{"id":8405,"date":"2026-03-26T02:07:50","date_gmt":"2026-03-26T02:07:50","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/referral-scorecard\/"},"modified":"2026-03-26T02:07:50","modified_gmt":"2026-03-26T02:07:50","slug":"referral-scorecard","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/referral-scorecard\/","title":{"rendered":"Referral Scorecard: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Referral Marketing"},"content":{"rendered":"\n

A Referral Scorecard<\/strong> is a structured way to measure, compare, and improve how well referrals contribute to growth. In Direct & Retention Marketing<\/strong>, it acts like a performance dashboard for the referral engine\u2014showing whether customers are actually sharing, whether referred prospects are high quality, and whether the program is profitable and scalable. In Referral Marketing<\/strong>, it\u2019s the bridge between \u201cpeople are talking about us\u201d and \u201cwe can prove referrals drive revenue, efficiently, and in a repeatable way.\u201d<\/p>\n\n\n\n

Modern teams need a Referral Scorecard because referral programs can look healthy on the surface (high share counts or coupon claims) while silently underperforming on fundamentals like conversion quality, fraud, payout efficiency, or long-term retention. A scorecard makes referral performance legible across channels, cohorts, and time\u2014so decisions aren\u2019t based on anecdotes or vanity metrics.<\/p>\n\n\n\n

What Is Referral Scorecard?<\/h2>\n\n\n\n

A Referral Scorecard<\/strong> is a standardized set of metrics, targets, and reporting views that evaluates the performance of a referral program end-to-end\u2014from invite behavior to downstream revenue and retention. It combines leading indicators (like share rate and click-through) with lagging indicators (like conversion rate, CAC, LTV, and churn) to give a balanced picture of impact.<\/p>\n\n\n\n

The core concept is simple: referrals are a funnel. A scorecard ensures you measure each stage consistently and tie it back to business outcomes. The business meaning is accountability: it helps you answer questions such as:<\/p>\n\n\n\n

    \n
  • Are referrals incremental or just stealing conversions from other channels?<\/li>\n
  • Are referred customers better than average customers?<\/li>\n
  • Is the incentive structure sustainable?<\/li>\n
  • Where is the funnel leaking, and what should we fix first?<\/li>\n<\/ul>\n\n\n\n

    In Direct & Retention Marketing<\/strong>, the Referral Scorecard sits alongside lifecycle reporting (activation, retention, reactivation) and complements owned-channel performance tracking (email, SMS, push). Within Referral Marketing<\/strong>, it becomes the operating system for experimentation\u2014guiding incentive tests, messaging tests, placement changes, and audience targeting.<\/p>\n\n\n\n

    Why Referral Scorecard Matters in Direct & Retention Marketing<\/h2>\n\n\n\n

    Referral programs influence both acquisition and retention, which is why they belong in Direct & Retention Marketing<\/strong> strategy, not only growth acquisition. A strong Referral Scorecard matters because it:<\/p>\n\n\n\n

      \n
    • Aligns teams on the same definition of success.<\/strong> Product, marketing, analytics, and finance often disagree on what \u201cgood\u201d looks like. A scorecard forces explicit targets and consistent measurement.<\/li>\n
    • Improves capital efficiency.<\/strong> Referral incentives are effectively spend. A scorecard links that spend to unit economics so you can manage cost per referred customer and payback.<\/li>\n
    • Protects the customer experience.<\/strong> Over-incentivized programs can feel spammy. Scorecards can incorporate quality signals (complaint rate, unsubscribe spikes, low-quality traffic) to prevent short-term wins from harming trust.<\/li>\n
    • Creates competitive advantage.<\/strong> Many competitors run \u201cset-and-forget\u201d referral programs. A disciplined Referral Scorecard enables continuous optimization, better segmentation, and more durable performance.<\/li>\n<\/ul>\n\n\n\n

      In Referral Marketing<\/strong>, outcomes aren\u2019t just \u201cmore shares.\u201d They\u2019re better customers, higher retention, and lower blended acquisition costs\u2014measured consistently over time.<\/p>\n\n\n\n

      How Referral Scorecard Works<\/h2>\n\n\n\n

      A Referral Scorecard is more practical than theoretical. It works as a repeatable measurement and decision workflow:<\/p>\n\n\n\n

