{"id":9709,"date":"2026-03-28T07:38:58","date_gmt":"2026-03-28T07:38:58","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/review-spam-policy\/"},"modified":"2026-03-28T07:38:58","modified_gmt":"2026-03-28T07:38:58","slug":"review-spam-policy","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/review-spam-policy\/","title":{"rendered":"Review Spam Policy: What It Is, Key Features, Benefits, Use Cases, and How It Fits in SEO"},"content":{"rendered":"\n

A Review Spam Policy<\/strong> is the set of rules (from platforms and from your own organization) that defines what counts as fake, misleading, incentivized, or otherwise manipulative reviews\u2014and what actions should be taken to prevent, detect, report, remove, and respond to them. In Organic Marketing<\/strong>, reviews influence reputation, click-through rates, conversions, and especially visibility in local and marketplace discovery. In SEO<\/strong>, review integrity affects how search engines and platforms interpret trust signals around a brand, location, or product.<\/p>\n\n\n\n

This matters now more than ever because reviews have become both a growth lever and a target. As competition increases and AI makes content generation easier, review ecosystems are under pressure. A strong Review Spam Policy<\/strong> helps protect legitimate customers, defend brand credibility, and reduce the risk of ranking losses or account actions that can quietly derail Organic Marketing<\/strong> momentum.<\/p>\n\n\n\n

What Is Review Spam Policy?<\/h2>\n\n\n\n

At a beginner level, Review Spam Policy<\/strong> means \u201cthe rules about what reviews are allowed, and what happens when reviews are fake or manipulated.\u201d These rules exist at two layers:<\/p>\n\n\n\n

    \n
  • Platform policies<\/strong>: Guidelines set by review hosts (search engines, local listings, app stores, marketplaces, and industry directories) that define prohibited behavior and enforcement actions.<\/li>\n
  • Business policies<\/strong>: Your internal standards for collecting reviews ethically, monitoring for abuse, escalating suspicious activity, and responding transparently.<\/li>\n<\/ul>\n\n\n\n

    The core concept is simple: reviews should reflect real experiences from real customers without manipulation. Review spam includes fabricated reviews, paid or incentivized reviews without proper disclosure, coordinated attacks, review hijacking, impersonation, and other tactics designed to mislead.<\/p>\n\n\n\n

    From a business perspective, Review Spam Policy<\/strong> is risk management plus performance management. It protects revenue by preserving trust while ensuring your review strategy supports Organic Marketing<\/strong> goals like brand authority, conversion rate improvements, and sustainable customer acquisition.<\/p>\n\n\n\n

    In SEO<\/strong>, review content and ratings influence how users choose results and how platforms assess prominence. For many businesses\u2014especially those with physical locations\u2014review quality and volume can correlate with local visibility, engagement, and lead flow.<\/p>\n\n\n\n

    Why Review Spam Policy Matters in Organic Marketing<\/h2>\n\n\n\n

    A clear Review Spam Policy<\/strong> creates strategic advantage because it defends the credibility of one of the most powerful \u201cearned media\u201d assets in Organic Marketing<\/strong>: authentic social proof. When your reviews are trusted, your brand looks safer, more popular, and more reliable than competitors\u2014even before a user visits your site.<\/p>\n\n\n\n

    Key business outcomes include:<\/p>\n\n\n\n

      \n
    • Higher conversion rates<\/strong>: Users often decide based on rating distribution, recency, and response quality.<\/li>\n
    • Better customer intelligence<\/strong>: Genuine reviews reveal product gaps, service issues, and messaging opportunities.<\/li>\n
    • Reduced reputation volatility<\/strong>: Spam attacks and fake review bursts can cause sudden drops in rating and trust if unmanaged.<\/li>\n
    • Stronger <\/strong>SEO outcomes<\/strong>: Trust signals influence click behavior and can affect local and platform visibility.<\/li>\n<\/ul>\n\n\n\n

      Importantly, Review Spam Policy<\/strong> isn\u2019t only about blocking bad actors. It also prevents well-meaning teams or agencies from using risky \u201cgrowth hacks\u201d that violate guidelines and lead to removals, listing suspensions, or credibility loss.<\/p>\n\n\n\n

