{"id":8659,"date":"2026-03-26T14:05:33","date_gmt":"2026-03-26T14:05:33","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/mobile-app-benchmark\/"},"modified":"2026-03-26T14:05:33","modified_gmt":"2026-03-26T14:05:33","slug":"mobile-app-benchmark","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/mobile-app-benchmark\/","title":{"rendered":"Mobile App Benchmark: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Mobile & App Marketing"},"content":{"rendered":"\n

A Mobile App Benchmark<\/strong> is the reference point you use to judge whether an app\u2019s marketing and product performance is strong, average, or weak. In Mobile & App Marketing<\/strong>, benchmarks turn raw metrics (installs, activation, retention, revenue) into decisions: which channels to scale, which onboarding step to fix, and what targets are realistic for the next quarter. <\/p>\n\n\n\n

Because mobile growth is influenced by seasonality, platform changes, attribution limits, and fast-moving competitors, Mobile App Benchmark<\/strong> work helps teams avoid guessing. In modern Mobile & App Marketing<\/strong>, it\u2019s how you set credible goals, quantify improvement, and communicate performance in a way that executives, marketers, and developers can align on.<\/p>\n\n\n\n

What Is Mobile App Benchmark?<\/h2>\n\n\n\n

A Mobile App Benchmark<\/strong> is a comparative standard for evaluating an app metric or outcome. The comparison can be against your own history (last month vs this month), a peer group (similar apps in the same category), or an agreed target (a KPI threshold you consider \u201chealthy\u201d). <\/p>\n\n\n\n

The core concept is simple: performance only has meaning in context<\/strong>. A 20% D7 retention rate might be excellent for one category and poor for another. A $3 cost per install might be efficient in one region and unsustainable in another. A Mobile App Benchmark<\/strong> supplies that context.<\/p>\n\n\n\n

From a business perspective, benchmarking helps answer questions like:\n– Are we acquiring users profitably or just cheaply?\n– Is our onboarding converting at a competitive level?\n– Which channel is delivering high-quality users, not just volume?\n– Are changes in retention caused by product issues or traffic mix?<\/p>\n\n\n\n

Within Mobile & App Marketing<\/strong>, a Mobile App Benchmark<\/strong> sits between measurement and action: it translates analytics into planning, optimization, and budget allocation. Inside Mobile & App Marketing<\/strong>, benchmarking also supports cross-team accountability\u2014marketing can\u2019t optimize acquisition without product understanding activation and retention, and vice versa.<\/p>\n\n\n\n

Why Mobile App Benchmark Matters in Mobile & App Marketing<\/h2>\n\n\n\n

A Mobile App Benchmark<\/strong> matters because it improves decision quality. Without a benchmark, teams often chase the wrong wins\u2014like celebrating a low CPI while ignoring a collapsing activation rate.<\/p>\n\n\n\n

Key strategic benefits in Mobile & App Marketing<\/strong> include:<\/p>\n\n\n\n

    \n
  • Goal setting with credibility:<\/strong> Benchmarks prevent unrealistic targets (or under-ambitious ones). They help you set performance ranges by channel, region, and platform.<\/li>\n
  • Budget efficiency:<\/strong> When you know what \u201cgood\u201d looks like for ROAS, payback, or retention, you can reallocate spend faster and with more confidence.<\/li>\n
  • Faster problem diagnosis:<\/strong> Benchmarks highlight whether a drop is abnormal. If your D1 retention falls below your Mobile App Benchmark<\/strong>, you investigate onboarding, crashes, or traffic quality immediately.<\/li>\n
  • Competitive advantage:<\/strong> Teams that benchmark well can out-iterate competitors. They detect shifts (creative fatigue, platform policy changes, seasonality) earlier and respond with sharper experiments.<\/li>\n<\/ul>\n\n\n\n

    In short, Mobile App Benchmark<\/strong> practices make Mobile & App Marketing<\/strong> less reactive and more system-driven.<\/p>\n\n\n\n

    How Mobile App Benchmark Works<\/h2>\n\n\n\n

    A Mobile App Benchmark<\/strong> is less a single report and more a repeatable operating rhythm. In practice, it works through four stages:<\/p>\n\n\n\n

