{"id":7701,"date":"2026-03-24T23:09:16","date_gmt":"2026-03-24T23:09:16","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/customer-health-score\/"},"modified":"2026-03-24T23:09:16","modified_gmt":"2026-03-24T23:09:16","slug":"customer-health-score","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/customer-health-score\/","title":{"rendered":"Customer Health Score: What It Is, Key Features, Benefits, Use Cases, and How It Fits in CRM Marketing"},"content":{"rendered":"\n

Customer relationships don\u2019t fail all at once\u2014they weaken through small signals: lower usage, slower renewals, fewer purchases, more support friction, and reduced engagement with lifecycle messaging. A Customer Health Score<\/strong> is a structured way to quantify those signals into a single, actionable view of how \u201chealthy\u201d a customer relationship is right now.<\/p>\n\n\n\n

In Direct & Retention Marketing<\/strong>, that single view helps teams prioritize the right interventions\u2014onboarding, education, replenishment, loyalty offers, win-back sequences, or human outreach\u2014before revenue is at risk. In CRM Marketing<\/strong>, it becomes the backbone for segmentation, automation rules, and personalization across email, SMS, in-app messaging, direct mail, and customer success motions.<\/p>\n\n\n\n

\n\n\n\n

What Is Customer Health Score?<\/h2>\n\n\n\n

A Customer Health Score<\/strong> is a composite score that represents the likelihood a customer will retain, expand, or churn<\/strong>, based on behavioral, transactional, and relationship signals. It turns scattered customer data into a consistent, repeatable indicator that teams can use to make better decisions.<\/p>\n\n\n\n

At its core, the concept is simple:<\/p>\n\n\n\n

    \n
  • Inputs<\/strong> (usage, purchases, engagement, support, satisfaction, account signals) <\/li>\n
  • Weighted logic<\/strong> (rules or models) <\/li>\n
  • Output<\/strong> (a score and\/or health category such as Green\/Yellow\/Red)<\/li>\n<\/ul>\n\n\n\n

    The business meaning is even more important: a Customer Health Score is an early-warning system and a growth compass. It helps organizations answer practical questions like \u201cWhich customers are drifting?\u201d and \u201cWhich customers are ready for an upsell?\u201d without relying on intuition alone.<\/p>\n\n\n\n

    In Direct & Retention Marketing<\/strong>, it determines who gets nurturing vs. who needs rescue. In CRM Marketing<\/strong>, it becomes a field your segmentation and automation can reliably use across channels and campaigns.<\/p>\n\n\n\n

    \n\n\n\n

    Why Customer Health Score Matters in Direct & Retention Marketing<\/h2>\n\n\n\n

    Direct & Retention Marketing<\/strong> is fundamentally about protecting and growing existing customer revenue more efficiently than acquiring new customers. A Customer Health Score supports that strategy by making retention proactive rather than reactive.<\/p>\n\n\n\n

    Key reasons it matters:<\/p>\n\n\n\n

      \n
    • Earlier churn prevention:<\/strong> Marketing and customer teams can act on risk signals weeks or months before cancellation or inactivity.<\/li>\n
    • Smarter lifecycle orchestration:<\/strong> Different health tiers map naturally to onboarding, adoption, loyalty, replenishment, and win-back tracks.<\/li>\n
    • More efficient spend:<\/strong> Retention incentives can be targeted to customers who truly need them instead of being broadly discounted.<\/li>\n
    • Better customer experience:<\/strong> Customers receive relevant support and messaging aligned to their actual behavior, not generic sequences.<\/li>\n
    • Competitive advantage:<\/strong> Companies that operationalize health can stabilize revenue, improve LTV, and react faster to customer needs.<\/li>\n<\/ul>\n\n\n\n

      In short, Customer Health Score connects behavior to action\u2014exactly what CRM Marketing<\/strong> systems are meant to do.<\/p>\n\n\n\n

      \n\n\n\n

      How Customer Health Score Works<\/h2>\n\n\n\n

      A Customer Health Score is conceptual, but it becomes practical when implemented as a repeatable workflow:<\/p>\n\n\n\n

