{"id":8189,"date":"2026-03-25T18:08:21","date_gmt":"2026-03-25T18:08:21","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/automation-incrementality\/"},"modified":"2026-03-25T18:08:21","modified_gmt":"2026-03-25T18:08:21","slug":"automation-incrementality","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/automation-incrementality\/","title":{"rendered":"Automation Incrementality: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Marketing Automation"},"content":{"rendered":"\n

Automation is everywhere in lifecycle programs, but not all automated messages create new value. Automation Incrementality<\/strong> is the discipline of measuring the true added impact<\/em> of automated journeys\u2014what changes in revenue, retention, or engagement happen because<\/strong> automation ran, versus what would have happened anyway.<\/p>\n\n\n\n

In Direct & Retention Marketing<\/strong>, this matters because customers often convert or renew due to many influences: brand familiarity, product utility, seasonality, sales outreach, and prior campaigns. Marketing Automation<\/strong> can easily \u201cclaim\u201d conversions it merely captured<\/em> at the finish line. Automation Incrementality helps teams separate credit<\/em> from causality<\/em>, so strategy, budget, and customer experience decisions are grounded in evidence.<\/p>\n\n\n\n

\n\n\n\n

What Is Automation Incrementality?<\/h2>\n\n\n\n

Automation Incrementality<\/strong> is the measurable lift produced by automated marketing actions compared with a valid baseline (a control group, holdout, or modeled counterfactual). Put simply: it answers, \u201cHow many extra conversions, renewals, or actions did automation create that would not have happened without it?\u201d<\/p>\n\n\n\n

The core concept is counterfactual thinking applied to lifecycle programs. If you send an abandoned cart email and the customer buys, the important question is not \u201cDid the email precede the purchase?\u201d but \u201cWould they have purchased anyway?\u201d<\/p>\n\n\n\n

From a business perspective, Automation Incrementality turns automation from a \u201cset-and-forget\u201d production system into an accountable growth lever. In Direct & Retention Marketing<\/strong>, it guides how often to message, whom to target, and which journeys deserve investment. Inside Marketing Automation<\/strong>, it influences segmentation logic, journey design, send-time rules, and experimentation frameworks.<\/p>\n\n\n\n

\n\n\n\n

Why Automation Incrementality Matters in Direct & Retention Marketing<\/h2>\n\n\n\n

In Direct & Retention Marketing<\/strong>, you typically optimize for revenue per user, repeat purchase rate, churn reduction, and customer lifetime value. Without Automation Incrementality, teams risk optimizing the wrong thing: attributed<\/em> performance rather than incremental<\/em> performance.<\/p>\n\n\n\n

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

    \n
  • Sharper prioritization:<\/strong> Incremental lift reveals which automations actually move outcomes versus those that mainly shift timing or channel.<\/li>\n
  • Budget credibility:<\/strong> When finance asks whether automation is \u201cworth it,\u201d incrementality provides defensible proof, not just last-click reporting.<\/li>\n
  • Competitive advantage:<\/strong> Teams that measure lift can reduce noise, cut ineffective touches, and reallocate effort faster than competitors.<\/li>\n
  • Better customer experience:<\/strong> If an automation isn\u2019t incremental, it may be unnecessary friction\u2014more emails, more notifications, more unsubscribes.<\/li>\n<\/ul>\n\n\n\n

    Used well, Automation Incrementality improves both performance and brand trust by aligning Marketing Automation<\/strong> with what customers truly need.<\/p>\n\n\n\n

    \n\n\n\n

    How Automation Incrementality Works<\/h2>\n\n\n\n

    Automation Incrementality is both a measurement approach and an operating habit. In practice, it often follows a lifecycle workflow:<\/p>\n\n\n\n

      \n
    1. \n

      Input \/ trigger<\/strong>\n – A user behavior or state change (signup, cart abandon, inactivity threshold, renewal window).\n – Audience rules and eligibility (new users, high intent, at-risk customers).<\/p>\n<\/li>\n