      \n
    1. \n

      Input (what you measure and segment)<\/strong>\n You start with reliable event data (installs, sign-ups, purchases, subscriptions, key in-app actions) and segment it by dimensions that affect performance\u2014channel, campaign, platform (iOS\/Android), geo, device tier, and cohort date.<\/p>\n<\/li>\n

    2. \n

      Processing (normalization and comparison)<\/strong>\n You standardize definitions (what counts as \u201cactive,\u201d how you define \u201cconversion,\u201d what time window you use) and compare metrics to:\n – Your own historical baseline\n – Targets (OKRs, payback rules, margin constraints)\n – Peer or category norms (when available and comparable)<\/p>\n<\/li>\n

    3. \n

      Application (decisions and experiments)<\/strong>\n The benchmark becomes an action trigger: pause underperforming campaigns, adjust bids, change creative, fix onboarding steps, or prioritize product performance work.<\/p>\n<\/li>\n

    4. \n

      Output (targets, alerts, and learnings)<\/strong>\n You publish benchmark ranges, dashboards, and \u201cexceptions\u201d (where performance is outside the expected band). Over time, you improve the benchmark itself as the product, channels, and market evolve.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

      A good Mobile App Benchmark<\/strong> is not static\u2014it adapts to your business model, funnel, and measurement constraints.<\/p>\n\n\n\n

      Key Components of Mobile App Benchmark<\/h2>\n\n\n\n

      Effective Mobile App Benchmark<\/strong> programs typically include these building blocks:<\/p>\n\n\n\n

      Data inputs and tracking foundation<\/h3>\n\n\n\n
        \n
      • App install and open events, deep links, attribution data <\/li>\n
      • In-app events tied to the funnel (registration, tutorial completion, add-to-cart, purchase, subscription start) <\/li>\n
      • Revenue data (net vs gross, refunds, tax handling) <\/li>\n
      • Spend, impressions, clicks, and creative metadata for paid acquisition<\/li>\n<\/ul>\n\n\n\n

        Metrics framework<\/h3>\n\n\n\n
          \n
        • A clearly defined funnel: acquisition \u2192 activation \u2192 engagement\/retention \u2192 monetization <\/li>\n
        • A \u201cNorth Star\u201d metric (if applicable) plus supporting metrics that diagnose movement<\/li>\n<\/ul>\n\n\n\n

          Segmentation rules<\/h3>\n\n\n\n

          Benchmarks are only useful if they reflect meaningful slices, such as:\n– Platform differences (iOS vs Android)\n– Geo and language markets\n– Channel intent (search vs social vs influencer vs ASA-like app store search)\n– New vs returning users, organic vs paid, subscription vs non-subscription<\/p>\n\n\n\n

          Governance and ownership<\/h3>\n\n\n\n
            \n
          • Agreed metric definitions (a shared glossary) <\/li>\n
          • A cadence for review (weekly performance, monthly cohort analysis, quarterly target reset) <\/li>\n
          • Owners for action: growth marketing, lifecycle\/CRM, analytics, product, and engineering<\/li>\n<\/ul>\n\n\n\n

            In Mobile & App Marketing<\/strong>, a Mobile App Benchmark<\/strong> is strongest when the team treats it as a shared contract\u2014how performance is judged and what happens when it\u2019s off-track.<\/p>\n\n\n\n

            Types of Mobile App Benchmark<\/h2>\n\n\n\n

            While \u201cbenchmark\u201d is a general term, Mobile App Benchmark<\/strong> work usually falls into practical categories:<\/p>\n\n\n\n

              \n
            1. \n

              Internal (historical) benchmarks<\/strong>\n Compare performance to your own past cohorts. This is often the most reliable approach because definitions and audiences are consistent.<\/p>\n<\/li>\n

            2. \n

              External (industry\/peer) benchmarks<\/strong>\n Compare to apps in the same category or business model. Useful for context, but riskier if data sources use different definitions or sample mixes.<\/p>\n<\/li>\n

            3. \n

              Cohort benchmarks<\/strong>\n Compare user cohorts by install week\/month to track retention and LTV changes over time.<\/p>\n<\/li>\n