        \n
      1. \n

        Input (signals are collected)<\/strong>\n – Product usage (logins, key feature adoption, frequency)\n – Purchase behavior (order cadence, renewals, contract changes)\n – Marketing engagement (email clicks, SMS replies, site sessions)\n – Support signals (ticket volume, time-to-resolution, sentiment)\n – Relationship inputs (NPS\/CSAT, QBR outcomes, stakeholder changes)<\/p>\n<\/li>\n

      2. \n

        Analysis (signals are normalized and weighted)<\/strong>\n – Metrics are standardized (e.g., \u201cusage this week vs. baseline\u201d)\n – Each metric gets a weight based on business relevance\n – Thresholds define what \u201cgood,\u201d \u201cat risk,\u201d and \u201ccritical\u201d look like<\/p>\n<\/li>\n

      3. \n

        Execution (the score triggers actions)<\/strong>\n – Direct & Retention Marketing<\/strong> automations route customers into journeys:<\/p>\n

          \n
        • onboarding education<\/li>\n
        • adoption nudges<\/li>\n
        • renewal prep<\/li>\n
        • win-back offers<\/li>\n
        • Sales\/CS alerts are created for high-value accounts in danger<\/li>\n<\/ul>\n<\/li>\n
        • \n

          Output (score + interpretation)<\/strong>\n – A numerical score (e.g., 0\u2013100) and\/or categorical health status\n – Dashboards, segments, and audiences for CRM Marketing<\/strong> activation\n – Measured outcomes: churn reduction, expansion lift, engagement recovery<\/p>\n<\/li>\n<\/ol>\n\n\n\n

          The best implementations treat the Customer Health Score as a living system\u2014reviewed, tuned, and validated against retention and revenue outcomes.<\/p>\n\n\n\n

          \n\n\n\n

          Key Components of Customer Health Score<\/h2>\n\n\n\n

          A reliable Customer Health Score depends on more than a formula. It requires aligned data, process, and ownership.<\/p>\n\n\n\n

          Data inputs and metrics<\/h3>\n\n\n\n

          Common categories include:<\/p>\n\n\n\n

            \n
          • Adoption\/usage:<\/strong> active days, feature depth, time-to-value, seat utilization<\/li>\n
          • Commercial:<\/strong> renewal date proximity, plan tier, ARPA, discounting, payment failures<\/li>\n
          • Engagement:<\/strong> email engagement, in-app events, community participation, content consumption<\/li>\n
          • Support:<\/strong> ticket rate, severity, backlog, satisfaction, escalations<\/li>\n
          • Voice of customer:<\/strong> NPS\/CSAT, surveys, qualitative feedback<\/li>\n<\/ul>\n\n\n\n

            Systems and integration<\/h3>\n\n\n\n
              \n
            • CRM + billing\/subscription + product analytics + support platform<\/li>\n
            • Identity resolution (account IDs, user IDs, email matching)<\/li>\n
            • Data pipelines (ETL\/ELT), event tracking, and a consistent schema<\/li>\n<\/ul>\n\n\n\n

              Process and governance<\/h3>\n\n\n\n
                \n
              • Clear definitions (what \u201cactive\u201d means, how churn is defined)<\/li>\n
              • Version control for score logic<\/li>\n
              • Guardrails to prevent per-team \u201cscore drift\u201d<\/li>\n
              • Documentation so CRM Marketing<\/strong> and customer success interpret health consistently<\/li>\n<\/ul>\n\n\n\n

                Team responsibilities<\/h3>\n\n\n\n
                  \n
                • Marketing: segmentation, journeys, offers, experimentation<\/li>\n
                • Customer success: outreach plays, risk management, QBR workflows<\/li>\n
                • Analytics\/data: validation, weighting, monitoring, bias checks<\/li>\n
                • Product: usage instrumentation and adoption levers<\/li>\n<\/ul>\n\n\n\n
                  \n\n\n\n