    2. \n

      Analysis \/ baseline setup<\/strong>\n – Define the outcome (purchase, activation, renewal, reduced churn).\n – Create a comparison baseline: randomized holdout, time-based holdout, geographic split, or a robust model when randomization is not feasible.\n – Confirm the baseline is valid (similar users, similar timing, minimal contamination).<\/p>\n<\/li>\n

    3. \n

      Execution \/ application<\/strong>\n – Run the automated journey in Marketing Automation<\/strong> for the treatment group.\n – Withhold or alter the automation for the control\/holdout group (for example, delay by 48 hours, reduce touches, or use a neutral message).<\/p>\n<\/li>\n

    4. \n

      Output \/ outcome<\/strong>\n – Calculate incremental lift: difference in outcomes between treatment and baseline.\n – Translate lift into business impact: incremental revenue, incremental margin, incremental retention.\n – Feed insights back into journey design and governance in Direct & Retention Marketing<\/strong>.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

      The point is not to \u201ctest everything forever,\u201d but to continuously validate that automation is creating real lift as audiences, products, and channels change.<\/p>\n\n\n\n

      \n\n\n\n

      Key Components of Automation Incrementality<\/h2>\n\n\n\n

      Strong Automation Incrementality programs require more than a single experiment. The major components include:<\/p>\n\n\n\n

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

      You need reliable event tracking (views, add-to-cart, purchase, renewal), customer identifiers across channels, and consistent definitions for states like \u201cactive,\u201d \u201cchurned,\u201d or \u201cat-risk.\u201d In Direct & Retention Marketing<\/strong>, identity resolution is especially important when email, SMS, push, and in-app overlap.<\/p>\n\n\n\n

      Automation systems and controls<\/h3>\n\n\n\n

      Your Marketing Automation<\/strong> platform must support:\n– Segmentation and eligibility rules\n– Suppression lists and message caps\n– Holdouts or random splits (or integrations that enable them)\n– Logging of sends, exposures, and journey steps<\/p>\n\n\n\n

      Measurement design<\/h3>\n\n\n\n

      Automation Incrementality depends on:\n– Clear hypothesis (what you expect to change and why)\n– Appropriate control method (randomized if possible)\n– Defined measurement window (e.g., 7-day purchase rate after trigger)<\/p>\n\n\n\n

      Metrics and business mapping<\/h3>\n\n\n\n

      Incremental outcomes must map to financial reality: margin, refund rates, discount cost, support cost, and long-term retention\u2014especially in Direct & Retention Marketing<\/strong> where short-term conversion can trade off with unsubscribes.<\/p>\n\n\n\n

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

      High-performing teams assign ownership:\n– Marketing owns hypothesis, messaging, and journey logic\n– Analytics owns experimental design and validity checks\n– Data\/engineering owns instrumentation and data quality\n– Leadership sets guardrails (customer experience standards, risk tolerance)<\/p>\n\n\n\n

      \n\n\n\n

      Types of Automation Incrementality<\/h2>\n\n\n\n

      Automation Incrementality doesn\u2019t have one universal taxonomy, but practitioners commonly distinguish it by context and method:<\/p>\n\n\n\n

      1) Channel-level vs journey-level incrementality<\/h3>\n\n\n\n
        \n
      • Channel-level:<\/strong> How much incremental lift does \u201cemail\u201d add compared to no email?<\/li>\n
      • Journey-level:<\/strong> How much incremental lift does the entire sequence<\/em> add (timing, content, multi-touch logic)?<\/li>\n<\/ul>\n\n\n\n

        2) Immediate vs long-term incrementality<\/h3>\n\n\n\n
          \n
        • Immediate lift:<\/strong> Short-window conversion\/activation improvements.<\/li>\n
        • Long-term lift:<\/strong> Retention, repeat purchase, churn reduction, and customer lifetime value. In Direct & Retention Marketing<\/strong>, long-term incrementality is often the real prize.<\/li>\n<\/ul>\n\n\n\n