            4. \n

              Channel benchmarks<\/strong>\n Set expected ranges for CPI, CPA, ROAS, payback, or retention by acquisition source.<\/p>\n<\/li>\n

            5. \n

              Funnel-stage benchmarks<\/strong>\n Separate benchmarks for activation (e.g., signup completion), engagement (sessions per user), and monetization (trial-to-paid).<\/p>\n<\/li>\n

            6. \n

              Market\/platform benchmarks<\/strong>\n Maintain separate Mobile App Benchmark<\/strong> targets for iOS vs Android and for top geos, because performance drivers differ materially.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

              Real-World Examples of Mobile App Benchmark<\/h2>\n\n\n\n

              Example 1: Subscription app optimizing paid acquisition quality<\/h3>\n\n\n\n

              A subscription wellness app notices CPI is dropping, but trial-to-paid conversion is falling too. The team introduces a Mobile App Benchmark<\/strong> that pairs acquisition metrics with downstream quality: activation rate, trial start rate, and D30 retention by channel. <\/p>\n\n\n\n

              They discover one social campaign beats CPI benchmarks but underperforms the retention benchmark, leading to poor payback. In Mobile & App Marketing<\/strong>, they shift budget toward higher-intent channels, tighten creative messaging, and set a rule: campaigns must meet both CPI and D7 retention benchmarks to scale.<\/p>\n\n\n\n

              Example 2: E-commerce app improving onboarding and first purchase<\/h3>\n\n\n\n

              An e-commerce app uses a Mobile App Benchmark<\/strong> for activation: account creation, product view depth, add-to-cart rate, and first purchase within 7 days. After a release, activation drops below the benchmark band for Android mid-tier devices. <\/p>\n\n\n\n

              Engineering finds a performance regression on the checkout screen. Marketing pauses spend in affected segments while the fix ships, preventing wasted budget and protecting the funnel\u2014an example of Mobile & App Marketing<\/strong> and product operations working from the same benchmark signals.<\/p>\n\n\n\n

              Example 3: Gaming app managing creative fatigue<\/h3>\n\n\n\n

              A casual game tracks a Mobile App Benchmark<\/strong> for creative performance: IPM (installs per mille), CTR, CVR, and D1\/D7 retention by creative theme. Over two weeks, CTR holds but IPM and CVR slip below benchmark, indicating store page mismatch or ad fatigue. <\/p>\n\n\n\n

              The team refreshes creatives, updates screenshots, and runs A\/B tests on the store listing. Benchmark-based alerts reduce time-to-response and stabilize ROAS.<\/p>\n\n\n\n

              Benefits of Using Mobile App Benchmark<\/h2>\n\n\n\n

              A disciplined Mobile App Benchmark<\/strong> approach can deliver:<\/p>\n\n\n\n

                \n
              • Performance improvements:<\/strong> Clear targets accelerate optimization across acquisition, onboarding, and monetization.<\/li>\n
              • Cost savings:<\/strong> You stop funding campaigns that look good on surface metrics but fail quality benchmarks.<\/li>\n
              • Operational efficiency:<\/strong> Teams spend less time debating definitions and more time running experiments.<\/li>\n
              • Better user experience:<\/strong> Benchmarks tied to activation and retention encourage product improvements that reduce friction.<\/li>\n
              • Stronger forecasting:<\/strong> Cohort benchmarks improve LTV and payback projections, supporting smarter scaling decisions in Mobile & App Marketing<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                Challenges of Mobile App Benchmark<\/h2>\n\n\n\n

                Benchmarking is powerful, but only if you respect its limits:<\/p>\n\n\n\n

                  \n
                • Attribution and privacy constraints:<\/strong> Aggregated measurement and limited user-level data can reduce precision, especially on iOS.<\/li>\n
                • Inconsistent definitions:<\/strong> \u201cActive user\u201d or \u201cconversion\u201d can vary across tools and teams, breaking comparisons.<\/li>\n
                • Category mismatch:<\/strong> External benchmarks can mislead if your app\u2019s model, audience, or geo mix differs.<\/li>\n
                • Seasonality and shocks:<\/strong> Holidays, promotions, and platform algorithm shifts can temporarily distort benchmarks.<\/li>\n
                • Over-optimization risk:<\/strong> Teams may chase benchmark compliance at the expense of innovation (e.g., avoiding new channels because early cohorts underperform).<\/li>\n<\/ul>\n\n\n\n

