h2>\n\n\n\n

                    Example 1: Sponsored search efficiency for a CPG brand<\/h3>\n\n\n\n

                    A CPG brand notices ROAS declining month over month. Instead of cutting spend broadly, it uses a Retail Media Benchmark<\/strong> by keyword intent:\n– Brand terms: high ROAS, low CPC volatility\n– Generic category terms: lower ROAS, higher CPC inflation\n– Competitor conquest: lowest ROAS but strong new-to-brand contribution<\/p>\n\n\n\n

                    The benchmark reveals the decline is concentrated in generic terms after a category-wide CPC increase. The brand adjusts bids, improves PDP conversion (images, bullets, reviews), and protects profitable brand coverage\u2014an outcome driven by benchmarking within Commerce & Retail Media<\/strong> operations.<\/p>\n\n\n\n

                    Example 2: Onsite vs offsite retail media for a specialty retailer<\/h3>\n\n\n\n

                    A retailer runs onsite display and offsite audience ads. An overall blended ROAS looks acceptable, but a Retail Media Benchmark<\/strong> split by placement shows:\n– Onsite display: higher conversion rate but limited reach\n– Offsite: lower ROAS but higher incremental reach and assisted conversions<\/p>\n\n\n\n

                    With benchmark ranges per placement, the team stops judging offsite by onsite ROAS standards and instead applies an incrementality-informed benchmark. That improves budget allocation across Commerce & Retail Media<\/strong> tactics.<\/p>\n\n\n\n

                    Example 3: Agency cross-retailer reporting for a challenger brand<\/h3>\n\n\n\n

                    An agency supports a challenger brand selling across multiple retailers. The brand wants \u201cone scorecard.\u201d The agency builds a Retail Media Benchmark<\/strong> framework that normalizes:\n– Attribution window differences\n– New-to-brand definitions (where available)\n– Spend-weighted efficiency targets by retailer<\/p>\n\n\n\n

                    The result is a comparable view that highlights which retailer offers the best marginal returns, enabling smarter expansion decisions in Commerce & Retail Media<\/strong>.<\/p>\n\n\n\n

                    Benefits of Using Retail Media Benchmark<\/h2>\n\n\n\n

                    A disciplined Retail Media Benchmark<\/strong> approach delivers practical benefits:<\/p>\n\n\n\n

                      \n
                    • Faster optimization:<\/strong> Teams know what \u201ctoo high\u201d CPC or \u201ctoo low\u201d conversion looks like by segment.<\/li>\n
                    • Better profitability control:<\/strong> Benchmarks tied to contribution margin prevent scaling campaigns that look good on ROAS but lose money after fees and promos.<\/li>\n
                    • More efficient testing:<\/strong> Benchmark ranges help determine whether a test result is meaningful enough to roll out.<\/li>\n
                    • Improved forecasting:<\/strong> Historical benchmark curves (seasonality, event uplift) make planning more accurate.<\/li>\n
                    • Stronger cross-functional alignment:<\/strong> Finance, sales, and marketing can agree on performance standards in Commerce & Retail Media<\/strong> planning.<\/li>\n<\/ul>\n\n\n\n

                      Challenges of Retail Media Benchmark<\/h2>\n\n\n\n

                      Benchmarking in retail media is powerful, but it has real limitations:<\/p>\n\n\n\n

                        \n
                      • Inconsistent measurement:<\/strong> Retailers differ in attribution, reporting granularity, and what \u201csales\u201d includes.<\/li>\n
                      • Data gaps:<\/strong> Profitability inputs (fees, returns, trade spend) may not be integrated with ad reporting.<\/li>\n
                      • Mix effects:<\/strong> A shift toward upper-funnel placements can depress short-term ROAS while improving long-term outcomes.<\/li>\n
                      • Seasonality and promotions:<\/strong> Benchmarks can be distorted by holidays, deal events, and temporary price changes.<\/li>\n
                      • Small sample sizes:<\/strong> New campaigns or low-volume SKUs produce unstable benchmarks that encourage over-optimization.<\/li>\n<\/ul>\n\n\n\n