                  Types of Customer Health Score<\/h2>\n\n\n\n

                  There are no universal \u201cofficial\u201d types, but there are practical approaches that teams commonly use:<\/p>\n\n\n\n

                  1) Rules-based scoring<\/h3>\n\n\n\n

                  A point system with clear thresholds (e.g., +10 for weekly usage, -15 for payment failure). This is easier to explain and faster to deploy in CRM Marketing<\/strong>.<\/p>\n\n\n\n

                  2) Predictive or model-based scoring<\/h3>\n\n\n\n

                  Statistical or machine-learning models estimate churn or expansion probability from patterns. This can outperform rules but requires strong data quality and ongoing monitoring.<\/p>\n\n\n\n

                  3) Segment-specific scoring<\/h3>\n\n\n\n

                  Different formulas for different customer groups (SMB vs. enterprise, high-frequency buyers vs. annual renewals). This is often necessary because \u201chealthy behavior\u201d varies by segment.<\/p>\n\n\n\n

                  4) Lifecycle-stage scoring<\/h3>\n\n\n\n

                  Different health logic for onboarding vs. mature customers. A new customer may be \u201chealthy\u201d with onboarding milestones even if usage is still ramping.<\/p>\n\n\n\n

                  \n\n\n\n

                  Real-World Examples of Customer Health Score<\/h2>\n\n\n\n

                  Example 1: Subscription SaaS renewal protection<\/h3>\n\n\n\n

                  A SaaS company uses a Customer Health Score combining weekly active usage, feature adoption, support escalation rate, and NPS. In Direct & Retention Marketing<\/strong>, \u201cYellow\u201d customers automatically enter a 21-day adoption sequence with in-app tips and targeted training emails. In CRM Marketing<\/strong>, high-value \u201cRed\u201d accounts trigger an alert to customer success plus a personalized renewal-prep campaign. Result: fewer surprise churns and smoother renewal forecasting.<\/p>\n\n\n\n

                  Example 2: Ecommerce replenishment and churn prevention<\/h3>\n\n\n\n

                  A replenishable goods brand creates a Customer Health Score based on time since last purchase vs. typical reorder window, email\/SMS engagement, and customer service issues. Customers trending unhealthy receive reminder flows and replenishment bundles; healthy repeat buyers receive loyalty tier messaging. This Direct & Retention Marketing<\/strong> approach reduces blanket discounting while improving repeat rate.<\/p>\n\n\n\n

                  Example 3: B2B services expansion targeting<\/h3>\n\n\n\n

                  A services firm scores health using project milestone completion, stakeholder engagement, invoice timeliness, and satisfaction surveys. In CRM Marketing<\/strong>, \u201cGreen\u201d accounts are segmented into cross-sell campaigns aligned to service maturity, while \u201cYellow\u201d accounts get educational content and a check-in sequence. The score becomes a shared language across marketing, account management, and finance.<\/p>\n\n\n\n

                  \n\n\n\n

                  Benefits of Using Customer Health Score<\/h2>\n\n\n\n

                  When implemented well, a Customer Health Score improves both performance and alignment:<\/p>\n\n\n\n

                    \n
                  • Higher retention and lower churn<\/strong> through earlier interventions<\/li>\n
                  • Improved LTV<\/strong> by identifying expansion-ready customers<\/li>\n
                  • More efficient incentives<\/strong> by targeting discounts or perks to the right segments<\/li>\n
                  • Better personalization<\/strong> in Direct & Retention Marketing<\/strong> journeys (message, channel, timing)<\/li>\n
                  • Cleaner prioritization<\/strong> for customer success outreach and playbooks<\/li>\n
                  • Shared measurement<\/strong> across marketing, sales, product, and support via CRM Marketing<\/strong> fields and dashboards<\/li>\n<\/ul>\n\n\n\n
                    \n\n\n\n

                    Challenges of Customer Health Score<\/h2>\n\n\n\n

                    A Customer Health Score can fail when teams treat it as a simple number rather than a measurement system.<\/p>\n\n\n\n