      How Review Spam Policy Works<\/h2>\n\n\n\n

      A Review Spam Policy<\/strong> is partly rules and partly operational workflow. In practice, it works like a governance loop:<\/p>\n\n\n\n

        \n
      1. \n

        Input or trigger<\/strong>\n – New reviews appear on platforms (local listings, marketplaces, industry sites).\n – Anomalies are detected (sudden spikes, repeated phrases, suspicious user profiles).\n – Customer support flags suspicious tickets (\u201cI was asked to leave a 5-star review for a discount\u201d).<\/p>\n<\/li>\n

      2. \n

        Analysis or processing<\/strong>\n – Validate authenticity signals: purchase verification (where applicable), reviewer history, language patterns, timing, geographic consistency, and sentiment outliers.\n – Classify the issue: fake positive, fake negative, competitor attack, review gating, incentivized review, or policy violation by internal teams.<\/p>\n<\/li>\n

      3. \n

        Execution or application<\/strong>\n – Take action based on policy: respond publicly, request removal through platform processes, escalate internally, or remediate the customer issue.\n – Update internal controls: adjust review requests, training, and automation rules.<\/p>\n<\/li>\n

      4. \n

        Output or outcome<\/strong>\n – Cleaner review profile, reduced spam exposure, improved customer trust, and more reliable measurement.\n – Reduced risk of platform penalties and more stable Organic Marketing<\/strong> performance and SEO<\/strong> signals.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

        The goal isn\u2019t perfection; it\u2019s consistency, defensibility, and continuous improvement.<\/p>\n\n\n\n

        Key Components of Review Spam Policy<\/h2>\n\n\n\n

        A strong Review Spam Policy<\/strong> typically includes the following elements:<\/p>\n\n\n\n

        Policy definitions and prohibited practices<\/h3>\n\n\n\n

        Clear definitions of what the organization considers spam, including:\n– Fake reviews (self-authored or purchased)\n– Incentivized reviews without proper disclosure\n– Review gating (only asking happy customers and filtering unhappy ones)\n– Staff, friends, or vendors posing as customers\n– Coordinated harassment or competitor-driven review bombing<\/p>\n\n\n\n

        Processes and escalation paths<\/h3>\n\n\n\n
          \n
        • Who monitors reviews daily\/weekly<\/li>\n
        • When to respond publicly vs. escalate privately<\/li>\n
        • When to request takedown\/removal and who owns that request<\/li>\n
        • Legal or compliance involvement for defamation, impersonation, or harassment<\/li>\n<\/ul>\n\n\n\n

          Data inputs and monitoring signals<\/h3>\n\n\n\n
            \n
          • Review velocity (sudden bursts)<\/li>\n
          • Rating distribution shifts<\/li>\n
          • Duplicate language patterns<\/li>\n
          • Reviewer account quality indicators<\/li>\n
          • Location, device, or timestamp anomalies (where available)<\/li>\n<\/ul>\n\n\n\n

            Governance and responsibilities<\/h3>\n\n\n\n
              \n
            • Marketing owns review acquisition ethics and messaging<\/li>\n
            • Support owns service recovery and issue resolution<\/li>\n
            • Operations owns staff training and on-site practices<\/li>\n
            • Leadership sets risk tolerance and approves escalation thresholds<\/li>\n<\/ul>\n\n\n\n

              Documentation and audit readiness<\/h3>\n\n\n\n

              A practical Review Spam Policy<\/strong> includes logs of:\n– Suspected spam incidents\n– Actions taken and outcomes\n– Screenshots and timestamps (useful when platforms remove evidence later)<\/p>\n\n\n\n

              This structure helps teams execute Organic Marketing<\/strong> consistently and keeps SEO<\/strong> efforts aligned with platform rules.<\/p>\n\n\n\n

              Types of Review Spam Policy<\/h2>\n\n\n\n

              \u201cTypes\u201d of Review Spam Policy<\/strong> are less about formal categories and more about context. The most useful distinctions are:<\/p>\n\n\n\n