          3) Randomized holdout vs quasi-experimental incrementality<\/h3>\n\n\n\n
            \n
          • Randomized holdout:<\/strong> Gold standard when feasible.<\/li>\n
          • Quasi-experimental approaches:<\/strong> Matched audiences, regression, difference-in-differences, or time-based holdouts\u2014useful when operational constraints limit randomization, but require extra care.<\/li>\n<\/ul>\n\n\n\n

            4) \u201cWithhold\u201d vs \u201cthrottle\u201d tests<\/h3>\n\n\n\n
              \n
            • Withhold:<\/strong> No automation at all for holdout.<\/li>\n
            • Throttle:<\/strong> Reduced frequency or delayed sends to measure marginal contribution while managing risk.<\/li>\n<\/ul>\n\n\n\n
              \n\n\n\n

              Real-World Examples of Automation Incrementality<\/h2>\n\n\n\n

              Example 1: Abandoned cart automation that \u201csteals credit\u201d<\/h3>\n\n\n\n

              A retailer runs an abandoned cart email series. Standard reporting shows strong revenue attributed to email. An Automation Incrementality holdout reveals many customers would have purchased within 24 hours anyway. The email\u2019s incremental<\/em> lift is modest, but a revised approach\u2014sending only to high-price carts or new customers\u2014restores meaningful incrementality and reduces inbox fatigue. This is classic Direct & Retention Marketing<\/strong> optimization powered by Marketing Automation<\/strong> controls.<\/p>\n\n\n\n

              Example 2: Renewal reminders that reduce churn\u2014unless they\u2019re too early<\/h3>\n\n\n\n

              A subscription company automates renewal reminders 30 days before renewal. A holdout test finds early reminders don\u2019t increase renewals; they increase cancellations by prompting customers to re-evaluate. Shifting reminders to 10 days and adding in-product value messaging produces positive Automation Incrementality on renewals and lowers support tickets.<\/p>\n\n\n\n

              Example 3: Winback journeys where the real lever is suppression, not messaging<\/h3>\n\n\n\n

              A consumer app runs winback push notifications for inactive users. Incrementality testing shows messaging adds little for deeply dormant users but works for \u201crecently inactive\u201d segments. The biggest gain comes from not<\/em> messaging long-dormant users, improving deliverability and reducing opt-outs\u2014an important Direct & Retention Marketing<\/strong> outcome that attributed conversions alone would miss.<\/p>\n\n\n\n

              \n\n\n\n

              Benefits of Using Automation Incrementality<\/h2>\n\n\n\n

              When applied consistently, Automation Incrementality delivers benefits across performance, cost, and experience:<\/p>\n\n\n\n

                \n
              • Higher true ROI:<\/strong> You invest in automations that create net-new outcomes, not just measurable attribution.<\/li>\n
              • Lower wasted spend:<\/strong> Reduced sends, fewer discounts, and less reliance on incentives that would have happened anyway.<\/li>\n
              • Smarter personalization:<\/strong> Incrementality identifies which segments are persuadable versus already intent-driven.<\/li>\n
              • Improved deliverability and engagement:<\/strong> Cutting non-incremental messages often increases open\/click rates and reduces unsubscribes.<\/li>\n
              • Better forecasting:<\/strong> Incremental lift supports more accurate projections for Direct & Retention Marketing<\/strong> roadmaps and Marketing Automation<\/strong> expansion.<\/li>\n<\/ul>\n\n\n\n
                \n\n\n\n

                Challenges of Automation Incrementality<\/h2>\n\n\n\n

                Automation Incrementality is powerful, but it\u2019s not trivial to do well:<\/p>\n\n\n\n

                Measurement and validity risks<\/h3>\n\n\n\n
                  \n
                • Selection bias:<\/strong> If holdouts aren\u2019t truly comparable, lift estimates can be misleading.<\/li>\n
                • Contamination:<\/strong> Control users might still receive similar messages via other channels or campaigns.<\/li>\n
                • Seasonality and timing:<\/strong> Promotions, holidays, and product changes can swamp the signal.<\/li>\n<\/ul>\n\n\n\n