        \n
      1. \n

        Inputs (data and triggers)<\/strong>\n You capture referral events (invite sent, link clicked, code applied), user attributes (referrer tenure, segment, geography), and downstream outcomes (trial start, purchase, repeat purchase). In Direct & Retention Marketing<\/strong>, this includes lifecycle events like first-order date, subscription status, and churn markers.<\/p>\n<\/li>\n

      2. \n

        Processing (attribution and normalization)<\/strong>\n Referral data is reconciled across systems (app\/web analytics, CRM, order system). You define attribution rules: what counts as a referral conversion, the lookback window, and how to handle multi-touch journeys. You also filter for fraud and duplicates.<\/p>\n<\/li>\n

      3. \n

        Application (reporting and decisioning)<\/strong>\n The scorecard presents metrics by cohort and segment (new vs existing referrers, high-LTV customers, regions, device types). Teams use it to prioritize experiments\u2014e.g., improve invite conversion, adjust incentives, or change where prompts appear.<\/p>\n<\/li>\n

      4. \n

        Outputs (actions and outcomes)<\/strong>\n The scorecard produces clear actions (pause a placement, raise the reward for a segment, tighten fraud rules) and tracks the business outcomes: incremental revenue, retention lift, and reduced acquisition cost\u2014core Direct & Retention Marketing<\/strong> results.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

        Key Components of Referral Scorecard<\/h2>\n\n\n\n

        A useful Referral Scorecard typically includes these elements:<\/p>\n\n\n\n

        Metrics framework (the \u201cwhat\u201d)<\/h3>\n\n\n\n

        A balanced set of leading and lagging indicators across the referral funnel:\n– Referral participation and sharing behavior\n– Traffic and landing engagement\n– Conversion and revenue outcomes\n– Retention and customer value outcomes\n– Incentive efficiency and fraud controls<\/p>\n\n\n\n

        Data inputs (the \u201cwhere from\u201d)<\/h3>\n\n\n\n

        Common sources include:\n– Web\/app analytics events (invites, clicks, signups)\n– CRM and lifecycle tools (customer status, segments)\n– Order\/subscription systems (revenue, refunds, churn)\n– Customer support signals (complaints, abuse reports)\n– Identity and device signals (to reduce fraud)<\/p>\n\n\n\n

        Reporting views (the \u201chow you see it\u201d)<\/h3>\n\n\n\n

        Effective scorecards include:\n– Weekly executive snapshot (health + trend)\n– Deep-dive funnel view (stage-by-stage)\n– Cohort analysis (performance over time)\n– Segment breakdown (who refers, who converts, who retains)<\/p>\n\n\n\n

        Governance and ownership (the \u201cwho\u201d)<\/h3>\n\n\n\n

        In Direct & Retention Marketing<\/strong>, scorecards work best with clear responsibilities:\n– Marketing owns strategy, creative, and channel orchestration\n– Analytics owns definitions, tracking integrity, and interpretation\n– Product owns referral UX surfaces and eligibility logic\n– Finance\/ops validates incentive cost and profitability\n– Support\/trust teams monitor abuse and policy adherence<\/p>\n\n\n\n

        Types of Referral Scorecard<\/h2>\n\n\n\n

        There aren\u2019t universally \u201cformal\u201d types, but in practice Referral Scorecard approaches vary by context:<\/p>\n\n\n\n

        1) Executive vs operational scorecards<\/h3>\n\n\n\n
          \n
        • Executive scorecard:<\/strong> high-level KPIs (incremental customers, CAC, ROI, revenue contribution).<\/li>\n
        • Operational scorecard:<\/strong> diagnostic metrics (share-to-click, click-to-signup, signup-to-purchase, fraud rate).<\/li>\n<\/ul>\n\n\n\n

          2) Program-level vs cohort\/segment scorecards<\/h3>\n\n\n\n
            \n
          • Program-level:<\/strong> overall health and trend.<\/li>\n
          • Cohort\/segment-level:<\/strong> referrer tenure, VIP tiers, geography, device, channel entry point\u2014critical for Referral Marketing<\/strong> optimization.<\/li>\n<\/ul>\n\n\n\n