              Platform-level vs. business-level policies<\/h3>\n\n\n\n
                \n
              • Platform-level<\/strong> policies define what is allowed on that platform and what enforcement looks like.<\/li>\n
              • Business-level<\/strong> policies define how your organization behaves and how it responds to violations.<\/li>\n<\/ul>\n\n\n\n

                Proactive vs. reactive policy focus<\/h3>\n\n\n\n
                  \n
                • Proactive<\/strong>: training, ethical review request flows, fraud-prevention controls, and monitoring.<\/li>\n
                • Reactive<\/strong>: incident response playbooks for spam attacks, takedown requests, and public replies.<\/li>\n<\/ul>\n\n\n\n

                  Local reviews vs. product\/service reviews<\/h3>\n\n\n\n
                    \n
                  • Local<\/strong> reviews emphasize location authenticity, service experience, and local relevance\u2014highly tied to local SEO<\/strong>.<\/li>\n
                  • Product<\/strong> reviews emphasize purchase verification, SKU-level quality, and marketplace compliance.<\/li>\n<\/ul>\n\n\n\n

                    Real-World Examples of Review Spam Policy<\/h2>\n\n\n\n

                    Example 1: Local service business faces a competitor spam attack<\/h3>\n\n\n\n

                    A home services company sees a sudden wave of 1-star reviews with vague complaints and no matching customer records. Their Review Spam Policy<\/strong> triggers an incident workflow: support checks CRM records, marketing documents patterns (timing, repeated phrases), and the team requests removal for policy violations while posting calm, factual replies to protect conversion rate. The outcome: reduced reputational damage, better customer confidence, and steadier local SEO<\/strong> visibility in maps and local results.<\/p>\n\n\n\n

                    Example 2: Ecommerce brand avoids incentivized review violations<\/h3>\n\n\n\n

                    A retail team wants to offer a discount \u201cfor a 5-star review.\u201d The internal Review Spam Policy<\/strong> blocks this and replaces it with a compliant approach: requesting honest feedback from all purchasers, not conditioning incentives on sentiment, and focusing on service recovery for unhappy customers. This protects Organic Marketing<\/strong> credibility and prevents mass review removals that would have weakened conversion performance and SEO<\/strong> click behavior.<\/p>\n\n\n\n

                    Example 3: SaaS company cleans up review acquisition practices<\/h3>\n\n\n\n

                    A SaaS company discovers an agency was asking employees and partners to submit reviews as \u201ccustomers.\u201d The Review Spam Policy<\/strong> requires disclosure and authenticity standards, so the company stops the practice, removes questionable reviews where possible, and implements verified outreach to real users post-onboarding. Over time, review quality improves, and sales sees fewer trust objections\u2014supporting long-term Organic Marketing<\/strong> growth.<\/p>\n\n\n\n

                    Benefits of Using Review Spam Policy<\/h2>\n\n\n\n

                    A well-run Review Spam Policy<\/strong> drives measurable improvements:<\/p>\n\n\n\n

                      \n
                    • Stronger trust and brand equity<\/strong>: Users can sense unnatural review patterns; authenticity wins.<\/li>\n
                    • More stable performance<\/strong>: Less exposure to rating shocks caused by spam bursts.<\/li>\n
                    • Higher conversion efficiency<\/strong>: Better review quality often improves lead-to-sale rates without additional spend.<\/li>\n
                    • Lower remediation costs<\/strong>: Preventing violations is cheaper than recovering from listing suspensions or mass removals.<\/li>\n
                    • Better team alignment<\/strong>: Marketing, support, and operations follow the same ethical standards, strengthening Organic Marketing<\/strong> execution.<\/li>\n
                    • Reduced <\/strong>SEO risk<\/strong>: Cleaner review ecosystems reduce the likelihood of platform penalties that can indirectly harm visibility.<\/li>\n<\/ul>\n\n\n\n

                      Challenges of Review Spam Policy<\/h2>\n\n\n\n

                      Even with a strong Review Spam Policy<\/strong>, real constraints exist:<\/p>\n\n\n\n