                        A Retail Media Benchmark<\/strong> should be treated as a guide with confidence ranges\u2014not a rigid score to chase.<\/p>\n\n\n\n

                        Best Practices for Retail Media Benchmark<\/h2>\n\n\n\n

                        To make benchmarking actionable and trustworthy:<\/p>\n\n\n\n

                          \n
                        • Benchmark by segment, not just totals.<\/strong> Separate by retailer, ad product, keyword intent, and SKU tier.<\/li>\n
                        • Use ranges, not single numbers.<\/strong> Define \u201cgreen\/yellow\/red\u201d bands to reduce knee-jerk reactions.<\/li>\n
                        • Tie benchmarks to business outcomes.<\/strong> Where possible, anchor to contribution margin, incremental sales, or customer acquisition goals.<\/li>\n
                        • Document definitions.<\/strong> Write down attribution windows, inclusion rules, and data sources so reporting remains consistent.<\/li>\n
                        • Refresh on a cadence.<\/strong> Monthly updates are common; high-velocity categories may need weekly monitoring.<\/li>\n
                        • Account for retail fundamentals.<\/strong> Build checks for in-stock rate, price competitiveness, and PDP quality before judging media performance.<\/li>\n
                        • Validate with experiments.<\/strong> Use incrementality tests where feasible to avoid optimizing toward attributed\u2014but not incremental\u2014sales.<\/li>\n<\/ul>\n\n\n\n

                          In Commerce & Retail Media<\/strong>, the best benchmarks are those that change behavior: clearer priorities, smarter bids, and better content and merchandising decisions.<\/p>\n\n\n\n

                          Tools Used for Retail Media Benchmark<\/h2>\n\n\n\n

                          A Retail Media Benchmark<\/strong> program is usually supported by a stack of systems rather than one tool:<\/p>\n\n\n\n

                            \n
                          • Retail media platform reporting:<\/strong> Native dashboards and exports for campaign performance and placements.<\/li>\n
                          • Analytics and measurement tools:<\/strong> Web\/app analytics, conversion tracking (where applicable), and attribution frameworks for onsite\/offsite.<\/li>\n
                          • Data warehouse or data lake:<\/strong> Centralizes performance, product, and margin inputs for consistent calculations.<\/li>\n
                          • BI and reporting dashboards:<\/strong> Standardizes benchmark views, segmentation, and alerts for stakeholders.<\/li>\n
                          • Marketing automation and workflow tools:<\/strong> Helps operationalize actions (naming conventions, QA checklists, change tracking).<\/li>\n
                          • CRM\/CDP (when relevant):<\/strong> Connects retail outcomes to customer strategy, especially for loyalty and retention contexts.<\/li>\n
                          • SEO and content tooling (supporting role):<\/strong> Improves retail PDP discoverability and conversion drivers that materially affect benchmark performance.<\/li>\n<\/ul>\n\n\n\n

                            In Commerce & Retail Media<\/strong>, tool choice matters less than data consistency, governance, and the ability to segment benchmarks in meaningful ways.<\/p>\n\n\n\n

                            Metrics Related to Retail Media Benchmark<\/h2>\n\n\n\n

                            Common metrics used to define or evaluate a Retail Media Benchmark<\/strong> include:<\/p>\n\n\n\n

                            Performance metrics<\/h3>\n\n\n\n
                              \n
                            • Impressions, reach (where available), frequency<\/li>\n
                            • Click-through rate (CTR)<\/li>\n
                            • Conversion rate (CVR)<\/li>\n
                            • Cost per click (CPC)<\/li>\n
                            • Cost per acquisition\/order (CPA\/CPO)<\/li>\n<\/ul>\n\n\n\n

                              Revenue and efficiency metrics<\/h3>\n\n\n\n
                                \n
                              • Return on ad spend (ROAS)<\/li>\n
                              • Advertising cost of sale (ACoS)<\/li>\n
                              • Total ACoS \/ blended efficiency (where used)<\/li>\n
                              • Average order value (AOV)<\/li>\n<\/ul>\n\n\n\n