                    Common challenges include:<\/p>\n\n\n\n

                      \n
                    • Data gaps and tracking inconsistencies:<\/strong> missing product events, unlinked identities, incomplete billing signals<\/li>\n
                    • Wrong weights and thresholds:<\/strong> scoring what\u2019s easy to measure instead of what drives retention<\/li>\n
                    • Lagging indicators disguised as predictors:<\/strong> using metrics that only change after churn is inevitable<\/li>\n
                    • One-size-fits-all scoring:<\/strong> healthy behavior differs by segment, plan, and lifecycle stage<\/li>\n
                    • Operational misuse:<\/strong> campaigns triggered without context (e.g., sending discounts to customers who would have renewed anyway)<\/li>\n
                    • Organizational confusion:<\/strong> marketing, CS, and product interpret the same score differently without governance<\/li>\n<\/ul>\n\n\n\n
                      \n\n\n\n

                      Best Practices for Customer Health Score<\/h2>\n\n\n\n

                      To make Customer Health Score trustworthy and actionable in Direct & Retention Marketing<\/strong> and CRM Marketing<\/strong>, focus on these practices:<\/p>\n\n\n\n

                        \n
                      1. \n

                        Start with outcomes, not metrics<\/strong>\n – Define what you want to predict or improve: churn, renewal, repeat purchase rate, expansion.<\/p>\n<\/li>\n

                      2. \n

                        Use a small set of high-signal inputs<\/strong>\n – Begin with 5\u201310 metrics that clearly relate to retention or repeat behavior.<\/p>\n<\/li>\n

                      3. \n

                        Validate against historical cohorts<\/strong>\n – Compare past health scores to actual churn\/renewal outcomes and tune weights.<\/p>\n<\/li>\n

                      4. \n

                        Separate \u201crisk\u201d and \u201cvalue\u201d<\/strong>\n – Consider tracking both health and account value so teams don\u2019t overreact to low-value noise or miss high-value risk.<\/p>\n<\/li>\n

                      5. \n

                        Operationalize with clear playbooks<\/strong>\n – Define what happens at each threshold: what journey, what offer, what outreach, what SLA.<\/p>\n<\/li>\n

                      6. \n

                        Review monthly and version the logic<\/strong>\n – Treat changes like a product release: document updates, measure impact, and avoid constant tinkering.<\/p>\n<\/li>\n

                      7. \n

                        Make it explainable<\/strong>\n – Even if you use predictive scoring, provide \u201creason codes\u201d (e.g., low usage, high ticket volume) so actions are targeted.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                        \n\n\n\n

                        Tools Used for Customer Health Score<\/h2>\n\n\n\n

                        Customer Health Score is tool-enabled, but vendor-neutral in concept. Typical tool groups include:<\/p>\n\n\n\n

                          \n
                        • CRM systems:<\/strong> store the score as an account\/contact field, power segmentation and routing for CRM Marketing<\/strong><\/li>\n
                        • Marketing automation platforms:<\/strong> trigger Direct & Retention Marketing<\/strong> journeys based on health tiers<\/li>\n
                        • Product analytics and event tracking:<\/strong> capture adoption and feature usage signals<\/li>\n
                        • Customer support platforms:<\/strong> provide ticket volume, resolution time, and satisfaction signals<\/li>\n
                        • Data warehouse + pipelines:<\/strong> unify billing, product, and engagement data; compute the score at scale<\/li>\n
                        • BI and reporting dashboards:<\/strong> monitor score distribution, cohort trends, and performance outcomes<\/li>\n
                        • Experimentation tools:<\/strong> test retention interventions by health segment (offers, messaging, cadence)<\/li>\n<\/ul>\n\n\n\n

                          The key is not the tool list\u2014it\u2019s consistent identity matching and reliable refresh schedules so health reflects reality.<\/p>\n\n\n\n

                          \n\n\n\n

                          Metrics Related to Customer Health Score<\/h2>\n\n\n\n

                          A Customer Health Score is built from metrics, but it also influences how teams measure retention performance. Useful related metrics include:<\/p>\n\n\n\n