                        \n
                      • Limited platform transparency<\/strong>: You may not get detailed evidence for why a review remains or is removed.<\/li>\n
                      • False positives and negatives<\/strong>: Genuine reviews can look suspicious; sophisticated spam can look real.<\/li>\n
                      • Attribution difficulty<\/strong>: Proving a competitor attack can be hard without clear signals.<\/li>\n
                      • Operational burden<\/strong>: Monitoring multiple platforms and locations requires consistent staffing and process design.<\/li>\n
                      • Global and multi-language complexity<\/strong>: Spam patterns vary by region and language, complicating detection.<\/li>\n
                      • Measurement limitations<\/strong>: It\u2019s hard to quantify the exact SEO<\/strong> impact of spam removal versus other ranking factors.<\/li>\n<\/ul>\n\n\n\n

                        The goal is to reduce risk and improve decision-making, not to achieve perfect enforcement.<\/p>\n\n\n\n

                        Best Practices for Review Spam Policy<\/h2>\n\n\n\n

                        To operationalize Review Spam Policy<\/strong> effectively:<\/p>\n\n\n\n

                          \n
                        • Write clear internal standards<\/strong>: Define prohibited actions (including \u201cwell-intentioned\u201d shortcuts) and train staff and agencies.<\/li>\n
                        • Request reviews ethically and consistently<\/strong>: Ask all customers, not just happy ones; avoid conditioning requests on rating.<\/li>\n
                        • Centralize monitoring<\/strong>: Use a single workflow for triage, tagging, escalation, and resolution across platforms.<\/li>\n
                        • Respond strategically<\/strong>: Public replies should be calm, specific, and privacy-aware; don\u2019t accuse reviewers without evidence.<\/li>\n
                        • Document incidents<\/strong>: Keep internal records of suspicious patterns and actions taken; it improves consistency over time.<\/li>\n
                        • Review quarterly<\/strong>: Update the Review Spam Policy<\/strong> as platforms change enforcement and as your Organic Marketing<\/strong> channels evolve.<\/li>\n
                        • Coordinate with support<\/strong>: Service recovery is often the best \u201canti-spam\u201d strategy\u2014real customers update reviews when issues are resolved.<\/li>\n
                        • Protect structured data integrity<\/strong>: Ensure review markup on your site reflects real, first-party reviews and aligns with guidelines; misleading markup can harm SEO<\/strong> trust.<\/li>\n<\/ul>\n\n\n\n

                          Tools Used for Review Spam Policy<\/h2>\n\n\n\n

                          Review Spam Policy<\/strong> is executed through systems rather than a single tool. Common tool categories in Organic Marketing<\/strong> and SEO<\/strong> workflows include:<\/p>\n\n\n\n

                            \n
                          • Review monitoring and inbox tools<\/strong>: Aggregate reviews across platforms, assign owners, tag incidents, and track response SLAs.<\/li>\n
                          • Customer support\/ticketing systems<\/strong>: Connect reviews to customer records and document resolution steps.<\/li>\n
                          • CRM systems<\/strong>: Validate whether a reviewer is a known lead\/customer and segment outreach for review requests.<\/li>\n
                          • Analytics tools<\/strong>: Measure conversion rate changes, branded search trends, and landing page performance tied to reputation shifts.<\/li>\n
                          • SEO tools and local listing management systems<\/strong>: Track local visibility, citations, and listing health; monitor fluctuations that may coincide with review events.<\/li>\n
                          • Reporting dashboards<\/strong>: Combine review metrics, response times, and business KPIs for leadership visibility.<\/li>\n
                          • Fraud detection \/ anomaly detection workflows<\/strong>: Rules-based alerts (spikes, duplicate text) and, where appropriate, machine-learning assisted flagging.<\/li>\n<\/ul>\n\n\n\n

                            Tooling doesn\u2019t replace policy; it makes the policy enforceable at scale.<\/p>\n\n\n\n

                            Metrics Related to Review Spam Policy<\/h2>\n\n\n\n

                            To measure whether your Review Spam Policy<\/strong> supports Organic Marketing<\/strong> and SEO<\/strong>, track a balanced scorecard:<\/p>\n\n\n\n