                                Profit and incrementality metrics<\/h3>\n\n\n\n
                                  \n
                                • Contribution margin after ad spend<\/li>\n
                                • Incremental sales lift (from tests or modeled approaches)<\/li>\n
                                • New-to-brand or new-to-file rate (definition varies by retailer)<\/li>\n<\/ul>\n\n\n\n

                                  Competitive and quality signals<\/h3>\n\n\n\n
                                    \n
                                  • Impression share \/ share of voice (when available)<\/li>\n
                                  • Top-of-search or premium placement rate (where applicable)<\/li>\n
                                  • In-stock rate, price index, ratings\/reviews, PDP content completeness<\/li>\n<\/ul>\n\n\n\n

                                    A strong Retail Media Benchmark<\/strong> ties these metrics together so teams can see why<\/em> a KPI moved, not just that<\/em> it moved.<\/p>\n\n\n\n

                                    Future Trends of Retail Media Benchmark<\/h2>\n\n\n\n

                                    Several trends are shaping how Retail Media Benchmark<\/strong> evolves in Commerce & Retail Media<\/strong>:<\/p>\n\n\n\n

                                      \n
                                    • More automation in bidding and budgeting:<\/strong> AI-driven optimization increases the need for guardrails\u2014benchmarks become policy controls (floors\/ceilings) as much as reporting outputs.<\/li>\n
                                    • Incrementality becomes more central:<\/strong> Brands will rely less on attributed ROAS alone and more on benchmarked incrementality signals, even if they come from smaller test samples.<\/li>\n
                                    • Standardization pressure:<\/strong> As retail media grows, advertisers will demand more consistent definitions across networks, which should improve benchmark portability.<\/li>\n
                                    • Privacy and data access changes:<\/strong> Clean-room style analysis and aggregated reporting may limit granularity, pushing benchmarks toward modeled ranges rather than exact comparisons.<\/li>\n
                                    • Personalization and audience maturity:<\/strong> Benchmarks will increasingly differ by audience cohort (new vs loyal, category buyers vs brand buyers), not just by keyword or placement.<\/li>\n<\/ul>\n\n\n\n

                                      Net: Retail Media Benchmark<\/strong> will shift from \u201creporting averages\u201d to \u201coperating constraints and decision rules\u201d inside Commerce & Retail Media<\/strong>.<\/p>\n\n\n\n

                                      Retail Media Benchmark vs Related Terms<\/h2>\n\n\n\n

                                      Retail Media Benchmark vs KPI target<\/h3>\n\n\n\n

                                      A KPI target is a goal you want to hit (e.g., ROAS \u2265 4.0). A Retail Media Benchmark<\/strong> is the context for setting and interpreting that target\u2014often a range based on history, category norms, and constraints.<\/p>\n\n\n\n

                                      Retail Media Benchmark vs competitive benchmarking<\/h3>\n\n\n\n

                                      Competitive benchmarking compares your performance or presence versus competitors (share of voice, rank, impression share). A Retail Media Benchmark<\/strong> can include competitive inputs, but it also includes internal baselines, profitability context, and segmentation that competitors can\u2019t reveal.<\/p>\n\n\n\n

                                      Retail Media Benchmark vs incrementality testing<\/h3>\n\n\n\n

                                      Incrementality testing measures causal lift (what sales happened because of ads). A Retail Media Benchmark<\/strong> may incorporate incrementality results, but it also covers day-to-day performance standards where always-on testing isn\u2019t feasible.<\/p>\n\n\n\n