                  Technical and operational barriers<\/h3>\n\n\n\n
                    \n
                  • Tool limitations:<\/strong> Not every Marketing Automation<\/strong> setup supports clean randomization or holdouts.<\/li>\n
                  • Data quality gaps:<\/strong> Missing events, inconsistent identity, or delayed reporting distort outcomes.<\/li>\n
                  • Cross-channel complexity:<\/strong> In Direct & Retention Marketing<\/strong>, email, SMS, push, paid retargeting, and onsite experiences interact.<\/li>\n<\/ul>\n\n\n\n

                    Strategic trade-offs<\/h3>\n\n\n\n
                      \n
                    • Short-term vs long-term:<\/strong> An automation can increase immediate conversions while harming retention through fatigue.<\/li>\n
                    • Risk management:<\/strong> Holding out users may feel uncomfortable; teams need guardrails, smaller tests, and clear thresholds.<\/li>\n<\/ul>\n\n\n\n
                      \n\n\n\n

                      Best Practices for Automation Incrementality<\/h2>\n\n\n\n
                        \n
                      • Start with high-impact journeys:<\/strong> Prioritize onboarding, cart abandon, renewal, and winback before testing minor nudges.<\/li>\n
                      • Prefer randomized holdouts when feasible:<\/strong> Even a small persistent holdout (e.g., 5\u201310%) can yield reliable insight over time.<\/li>\n
                      • Define a single primary outcome per test:<\/strong> Add secondary metrics (unsubscribe, complaint rate, support contacts) to protect experience.<\/li>\n
                      • Use suppression and frequency caps as test levers:<\/strong> Many gains come from reducing<\/em> automation, not adding more.<\/li>\n
                      • Document assumptions and changes:<\/strong> Track eligibility rules, creative changes, and product updates so you can interpret results.<\/li>\n
                      • Re-test periodically:<\/strong> Incrementality decays as audiences learn, competitors respond, and channels change\u2014especially in Direct & Retention Marketing<\/strong> where behavior patterns shift quickly.<\/li>\n
                      • Operationalize learning:<\/strong> Feed lift results back into Marketing Automation<\/strong> templates, segment libraries, and governance standards.<\/li>\n<\/ul>\n\n\n\n
                        \n\n\n\n

                        Tools Used for Automation Incrementality<\/h2>\n\n\n\n

                        Automation Incrementality is enabled by tool categories<\/em> working together:<\/p>\n\n\n\n

                          \n
                        • Marketing Automation platforms:<\/strong> Build journeys, manage segmentation, control suppression, and log exposures across email\/SMS\/push\/in-app.<\/li>\n
                        • CRM and customer data systems:<\/strong> Store customer profiles, lifecycle states, consent, and communication preferences critical to Direct & Retention Marketing<\/strong>.<\/li>\n
                        • Analytics tools (product + web):<\/strong> Measure behavioral outcomes, cohorts, funnels, and retention changes from automated interventions.<\/li>\n
                        • Experimentation and testing frameworks:<\/strong> Support randomization, holdout management, and statistical evaluation of lift.<\/li>\n
                        • Ad platforms and retargeting systems:<\/strong> Helpful when measuring incrementality across paid remarketing versus owned automation.<\/li>\n
                        • Reporting dashboards \/ BI:<\/strong> Centralize definitions and enable stakeholders to monitor incremental lift, not just attributed conversions.<\/li>\n
                        • SEO tools (supporting role):<\/strong> While not core to Automation Incrementality, SEO insights can inform lifecycle content strategy and reduce over-reliance on pushy automation by improving inbound intent quality.<\/li>\n<\/ul>\n\n\n\n
                          \n\n\n\n

                          Metrics Related to Automation Incrementality<\/h2>\n\n\n\n

                          To evaluate Automation Incrementality properly, combine outcome metrics with cost and experience metrics:<\/p>\n\n\n\n