                              \n
                            • Review volume and velocity<\/strong>: New reviews per week\/month; spikes can indicate campaigns or spam.<\/li>\n
                            • Rating distribution<\/strong>: Not just average rating\u2014watch shifts in 1-star and 5-star proportions.<\/li>\n
                            • Recency<\/strong>: Fresh reviews often influence user trust and engagement.<\/li>\n
                            • Response rate and response time<\/strong>: Percentage responded and median time to first response.<\/li>\n
                            • Removal success rate<\/strong>: Percentage of reported spam reviews removed (track by platform and reason).<\/li>\n
                            • Sentiment themes<\/strong>: Common positives\/negatives to guide messaging and product improvements.<\/li>\n
                            • Conversion indicators<\/strong>: Calls, form fills, bookings, add-to-cart rate, or demo requests after reputation changes.<\/li>\n
                            • Visibility indicators<\/strong>: Local pack presence, impressions, and branded search interest (useful SEO<\/strong> proxies even when direct causality is hard).<\/li>\n<\/ul>\n\n\n\n

                              Good measurement avoids vanity metrics and focuses on outcomes tied to trust and revenue.<\/p>\n\n\n\n

                              Future Trends of Review Spam Policy<\/h2>\n\n\n\n

                              Review Spam Policy<\/strong> is evolving quickly across Organic Marketing<\/strong> ecosystems:<\/p>\n\n\n\n

                                \n
                              • AI-generated spam at scale<\/strong>: Synthetic reviews will become more fluent and harder to spot, increasing the need for anomaly detection and identity verification.<\/li>\n
                              • Stronger identity and proof signals<\/strong>: More platforms will emphasize verified purchase\/service indicators and account reputation.<\/li>\n
                              • Policy enforcement automation<\/strong>: Platforms will increasingly auto-filter and auto-remove suspected spam, which can also create false positives brands must appeal.<\/li>\n
                              • Richer review formats<\/strong>: Video, images, and long-form experiences can improve authenticity but also introduce new manipulation vectors.<\/li>\n
                              • Privacy and data minimization<\/strong>: Teams will need to investigate incidents with less user data available, relying more on patterns than personal identifiers.<\/li>\n
                              • Integration into <\/strong>SEO and brand strategy<\/strong>: Reviews will remain a critical trust layer that shapes click behavior, local visibility, and on-site conversion\u2014keeping Review Spam Policy<\/strong> central to modern Organic Marketing<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                                Review Spam Policy vs Related Terms<\/h2>\n\n\n\n

                                Review Spam Policy vs reputation management<\/h3>\n\n\n\n

                                Reputation management is broader: it includes brand perception, messaging, PR, and customer experience. Review Spam Policy<\/strong> is narrower and rule-focused, defining what\u2019s acceptable and how to handle fake or manipulated reviews. Reputation management may use reviews as one input; Review Spam Policy<\/strong> governs review integrity.<\/p>\n\n\n\n

                                Review Spam Policy vs review gating<\/h3>\n\n\n\n

                                Review gating is the practice of steering only satisfied customers to leave public reviews while filtering out unhappy customers. Many platforms discourage or prohibit it because it distorts reality. A strong Review Spam Policy<\/strong> explicitly forbids gating and replaces it with ethical, consistent requests that support long-term Organic Marketing<\/strong> credibility.<\/p>\n\n\n\n

                                Review Spam Policy vs content moderation policy<\/h3>\n\n\n\n

                                A content moderation policy governs many forms of user-generated content (comments, profiles, images, community posts). Review Spam Policy<\/strong> focuses specifically on reviews: authenticity, incentives, conflicts of interest, and manipulative behavior. In SEO<\/strong> contexts, the review-specific nuance matters because reviews influence trust and conversion at the point of decision.<\/p>\n\n\n\n