            3) Lifecycle-based scorecards<\/h3>\n\n\n\n

            Especially relevant to Direct & Retention Marketing<\/strong>:\n– Acquisition-focused (new customer growth)\n– Retention-focused (repeat purchase, churn reduction)\n– Reactivation-focused (win-back referrals from lapsed customers)<\/p>\n\n\n\n

            Real-World Examples of Referral Scorecard<\/h2>\n\n\n\n

            Example 1: DTC ecommerce improving referral profitability<\/h3>\n\n\n\n

            A DTC brand runs a \u201cGive $10, Get $10\u201d referral offer. The Referral Scorecard shows:\n– High click volume but low purchase conversion on mobile\n– Referred customers have higher refund rates than average\nActions:\n– Optimize the mobile landing flow (fewer steps, clearer terms)\n– Adjust eligibility (reward after the first non-refunded order)\nOutcome:\n– Lower incentive waste and higher net revenue per referred customer, supporting Direct & Retention Marketing<\/strong> efficiency goals.<\/p>\n\n\n\n

            Example 2: SaaS subscription reducing churn via referrals<\/h3>\n\n\n\n

            A SaaS company finds referred users activate faster but churn similarly to other channels. The Referral Scorecard reveals:\n– Referrals from long-tenure customers retain better than referrals from brand-new users\nActions:\n– Target referral prompts after key success milestones\n– Offer a non-monetary incentive for power users (extended features) to reduce payout costs\nOutcome:\n– Improved retention and LTV, strengthening Referral Marketing<\/strong> as a retention lever.<\/p>\n\n\n\n

            Example 3: Marketplace preventing fraud while scaling referrals<\/h3>\n\n\n\n

            A marketplace scales referral incentives and sees a spike in signups. The Referral Scorecard flags:\n– Unusual conversion patterns and multiple accounts per device\n– High incentive payout with low downstream purchases\nActions:\n– Tighten fraud rules (device fingerprinting, delayed payout until first transaction)\n– Add quality checks and monitoring alerts\nOutcome:\n– Program scales with controlled risk, protecting Direct & Retention Marketing<\/strong> performance and brand trust.<\/p>\n\n\n\n

            Benefits of Using Referral Scorecard<\/h2>\n\n\n\n

            A well-built Referral Scorecard delivers concrete benefits:<\/p>\n\n\n\n

              \n
            • Better performance through focus:<\/strong> highlights the exact funnel stage to optimize (share rate vs conversion vs retention).<\/li>\n
            • Lower costs:<\/strong> reduces wasted incentives and identifies where rewards are too generous or poorly targeted.<\/li>\n
            • Faster experimentation:<\/strong> standard definitions make A\/B tests easier to interpret and compare over time.<\/li>\n
            • Higher-quality acquisition:<\/strong> emphasizes downstream value (LTV, retention) so Referral Marketing<\/strong> doesn\u2019t optimize for low-quality volume.<\/li>\n
            • Improved customer experience:<\/strong> catches spammy behaviors or over-messaging that can harm loyalty\u2014central to Direct & Retention Marketing<\/strong>.<\/li>\n<\/ul>\n\n\n\n

              Challenges of Referral Scorecard<\/h2>\n\n\n\n

              Referral measurement is deceptively hard. Common challenges include:<\/p>\n\n\n\n

                \n
              • Attribution ambiguity:<\/strong> referrals often overlap with email, paid social, and organic. Without clear rules, you may double-count or miscredit conversions.<\/li>\n
              • Incrementality measurement:<\/strong> some \u201creferred\u201d customers might have purchased anyway. Measuring true lift often requires tests or holdouts.<\/li>\n
              • Fraud and gaming:<\/strong> self-referrals, coupon abuse, and fake accounts can inflate top-line metrics.<\/li>\n
              • Cross-device identity gaps:<\/strong> users may click on one device and convert on another, breaking the chain.<\/li>\n
              • Lagging outcomes:<\/strong> LTV and retention take time; scorecards must balance fast signals with long-term truth.<\/li>\n
              • Data fragmentation:<\/strong> referral events can live in product analytics while revenue lives in billing systems\u2014difficult to reconcile without strong data practices.<\/li>\n<\/ul>\n\n\n\n