                            \n
                          • Churn rate:<\/strong> customer churn and revenue churn (gross and net)<\/li>\n
                          • Retention rates:<\/strong> logo retention, revenue retention, repeat purchase rate<\/li>\n
                          • Engagement metrics:<\/strong> active days, session frequency, email\/SMS engagement rate, in-app event completion<\/li>\n
                          • Adoption metrics:<\/strong> time-to-first-value, feature adoption rate, seat utilization<\/li>\n
                          • Customer experience metrics:<\/strong> NPS, CSAT, CES, complaint rate<\/li>\n
                          • Support metrics:<\/strong> time-to-first-response, resolution time, reopen rate<\/li>\n
                          • Commercial metrics:<\/strong> renewal rate, expansion rate, downgrade rate, payment failure rate<\/li>\n
                          • Efficiency metrics:<\/strong> cost per retained customer, incentive cost per save, automation-to-human handoff rate<\/li>\n<\/ul>\n\n\n\n

                            In Direct & Retention Marketing<\/strong>, the goal is to connect health improvements to measurable business outcomes (retained revenue, reduced churn, increased repeat).<\/p>\n\n\n\n

                            \n\n\n\n

                            Future Trends of Customer Health Score<\/h2>\n\n\n\n

                            Customer Health Score is evolving as data and privacy expectations change:<\/p>\n\n\n\n

                              \n
                            • More automation with guardrails:<\/strong> automated segmentation and journey routing, with explainability and approval workflows.<\/li>\n
                            • AI-assisted \u201creason codes\u201d:<\/strong> models that not only score health but identify the top drivers of risk (e.g., \u201cusage dropped 40% vs. baseline\u201d).<\/li>\n
                            • Real-time and event-driven scoring:<\/strong> updates based on meaningful events (payment failure, usage cliff, negative support sentiment) rather than weekly batches.<\/li>\n
                            • Personalization beyond email:<\/strong> health-driven messaging across in-app, SMS, push, and even offline channels in Direct & Retention Marketing<\/strong>.<\/li>\n
                            • Privacy-aware measurement:<\/strong> greater reliance on first-party and product data, stronger consent management, and careful use of sensitive attributes.<\/li>\n
                            • Unified lifecycle intelligence:<\/strong> tighter connection between Customer Health Score and next-best-action systems inside CRM Marketing<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                              The direction is clear: health scoring will be less about static dashboards and more about operational decisioning across the retention funnel.<\/p>\n\n\n\n

                              \n\n\n\n

                              Customer Health Score vs Related Terms<\/h2>\n\n\n\n

                              Customer Health Score vs NPS<\/h3>\n\n\n\n
                                \n
                              • NPS<\/strong> measures sentiment at a point in time (\u201cHow likely to recommend?\u201d).<\/li>\n
                              • Customer Health Score<\/strong> blends sentiment with behavior and commercial signals to estimate retention or growth likelihood.<\/li>\n
                              • Practically: NPS is one input; health is the decision framework.<\/li>\n<\/ul>\n\n\n\n

                                Customer Health Score vs Churn Risk Score<\/h3>\n\n\n\n
                                  \n
                                • A churn risk score<\/strong> focuses narrowly on likelihood to churn.<\/li>\n
                                • Customer Health Score<\/strong> is broader: it can reflect adoption, satisfaction, and expansion readiness, not just risk.<\/li>\n
                                • Practically: churn risk can be a component or a parallel metric to health.<\/li>\n<\/ul>\n\n\n\n

                                  Customer Health Score vs Lead Score<\/h3>\n\n\n\n
                                    \n
                                  • Lead scoring<\/strong> ranks prospects for conversion.<\/li>\n
                                  • Customer Health Score<\/strong> ranks customers for retention and expansion actions.<\/li>\n
                                  • Practically: both are scoring systems, but they serve different lifecycle stages and are owned by different parts of CRM Marketing<\/strong>.<\/li>\n<\/ul>\n\n\n\n
                                    \n\n\n\n