                          Incremental performance metrics<\/h3>\n\n\n\n
                            \n
                          • Incremental conversion rate (treatment minus control)<\/li>\n
                          • Incremental revenue per user (or per eligible user)<\/li>\n
                          • Incremental renewals \/ churn reduction<\/li>\n
                          • Incremental repeat purchase rate<\/li>\n
                          • Incremental activation (time-to-value, feature adoption)<\/li>\n<\/ul>\n\n\n\n

                            Efficiency and ROI metrics<\/h3>\n\n\n\n
                              \n
                            • Incremental ROI (incremental profit \u00f7 automation cost)<\/li>\n
                            • Incremental cost per incremental conversion<\/li>\n
                            • Discount or incentive cost per incremental outcome<\/li>\n<\/ul>\n\n\n\n

                              Experience and quality metrics<\/h3>\n\n\n\n
                                \n
                              • Unsubscribe\/opt-out rate changes (treatment vs control)<\/li>\n
                              • Complaint rates (spam complaints, SMS complaints)<\/li>\n
                              • Engagement quality (repeat engagement, session depth)<\/li>\n
                              • Deliverability indicators (bounce rate, inbox placement proxies)<\/li>\n<\/ul>\n\n\n\n

                                In Direct & Retention Marketing<\/strong>, a \u201cwin\u201d should not be declared without checking the experience metrics that protect long-term value.<\/p>\n\n\n\n

                                \n\n\n\n

                                Future Trends of Automation Incrementality<\/h2>\n\n\n\n

                                Several shifts are pushing Automation Incrementality from \u201cadvanced\u201d to \u201cnecessary\u201d:<\/p>\n\n\n\n

                                  \n
                                • AI-assisted journey optimization:<\/strong> AI can generate variants and predict outcomes, but incrementality measurement will remain essential to verify real lift rather than model optimism.<\/li>\n
                                • More personalization, more risk:<\/strong> Hyper-targeted Marketing Automation<\/strong> increases the chance of over-contacting persuadable users; incrementality helps find the point of diminishing returns.<\/li>\n
                                • Privacy and signal loss:<\/strong> As tracking becomes harder, holdouts and first-party measurement become more valuable in Direct & Retention Marketing<\/strong>.<\/li>\n
                                • Cross-channel orchestration:<\/strong> Incrementality will evolve from single-message tests to system-wide measurement across email, push, in-app, and paid media.<\/li>\n
                                • Continuous experimentation culture:<\/strong> High-performing teams will maintain \u201calways-on\u201d holdouts to monitor whether automation remains incremental as products and markets change.<\/li>\n<\/ul>\n\n\n\n
                                  \n\n\n\n

                                  Automation Incrementality vs Related Terms<\/h2>\n\n\n\n

                                  Automation Incrementality vs Attribution<\/h3>\n\n\n\n

                                  Attribution<\/strong> assigns credit for conversions across touchpoints. Automation Incrementality<\/strong> measures causal impact\u2014what automation caused<\/em> beyond a baseline. Attribution is useful for reporting; incrementality is essential for decision-making.<\/p>\n\n\n\n

                                  Automation Incrementality vs A\/B Testing<\/h3>\n\n\n\n

                                  A\/B testing<\/strong> compares two variants (A vs B). Automation Incrementality often compares \u201cautomation vs no automation\u201d (or reduced automation) to quantify lift. You can use A\/B testing within Marketing Automation<\/strong>, but without a true baseline you may only learn which version is better\u2014not whether either is necessary.<\/p>\n\n\n\n

                                  Automation Incrementality vs Marketing Mix Modeling (MMM)<\/h3>\n\n\n\n

                                  MMM estimates channel contribution at an aggregate level. Automation Incrementality is typically user-level or cohort-level and is especially actionable for Direct & Retention Marketing<\/strong> flows like onboarding and renewal sequences. They complement each other: MMM guides macro allocation; incrementality guides lifecycle execution.<\/p>\n\n\n\n