                  A Mobile App Benchmark<\/strong> should guide decisions, not replace judgment.<\/p>\n\n\n\n

                  Best Practices for Mobile App Benchmark<\/h2>\n\n\n\n

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

                    \n
                  1. \n

                    Standardize definitions first<\/strong>\n Create a metric glossary and enforce consistent time windows (D1\/D7\/D30 retention, 7-day ROAS, etc.).<\/p>\n<\/li>\n

                  2. \n

                    Benchmark ranges, not single numbers<\/strong>\n Use bands (e.g., acceptable \/ good \/ excellent) to account for variance by channel and season.<\/p>\n<\/li>\n

                  3. \n

                    Segment before you conclude<\/strong>\n Always check platform, geo, and channel mix changes before declaring a win or loss against the Mobile App Benchmark<\/strong>.<\/p>\n<\/li>\n

                  4. \n

                    Tie top-line metrics to quality metrics<\/strong>\n Pair CPI with activation and retention; pair ROAS with refund rate or churn; pair conversions with LTV.<\/p>\n<\/li>\n

                  5. \n

                    Refresh benchmarks on a cadence<\/strong>\n Update monthly or quarterly so the benchmark reflects current product reality and market conditions.<\/p>\n<\/li>\n

                  6. \n

                    Operationalize alerts and actions<\/strong>\n Define triggers (e.g., \u201cif D7 retention falls 15% below benchmark for two cohorts, open a product incident\u201d).<\/p>\n<\/li>\n

                  7. \n

                    Document assumptions and data sources<\/strong>\n In Mobile & App Marketing<\/strong>, credibility comes from transparency\u2014where the number came from and how it\u2019s computed.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                    Tools Used for Mobile App Benchmark<\/h2>\n\n\n\n

                    A Mobile App Benchmark<\/strong> program is usually supported by a stack of tool categories rather than one tool:<\/p>\n\n\n\n

                      \n
                    • Analytics tools:<\/strong> Event tracking, funnels, cohorts, retention, and segmentation for in-app behavior. <\/li>\n
                    • Attribution and measurement tools:<\/strong> Channel-level performance, campaign mapping, and conversion reporting under privacy limits. <\/li>\n
                    • Ad platforms:<\/strong> Cost, impressions, clicks, creative metadata, and optimization controls for user acquisition. <\/li>\n
                    • ASO and store performance tools:<\/strong> Store listing conversion insights, keyword visibility context, and experiment tracking. <\/li>\n
                    • A\/B testing and experimentation tools:<\/strong> Onboarding tests, paywall tests, and feature rollouts tied to benchmark movement. <\/li>\n
                    • CRM\/lifecycle tools:<\/strong> Push, email, and in-app messaging performance against engagement benchmarks. <\/li>\n
                    • Data warehouse + BI dashboards:<\/strong> Centralized reporting, consistent definitions, and executive-ready benchmark views. <\/li>\n
                    • App performance monitoring:<\/strong> Crash rate, latency, and device-specific issues that often explain retention benchmark drops.<\/li>\n<\/ul>\n\n\n\n

                      In Mobile & App Marketing<\/strong>, the key is integration: benchmarking fails when spend, events, and revenue can\u2019t be reconciled across systems.<\/p>\n\n\n\n

                      Metrics Related to Mobile App Benchmark<\/h2>\n\n\n\n

                      A strong Mobile App Benchmark<\/strong> typically includes metrics across the full lifecycle:<\/p>\n\n\n\n

                      Acquisition efficiency<\/h3>\n\n\n\n
                        \n
                      • Cost per install (CPI) and cost per action (CPA) <\/li>\n
                      • Click-through rate (CTR), conversion rate (CVR), installs per mille (IPM) <\/li>\n
                      • Share of organic vs paid installs (to interpret blended outcomes)<\/li>\n<\/ul>\n\n\n\n