                Best Practices for Referral Scorecard<\/h2>\n\n\n\n

                To make a Referral Scorecard reliable and actionable:<\/p>\n\n\n\n

                  \n
                1. \n

                  Define the referral funnel precisely.<\/strong>\n Document what counts as invite, click, signup, first purchase, qualified purchase, and payout eligibility.<\/p>\n<\/li>\n

                2. \n

                  Use a balanced KPI set.<\/strong>\n Include both growth metrics (new customers) and quality metrics (retention, refund rate). This keeps Referral Marketing<\/strong> aligned with Direct & Retention Marketing<\/strong> goals.<\/p>\n<\/li>\n

                3. \n

                  Separate leading and lagging indicators.<\/strong>\n Track weekly leading metrics (share rate, CTR, conversion) and monthly\/quarterly lagging metrics (LTV, churn, payback).<\/p>\n<\/li>\n

                4. \n

                  Add an incrementality plan.<\/strong>\n Where possible, use holdout groups, geo tests, or time-boxed experiments to estimate true lift.<\/p>\n<\/li>\n

                5. \n

                  Build fraud monitoring into the scorecard.<\/strong>\n Include suspicious-signup rate, payout reversal rate, and anomaly alerts.<\/p>\n<\/li>\n

                6. \n

                  Segment relentlessly.<\/strong>\n Analyze by referrer cohort (tenure, spend tier), acquisition source of the referrer, geography, and device. Many referral wins are hidden in segments.<\/p>\n<\/li>\n

                7. \n

                  Operationalize action thresholds.<\/strong>\n Set clear rules: e.g., \u201cIf refund rate exceeds X% or payout efficiency drops below Y, pause incentives for the segment.\u201d<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                  Tools Used for Referral Scorecard<\/h2>\n\n\n\n

                  A Referral Scorecard is usually assembled from a stack rather than a single tool. Common tool groups include:<\/p>\n\n\n\n

                    \n
                  • Analytics tools:<\/strong> event tracking for invites, clicks, signups, and product activation; funnel and cohort analysis for Direct & Retention Marketing<\/strong>.<\/li>\n
                  • CRM systems:<\/strong> customer profiles, segmentation, lifecycle status, and communication history that inform who gets prompted to refer.<\/li>\n
                  • Marketing automation tools:<\/strong> email\/SMS\/push orchestration for referral prompts, reminders, and reward notifications\u2014core to Direct & Retention Marketing<\/strong> execution.<\/li>\n
                  • Reporting dashboards:<\/strong> centralized scorecard views, scheduled reports, and stakeholder-friendly KPI summaries.<\/li>\n
                  • Data warehouses and ETL\/ELT pipelines:<\/strong> unify referral events with orders, subscription billing, and support data for trustworthy reporting.<\/li>\n
                  • Experimentation platforms:<\/strong> run A\/B tests on incentive structure, referral placements, and messaging.<\/li>\n
                  • Fraud and risk systems (where needed):<\/strong> detect abuse patterns and enforce payout rules.<\/li>\n<\/ul>\n\n\n\n

                    The best setup is the one that ensures consistent definitions, reliable data, and rapid access for decisions.<\/p>\n\n\n\n

                    Metrics Related to Referral Scorecard<\/h2>\n\n\n\n

                    A strong Referral Scorecard typically includes metrics across five categories:<\/p>\n\n\n\n

                    Funnel and engagement metrics<\/h3>\n\n\n\n
                      \n
                    • Invite rate (percent of customers who send a referral)<\/li>\n
                    • Share rate by channel (link share, email share, in-app share)<\/li>\n
                    • Click-through rate (CTR) on referral links<\/li>\n
                    • Landing page conversion rate (visitor \u2192 signup)<\/li>\n
                    • Referral code\/application rate<\/li>\n<\/ul>\n\n\n\n

                      Conversion and revenue metrics<\/h3>\n\n\n\n
                        \n
                      • Referred signup-to-purchase conversion rate<\/li>\n
                      • Average order value (AOV) of referred customers<\/li>\n
                      • Gross margin from referred customers<\/li>\n
                      • Revenue per referral click \/ per invite sent<\/li>\n<\/ul>\n\n\n\n