                                    Who Should Learn Customer Health Score<\/h2>\n\n\n\n
                                      \n
                                    • Marketers:<\/strong> to improve segmentation, personalization, and offer strategy in Direct & Retention Marketing<\/strong><\/li>\n
                                    • Analysts:<\/strong> to design reliable scoring logic, validate predictors, and quantify incremental lift<\/li>\n
                                    • Agencies:<\/strong> to build retention programs and lifecycle automations that prove value beyond acquisition<\/li>\n
                                    • Business owners and founders:<\/strong> to forecast revenue more accurately and prioritize retention investments<\/li>\n
                                    • Developers and data teams:<\/strong> to implement event tracking, pipelines, identity resolution, and scoring refresh logic inside CRM Marketing<\/strong> stacks<\/li>\n<\/ul>\n\n\n\n
                                      \n\n\n\n

                                      Summary of Customer Health Score<\/h2>\n\n\n\n

                                      A Customer Health Score<\/strong> is a composite indicator of how likely a customer is to retain, renew, repeat purchase, or expand based on behavioral, transactional, engagement, and experience signals. It matters because it transforms retention from reactive firefighting into proactive lifecycle management. In Direct & Retention Marketing<\/strong>, it powers timely interventions and smarter personalization. In CRM Marketing<\/strong>, it becomes a core field for segmentation, automation, and cross-team alignment\u2014ultimately improving retention, efficiency, and customer experience.<\/p>\n\n\n\n

                                      \n\n\n\n

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

                                      1) What is a Customer Health Score used for?<\/h3>\n\n\n\n

                                      It\u2019s used to identify which customers are thriving, which are at risk, and which are ready for expansion\u2014so teams can trigger the right retention or growth actions.<\/p>\n\n\n\n

                                      2) How often should a Customer Health Score be updated?<\/h3>\n\n\n\n

                                      It depends on your business cycle. Many teams refresh daily or weekly, but event-driven updates (like payment failures or usage drops) are ideal for fast-moving Direct & Retention Marketing<\/strong> programs.<\/p>\n\n\n\n

                                      3) What data is most important for Customer Health Score?<\/h3>\n\n\n\n

                                      High-signal inputs typically include usage\/adoption, recent purchases or renewal indicators, support friction, and engagement. The \u201cright\u201d data is what most strongly correlates with retention for your segments.<\/p>\n\n\n\n

                                      4) How does Customer Health Score help CRM Marketing specifically?<\/h3>\n\n\n\n

                                      In CRM Marketing<\/strong>, the score becomes a consistent segmentation attribute that can trigger journeys, control message cadence, personalize content, and route accounts for human follow-up.<\/p>\n\n\n\n

                                      5) Should we use a rules-based or predictive approach?<\/h3>\n\n\n\n

                                      Start rules-based if you need speed, clarity, and easy governance. Move to predictive methods when you have enough clean historical data and the ability to monitor model drift and explain drivers.<\/p>\n\n\n\n

                                      6) What are common mistakes when implementing Customer Health Score?<\/h3>\n\n\n\n

                                      Common mistakes include using too many low-signal metrics, applying one formula to every segment, failing to validate against churn\/retention outcomes, and triggering incentives that reduce revenue unnecessarily.<\/p>\n\n\n\n

                                      7) Can Customer Health Score work for non-subscription businesses?<\/h3>\n\n\n\n

                                      Yes. For ecommerce or services, health can reflect repeat purchase likelihood, replenishment timing, engagement, satisfaction, and service delivery milestones\u2014still highly actionable for Direct & Retention Marketing<\/strong> and CRM Marketing<\/strong>.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                      Customer relationships don\u2019t fail all at once\u2014they weaken through small signals: lower usage, slower renewals, fewer purchases, more support friction, and reduced engagement with lifecycle messaging. A **Customer Health Score** is a structured way to quantify those signals into a single, actionable view of how \u201chealthy\u201d a customer relationship is right now.<\/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":[1893],"tags":[],"class_list":["post-7701","post","type-post","status-publish","format-standard","hentry","category-crm-marketing"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7701","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=7701"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7701\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=7701"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=7701"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=7701"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}