                        Activation and onboarding<\/h3>\n\n\n\n
                          \n
                        • Signup completion rate <\/li>\n
                        • Tutorial completion rate <\/li>\n
                        • Time to first key action (e.g., first search, first add-to-cart)<\/li>\n<\/ul>\n\n\n\n

                          Engagement and retention<\/h3>\n\n\n\n
                            \n
                          • D1 \/ D7 \/ D30 retention (classic cohort metrics) <\/li>\n
                          • DAU\/MAU (stickiness) <\/li>\n
                          • Sessions per user and time spent (contextual, category-dependent)<\/li>\n<\/ul>\n\n\n\n

                            Monetization and profitability<\/h3>\n\n\n\n
                              \n
                            • ARPU \/ ARPPU <\/li>\n
                            • Trial start rate and trial-to-paid conversion (subscription apps) <\/li>\n
                            • ROAS by day window and payback period <\/li>\n
                            • LTV estimates by cohort (with confidence ranges)<\/li>\n<\/ul>\n\n\n\n

                              Quality and experience<\/h3>\n\n\n\n
                                \n
                              • Crash rate, ANR rate (Android), app start time <\/li>\n
                              • Refund rate, chargeback rate (where relevant) <\/li>\n
                              • Store rating trends and review themes (qualitative benchmarking)<\/li>\n<\/ul>\n\n\n\n

                                Future Trends of Mobile App Benchmark<\/h2>\n\n\n\n

                                Mobile App Benchmark<\/strong> practices are evolving as measurement and competition change:<\/p>\n\n\n\n

                                  \n
                                • AI-assisted benchmarking:<\/strong> Models can forecast expected performance by cohort and flag anomalies faster than manual reviews, improving response time in Mobile & App Marketing<\/strong>.<\/li>\n
                                • More automation in alerting and budget moves:<\/strong> Rule-based and model-based systems will increasingly adjust bids or pause campaigns when benchmarks are violated.<\/li>\n
                                • Privacy-first measurement:<\/strong> Aggregated reporting and modeled conversions will become more common, pushing benchmarks toward ranges and probabilities rather than precise point estimates.<\/li>\n
                                • Personalization benchmarks:<\/strong> Teams will benchmark performance by audience segment and experience variant (e.g., paywall A vs B), not just by channel.<\/li>\n
                                • Creative intelligence:<\/strong> Benchmarks will expand to creative-level diagnostics\u2014messaging, format, and concept performance\u2014because creative is a primary growth lever.<\/li>\n
                                • Incrementality focus:<\/strong> More teams will benchmark incrementality (what advertising truly adds) rather than attributing all conversions at face value.<\/li>\n<\/ul>\n\n\n\n

                                  As Mobile & App Marketing<\/strong> matures, Mobile App Benchmark<\/strong> work will shift from \u201creporting\u201d to \u201cpredicting and preventing.\u201d<\/p>\n\n\n\n

                                  Mobile App Benchmark vs Related Terms<\/h2>\n\n\n\n

                                  Mobile App Benchmark vs KPI<\/h3>\n\n\n\n

                                  A KPI is a metric you track as important (e.g., D30 retention). A Mobile App Benchmark<\/strong> is the comparative standard that tells you whether that KPI is good or bad in a given context. KPIs are the \u201cwhat\u201d; benchmarks are the \u201ccompared to what.\u201d<\/p>\n\n\n\n

                                  Mobile App Benchmark vs Mobile App Analytics<\/h3>\n\n\n\n

                                  Mobile app analytics is the broader practice of collecting and analyzing app data. A Mobile App Benchmark<\/strong> is a specific use of analytics focused on comparison, targets, and performance interpretation.<\/p>\n\n\n\n

                                  Mobile App Benchmark vs Competitive Analysis<\/h3>\n\n\n\n

                                  Competitive analysis studies competitors\u2019 positioning, features, pricing, and go-to-market strategy. A Mobile App Benchmark<\/strong> may include competitive performance comparisons, but it also includes internal benchmarks, funnel-stage targets, and operational thresholds.<\/p>\n\n\n\n