                        Efficiency and ROI metrics<\/h3>\n\n\n\n
                          \n
                        • Incentive cost per referred customer (including both sides of the reward)<\/li>\n
                        • Payback period on referral incentive spend<\/li>\n
                        • Referral CAC (fully loaded) vs other channels<\/li>\n
                        • Incremental lift (estimated) from referral activity<\/li>\n<\/ul>\n\n\n\n

                          Customer quality and retention metrics (Direct & Retention Marketing alignment)<\/h3>\n\n\n\n
                            \n
                          • Day 30\/60\/90 retention of referred customers<\/li>\n
                          • Repeat purchase rate or subscription renewal rate<\/li>\n
                          • Churn rate vs non-referred cohorts<\/li>\n
                          • LTV of referred customers vs baseline<\/li>\n<\/ul>\n\n\n\n

                            Risk and trust metrics<\/h3>\n\n\n\n
                              \n
                            • Fraud rate \/ suspicious account rate<\/li>\n
                            • Payout reversal or chargeback rate<\/li>\n
                            • Refund rate for referred purchases<\/li>\n
                            • Support ticket rate tied to referral confusion or abuse<\/li>\n<\/ul>\n\n\n\n

                              Future Trends of Referral Scorecard<\/h2>\n\n\n\n

                              Referral programs are becoming more measurable, automated, and privacy-aware. Key trends shaping the Referral Scorecard include:<\/p>\n\n\n\n

                                \n
                              • AI-assisted insights and anomaly detection:<\/strong> faster identification of fraud spikes, conversion drops, or segment opportunities.<\/li>\n
                              • Personalized referral experiences:<\/strong> dynamically tailoring prompts, rewards, and timing based on predicted propensity\u2014deeply connected to Direct & Retention Marketing<\/strong> personalization.<\/li>\n
                              • More rigorous incrementality methods:<\/strong> teams increasingly use experimentation designs to prove real lift rather than reporting last-click credit.<\/li>\n
                              • Privacy-driven measurement changes:<\/strong> reduced reliance on third-party identifiers pushes brands toward first-party event tracking and modeled attribution.<\/li>\n
                              • Lifecycle integration:<\/strong> referrals increasingly appear as retention tactics (post-purchase prompts, loyalty-triggered sharing), so the Referral Scorecard will expand to include lifecycle milestones and customer experience signals.<\/li>\n<\/ul>\n\n\n\n

                                Referral Scorecard vs Related Terms<\/h2>\n\n\n\n

                                Referral Scorecard vs Referral Program<\/h3>\n\n\n\n

                                A referral program<\/strong> is the initiative (rules, incentives, placements, messaging). A Referral Scorecard<\/strong> is the measurement and management framework used to evaluate and optimize that initiative. You can run a program without a scorecard, but you\u2019ll struggle to improve it reliably.<\/p>\n\n\n\n

                                Referral Scorecard vs Referral Attribution<\/h3>\n\n\n\n

                                Referral attribution<\/strong> is the method of assigning credit for conversions to referral interactions (and often resolving multi-touch journeys). The Referral Scorecard<\/strong> uses attribution outputs, but also includes cost, retention, fraud, and operational KPIs.<\/p>\n\n\n\n

                                Referral Scorecard vs Net Promoter Score (NPS)<\/h3>\n\n\n\n

                                NPS<\/strong> measures stated likelihood to recommend, based on a survey question. A Referral Scorecard<\/strong> measures actual referral behavior and business impact. In Referral Marketing<\/strong>, NPS can be a useful leading indicator, but it doesn\u2019t replace conversion and value metrics.<\/p>\n\n\n\n