                                Who Should Learn Review Spam Policy<\/h2>\n\n\n\n
                                  \n
                                • Marketers<\/strong> need Review Spam Policy<\/strong> knowledge to run ethical review acquisition, protect brand trust, and support Organic Marketing<\/strong> performance.<\/li>\n
                                • Analysts<\/strong> benefit by distinguishing real reputation shifts from spam noise and building reliable measurement for SEO<\/strong> and conversion reporting.<\/li>\n
                                • Agencies<\/strong> must align client strategies with platform rules to avoid penalties and to deliver sustainable growth.<\/li>\n
                                • Business owners and founders<\/strong> should understand Review Spam Policy<\/strong> to manage risk, protect listings, and avoid shortcuts that can harm long-term revenue.<\/li>\n
                                • Developers<\/strong> play a role when implementing review collection flows, on-site review displays, structured data, and fraud prevention signals that support compliant SEO<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                                  Summary of Review Spam Policy<\/h2>\n\n\n\n

                                  A Review Spam Policy<\/strong> defines what review manipulation looks like and how to prevent, detect, and respond to it across platforms and internal teams. It matters because authentic reviews are a foundational trust signal in Organic Marketing<\/strong>, shaping click behavior, conversions, and customer perception. When implemented well, Review Spam Policy<\/strong> supports stable SEO<\/strong> outcomes, reduces platform risk, and creates a defensible, scalable approach to reputation growth.<\/p>\n\n\n\n

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

                                  1) What does \u201cReview Spam Policy\u201d mean in practice?<\/h3>\n\n\n\n

                                  It means having clear rules and workflows for preventing fake or manipulated reviews, monitoring for suspicious activity, documenting incidents, and taking consistent actions like responding, escalating, or requesting removal when reviews violate platform guidelines.<\/p>\n\n\n\n

                                  2) Can fake reviews hurt SEO?<\/h3>\n\n\n\n

                                  Yes. While reviews aren\u2019t the only factor, spam can reduce trust, lower click-through rates, and trigger platform enforcement actions (like listing suppression) that negatively affect local visibility and broader SEO<\/strong> performance.<\/p>\n\n\n\n

                                  3) Are incentivized reviews always prohibited?<\/h3>\n\n\n\n

                                  Not always, but they are high-risk. Many platforms restrict incentives or require clear disclosure and prohibit conditioning incentives on positive sentiment. Your Review Spam Policy<\/strong> should set strict internal rules so campaigns don\u2019t cross compliance lines.<\/p>\n\n\n\n

                                  4) How do I respond to a review I believe is spam?<\/h3>\n\n\n\n

                                  Avoid accusations. Reply calmly, state you can\u2019t find a matching record (if true), invite the reviewer to contact support, and document evidence internally. If it violates guidelines, follow the platform\u2019s reporting process as part of your Review Spam Policy<\/strong> workflow.<\/p>\n\n\n\n

                                  5) What\u2019s the difference between negative reviews and spam?<\/h3>\n\n\n\n

                                  Negative reviews can be legitimate customer feedback; spam involves deception, impersonation, or manipulation (fake accounts, coordinated attacks, paid posts). A good Review Spam Policy<\/strong> teaches teams to separate service recovery from enforcement actions.<\/p>\n\n\n\n

                                  6) How often should we audit our Review Spam Policy?<\/h3>\n\n\n\n

                                  At least quarterly, and whenever you expand to new platforms, new locations, or new review acquisition methods. Policy reviews should also follow any major platform enforcement changes that could impact Organic Marketing<\/strong> operations.<\/p>\n\n\n\n

                                  7) What\u2019s the safest way to grow reviews ethically?<\/h3>\n\n\n\n

                                  Ask all customers consistently, make it easy to leave honest feedback, fix issues quickly, and train staff to avoid incentives tied to ratings. This approach supports long-term trust, stronger Organic Marketing<\/strong>, and more resilient SEO<\/strong> results.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                  A **Review Spam Policy** is the set of rules (from platforms and from your own organization) that defines what counts as fake, misleading, incentivized, or otherwise manipulative reviews\u2014and what actions should be taken to prevent, detect, report, remove, and respond to them. In **Organic Marketing**, reviews influence reputation, click-through rates, conversions, and especially visibility in local and marketplace discovery. In **SEO**, review integrity affects how search engines and platforms interpret trust signals around a brand, location, or product.<\/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":[131],"tags":[],"class_list":["post-9709","post","type-post","status-publish","format-standard","hentry","category-seo"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/9709","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=9709"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/9709\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=9709"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=9709"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=9709"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}