                                  \n\n\n\n

                                  Who Should Learn Automation Incrementality<\/h2>\n\n\n\n
                                    \n
                                  • Marketers:<\/strong> To prove which lifecycle journeys genuinely improve retention and revenue, and to reduce non-incremental messaging.<\/li>\n
                                  • Analysts and data scientists:<\/strong> To design valid experiments, quantify lift, and translate results into business recommendations.<\/li>\n
                                  • Agencies and consultants:<\/strong> To move beyond surface-level automation builds and deliver measurable value for clients\u2019 Direct & Retention Marketing<\/strong>.<\/li>\n
                                  • Business owners and founders:<\/strong> To understand whether Marketing Automation<\/strong> investments create net-new growth or simply re-label existing demand.<\/li>\n
                                  • Developers and marketing ops:<\/strong> To implement tracking, identity, and holdout mechanics that make incrementality measurable and scalable.<\/li>\n<\/ul>\n\n\n\n
                                    \n\n\n\n

                                    Summary of Automation Incrementality<\/h2>\n\n\n\n

                                    Automation Incrementality<\/strong> measures the true added value created by automated lifecycle messages compared with a baseline. It matters because Direct & Retention Marketing<\/strong> is full of customers who may convert anyway, and standard attribution can overstate automation\u2019s impact. By using holdouts or rigorous comparisons, teams can identify which automations generate real lift, improve customer experience, and allocate effort more effectively. Done well, Automation Incrementality strengthens Marketing Automation<\/strong> by making it accountable, testable, and aligned with long-term retention.<\/p>\n\n\n\n

                                    \n\n\n\n

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

                                    1) What does Automation Incrementality mean in plain language?<\/h3>\n\n\n\n

                                    It means measuring how many extra conversions, renewals, or actions happened because<\/em> an automation ran, compared with what would have happened if it hadn\u2019t.<\/p>\n\n\n\n

                                    2) How do you measure Automation Incrementality without hurting revenue?<\/h3>\n\n\n\n

                                    Use a small holdout (often 5\u201310%), limit tests to lower-risk segments first, and monitor guardrail metrics (unsubscribes, complaints, support contacts). Many teams also use \u201cthrottle\u201d tests instead of full withholds.<\/p>\n\n\n\n

                                    3) Is Automation Incrementality only for email?<\/h3>\n\n\n\n

                                    No. It applies to any Marketing Automation<\/strong> channel\u2014SMS, push, in-app, messaging sequences, and even coordinated automation with paid retargeting\u2014especially in Direct & Retention Marketing<\/strong> where channels overlap.<\/p>\n\n\n\n

                                    4) What\u2019s the difference between incrementality and uplift modeling?<\/h3>\n\n\n\n

                                    Incrementality is the measured lift from a test or baseline comparison. Uplift modeling predicts which users are most likely to be influenced. Uplift models are most reliable when trained and validated against incrementality tests.<\/p>\n\n\n\n

                                    5) Which metric should I use first for Direct & Retention Marketing incrementality?<\/h3>\n\n\n\n

                                    Start with one primary outcome tied to the journey\u2019s purpose: activation rate for onboarding, purchase rate for cart recovery, or renewal rate for subscription retention. Add guardrails like opt-outs and complaint rates.<\/p>\n\n\n\n

                                    6) How often should we re-check incrementality for key automations?<\/h3>\n\n\n\n

                                    Re-check when you change eligibility rules, creative, incentives, or frequency\u2014and periodically (for example, quarterly or biannually) because audience behavior, seasonality, and competition can shift results.<\/p>\n\n\n\n

                                    7) Can Marketing Automation platforms calculate incrementality automatically?<\/h3>\n\n\n\n

                                    Some workflows support holdouts and reporting, but you still need sound experimental design, clean data, and governance. Automation Incrementality is as much a process and discipline as it is a feature.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                    Automation is everywhere in lifecycle programs, but not all automated messages create new value. **Automation Incrementality** is the discipline of measuring the *true added impact* of automated journeys\u2014what changes in revenue, retention, or engagement happen **because** automation ran, versus what would have happened anyway.<\/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":[1894],"tags":[],"class_list":["post-8189","post","type-post","status-publish","format-standard","hentry","category-marketing-automation"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/8189","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=8189"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/8189\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=8189"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=8189"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=8189"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}