                                  Who Should Learn Mobile App Benchmark<\/h2>\n\n\n\n
                                    \n
                                  • Marketers:<\/strong> To scale acquisition responsibly and connect campaign metrics to downstream value. <\/li>\n
                                  • Analysts:<\/strong> To build trustworthy dashboards, define metrics, and reduce misinterpretation across stakeholders. <\/li>\n
                                  • Agencies:<\/strong> To set realistic expectations, justify recommendations, and compare client performance consistently. <\/li>\n
                                  • Business owners and founders:<\/strong> To understand unit economics and avoid scaling channels that look efficient but lose money. <\/li>\n
                                  • Developers and product teams:<\/strong> To see how performance, stability, and UX changes affect retention and revenue benchmarks\u2014critical alignment for Mobile & App Marketing<\/strong> outcomes.<\/li>\n<\/ul>\n\n\n\n

                                    Summary of Mobile App Benchmark<\/h2>\n\n\n\n

                                    A Mobile App Benchmark<\/strong> is the reference standard used to evaluate app performance across acquisition, activation, retention, and monetization. It matters because it turns metrics into decisions, improving efficiency, forecasting, and cross-team alignment. In Mobile & App Marketing<\/strong>, benchmarking helps you set credible targets, diagnose problems quickly, and build a repeatable optimization engine. Done well, a Mobile App Benchmark<\/strong> becomes a shared language that strengthens Mobile & App Marketing<\/strong> strategy and execution.<\/p>\n\n\n\n

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

                                    1) What is a Mobile App Benchmark in simple terms?<\/h3>\n\n\n\n

                                    A Mobile App Benchmark<\/strong> is the baseline you compare your app\u2019s metrics against to judge performance\u2014such as last quarter\u2019s retention, a target ROAS range, or a peer-group norm.<\/p>\n\n\n\n

                                    2) Should benchmarks be different for iOS and Android?<\/h3>\n\n\n\n

                                    Yes. Platform differences in attribution, user behavior, and device diversity often require separate Mobile App Benchmark<\/strong> targets for iOS and Android to avoid misleading conclusions.<\/p>\n\n\n\n

                                    3) How often should I update a Mobile App Benchmark?<\/h3>\n\n\n\n

                                    Update when your product, channel mix, or market conditions shift. Many teams refresh benchmarks monthly for tactical use and quarterly for goal setting.<\/p>\n\n\n\n

                                    4) What\u2019s the biggest mistake teams make with benchmarking?<\/h3>\n\n\n\n

                                    Using a single number without segmentation. A reliable Mobile App Benchmark<\/strong> usually needs breakdowns by channel, geo, and cohort to be actionable.<\/p>\n\n\n\n

                                    5) How does Mobile & App Marketing use benchmarks differently than web marketing?<\/h3>\n\n\n\n

                                    Mobile & App Marketing<\/strong> relies more on cohort retention, in-app events, app store conversion, and privacy-limited attribution. Benchmarks therefore emphasize activation, retention, LTV, and payback\u2014not just last-click conversions.<\/p>\n\n\n\n

                                    6) Are external industry benchmarks trustworthy?<\/h3>\n\n\n\n

                                    They can be useful for rough context, but treat them as directional. Your best Mobile App Benchmark<\/strong> is often your own historical performance, segmented properly and tied to your business model.<\/p>\n\n\n\n

                                    7) Which metrics should I benchmark first?<\/h3>\n\n\n\n

                                    Start with a small set that maps to your funnel: CPI\/CPA, activation rate, D7 retention, and a monetization metric (trial-to-paid, ARPU, or ROAS). Expand once definitions and data quality are stable.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                    A **Mobile App Benchmark** is the reference point you use to judge whether an app\u2019s marketing and product performance is strong, average, or weak. In **Mobile & App Marketing**, benchmarks turn raw metrics (installs, activation, retention, revenue) into decisions: which channels to scale, which onboarding step to fix, and what targets are realistic for the next quarter.<\/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":[1900],"tags":[],"class_list":["post-8659","post","type-post","status-publish","format-standard","hentry","category-mobile-app-marketing"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/8659","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=8659"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/8659\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=8659"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=8659"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=8659"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}