                                      Who Should Learn Retail Media Benchmark<\/h2>\n\n\n\n
                                        \n
                                      • Marketers:<\/strong> To set realistic targets, optimize efficiently, and communicate results credibly.<\/li>\n
                                      • Analysts:<\/strong> To build reliable scorecards, normalize data differences, and avoid misleading comparisons.<\/li>\n
                                      • Agencies:<\/strong> To standardize cross-retailer reporting and align clients on what \u201cgood\u201d looks like.<\/li>\n
                                      • Business owners and founders:<\/strong> To ensure retail media spend supports profitable growth, not vanity ROAS.<\/li>\n
                                      • Developers and data teams:<\/strong> To design pipelines, data models, and dashboards that make Retail Media Benchmark<\/strong> operational in Commerce & Retail Media<\/strong> environments.<\/li>\n<\/ul>\n\n\n\n

                                        Summary of Retail Media Benchmark<\/h2>\n\n\n\n

                                        A Retail Media Benchmark<\/strong> is a structured reference point for evaluating and improving retail media performance. It matters because retail media measurement is complex, retailer-specific, and easy to misinterpret without context. When designed with clear segmentation, documented definitions, and business-aware targets, benchmarking becomes a practical operating system for planning, optimization, and governance in Commerce & Retail Media<\/strong>\u2014supporting stronger decisions across Commerce & Retail Media<\/strong> strategy, execution, and measurement.<\/p>\n\n\n\n

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

                                        1) What is a Retail Media Benchmark, in simple terms?<\/h3>\n\n\n\n

                                        A Retail Media Benchmark<\/strong> is a standard (often a range) you use to compare campaign results so you can tell whether performance is strong, average, or weak for a given retailer, placement, and objective.<\/p>\n\n\n\n

                                        2) Are Retail Media Benchmarks the same across all retailers?<\/h3>\n\n\n\n

                                        No. Different retailers use different ad products, shopper behavior patterns, and attribution rules. Good benchmarking is usually retailer-specific and segmented by format and intent.<\/p>\n\n\n\n

                                        3) What metrics should I include in a Retail Media Benchmark dashboard?<\/h3>\n\n\n\n

                                        Start with CTR, CVR, CPC, ROAS\/ACoS, and contribution margin (if available). Add context signals like in-stock rate, price changes, and share-of-voice where possible.<\/p>\n\n\n\n

                                        4) How often should benchmarks be updated?<\/h3>\n\n\n\n

                                        Monthly is common for stable categories. Weekly updates can be useful during peak seasons, major promotions, or rapid growth periods\u2014especially when auction dynamics shift quickly.<\/p>\n\n\n\n

                                        5) How does benchmarking help in Commerce & Retail Media planning?<\/h3>\n\n\n\n

                                        In Commerce & Retail Media<\/strong>, benchmarks turn last quarter\u2019s performance into next quarter\u2019s targets and budgets. They also help forecast seasonality, set bid ceilings, and justify spend changes with evidence.<\/p>\n\n\n\n

                                        6) What\u2019s the biggest mistake teams make with Retail Media Benchmark?<\/h3>\n\n\n\n

                                        Using a single blended benchmark for everything. Benchmarks need segmentation (retailer, ad product, keyword intent, SKU tier) or they\u2019ll hide problems and encourage the wrong optimizations.<\/p>\n\n\n\n

                                        7) Can I use external \u201cindustry benchmarks\u201d safely?<\/h3>\n\n\n\n

                                        Use them as a rough reference only. Without matching category, margin structure, ad mix, and measurement definitions, external benchmarks can mislead. Internal, retailer-specific benchmarks are usually more actionable.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                        Retail media has become a core growth lever for brands and retailers, but performance data is only useful when you can interpret it in context. A **Retail Media Benchmark** is the reference point you use to judge whether a retail media campaign, ad format, keyword strategy, or onsite\/offsite placement is performing \u201cwell\u201d relative to expectations or peers. In **Commerce & Retail Media**, benchmarks turn raw metrics into actionable decisions: what to scale, what to fix, and what \u201cgood\u201d looks like for your category, retailer, and objectives.<\/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":[1886],"tags":[],"class_list":["post-6754","post","type-post","status-publish","format-standard","hentry","category-commerce-retail-media"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/6754","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=6754"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/6754\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=6754"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=6754"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=6754"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}