                                Who Should Learn Referral Scorecard<\/h2>\n\n\n\n

                                A Referral Scorecard is valuable across roles:<\/p>\n\n\n\n

                                  \n
                                • Marketers:<\/strong> to optimize Referral Marketing<\/strong> performance, improve incentives, and integrate referrals into Direct & Retention Marketing<\/strong> campaigns.<\/li>\n
                                • Analysts:<\/strong> to build reliable definitions, cohort views, and incrementality tests that make results credible.<\/li>\n
                                • Agencies and consultants:<\/strong> to audit referral performance and create optimization roadmaps that tie to unit economics.<\/li>\n
                                • Business owners and founders:<\/strong> to understand whether referrals are truly scalable and profitable, not just \u201cbuzz.\u201d<\/li>\n
                                • Developers and product teams:<\/strong> to implement clean event tracking, referral logic, eligibility rules, and fraud-resistant flows.<\/li>\n<\/ul>\n\n\n\n

                                  Summary of Referral Scorecard<\/h2>\n\n\n\n

                                  A Referral Scorecard<\/strong> is a structured measurement framework that tracks referral performance from sharing behavior through conversion, cost, and long-term customer value. It matters because it turns Referral Marketing<\/strong> into an accountable growth lever\u2014showing what\u2019s working, what\u2019s wasting budget, and which segments drive the best customers. In Direct & Retention Marketing<\/strong>, it connects referrals to lifecycle outcomes like retention, repeat purchase, and churn, enabling smarter incentives, better customer experiences, and more predictable growth.<\/p>\n\n\n\n

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

                                  1) What is a Referral Scorecard and what should it include?<\/h3>\n\n\n\n

                                  A Referral Scorecard is a standardized set of referral KPIs, targets, and reporting views. It should include funnel metrics (invites, clicks, conversions), efficiency metrics (incentive cost, payback), and quality metrics (retention, LTV, refunds\/fraud).<\/p>\n\n\n\n

                                  2) How often should Direct & Retention Marketing teams review a referral scorecard?<\/h3>\n\n\n\n

                                  Most teams review leading indicators weekly (shares, clicks, conversion) and review lagging indicators monthly or quarterly (LTV, churn, payback). The right cadence depends on traffic volume and purchase cycle length.<\/p>\n\n\n\n

                                  3) Which metrics prove Referral Marketing is driving real growth?<\/h3>\n\n\n\n

                                  The strongest proof combines incrementality (lift from tests\/holdouts) with downstream value (LTV, retention) and efficiency (incentive cost per incremental customer). High share counts alone don\u2019t prove impact.<\/p>\n\n\n\n

                                  4) How do you prevent referral fraud from inflating scorecard results?<\/h3>\n\n\n\n

                                  Use eligibility rules (delayed payouts until a qualified event), monitor suspicious patterns (device duplication, rapid signups), and include fraud KPIs directly in the Referral Scorecard so problems are visible early.<\/p>\n\n\n\n

                                  5) Can small businesses benefit from a Referral Scorecard, or is it only for enterprises?<\/h3>\n\n\n\n

                                  Small businesses benefit significantly. Start simple: track invites, referred purchases, incentive cost, and repeat purchase rate. As volume grows, add cohort retention and incrementality methods.<\/p>\n\n\n\n

                                  6) How do you connect a Referral Scorecard to revenue and LTV accurately?<\/h3>\n\n\n\n

                                  Unify referral event tracking with order\/subscription data, use consistent customer IDs, define what counts as \u201cqualified revenue,\u201d and report LTV by cohort (referred vs non-referred) over the same time window.<\/p>\n\n\n\n

                                  7) What\u2019s the biggest mistake teams make with referral measurement?<\/h3>\n\n\n\n

                                  Optimizing only for top-of-funnel activity (shares, clicks) without tying performance to Direct & Retention Marketing<\/strong> outcomes like retention, margin, and payback. This often leads to costly incentives and low-quality growth.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                  A **Referral Scorecard** is a structured way to measure, compare, and improve how well referrals contribute to growth. In **Direct & Retention Marketing**, it acts like a performance dashboard for the referral engine\u2014showing whether customers are actually sharing, whether referred prospects are high quality, and whether the program is profitable and scalable. In **Referral Marketing**, it\u2019s the bridge between \u201cpeople are talking about us\u201d and \u201cwe can prove referrals drive revenue, efficiently, and in a repeatable way.\u201d<\/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":[1896],"tags":[],"class_list":["post-8405","post","type-post","status-publish","format-standard","hentry","category-referral-marketing"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/8405","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=8405"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/8405\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=8405"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=8405"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=8405"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}