{"id":9801,"date":"2026-03-28T10:55:20","date_gmt":"2026-03-28T10:55:20","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/organic-search-analysis\/"},"modified":"2026-03-28T10:55:20","modified_gmt":"2026-03-28T10:55:20","slug":"organic-search-analysis","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/organic-search-analysis\/","title":{"rendered":"Organic Search Analysis: What It Is, Key Features, Benefits, Use Cases, and How It Fits in SEO"},"content":{"rendered":"\n

Organic Search Analysis is the practice of examining how people discover your site through unpaid search results, what they do after they land, and which optimizations will most reliably improve outcomes. In Organic Marketing<\/strong>, it\u2019s the measurement layer that turns \u201cwe publish content\u201d into \u201cwe know which topics, pages, and intents drive qualified demand.\u201d Within SEO<\/strong>, it\u2019s how you validate technical fixes, content strategy, and authority-building efforts using evidence instead of assumptions.<\/p>\n\n\n\n

Modern search is noisy: results pages change often, intent shifts quickly, and attribution is imperfect. Organic Search Analysis<\/strong> matters because it helps you separate signal from noise\u2014identifying what\u2019s truly working, what\u2019s stagnating, and what\u2019s costing you growth\u2014so your Organic Marketing strategy stays efficient and defensible.<\/p>\n\n\n\n

What Is Organic Search Analysis?<\/h2>\n\n\n\n

At a beginner level, Organic Search Analysis<\/strong> means collecting and interpreting data about organic search visibility and performance\u2014queries, impressions, clicks, rankings, landing pages, and on-site behavior\u2014so you can make better decisions.<\/p>\n\n\n\n

At its core, it answers questions like:<\/p>\n\n\n\n

    \n
  • Which searches are we showing up for, and how often?<\/li>\n
  • Which pages earn clicks, and why?<\/li>\n
  • Are we attracting the right audience and intent?<\/li>\n
  • What changes will most likely improve Organic Marketing outcomes?<\/li>\n<\/ul>\n\n\n\n

    From a business perspective, Organic Search Analysis<\/strong> ties SEO<\/strong> activity to measurable results such as leads, sales, sign-ups, retention, or reduced support costs. It fits into Organic Marketing<\/strong> as a continuous feedback loop: research \u2192 publish\/optimize \u2192 measure \u2192 iterate.<\/p>\n\n\n\n

    Within SEO<\/strong>, it sits across technical, content, and off-page work. Technical fixes should increase crawlability and indexation; content improvements should raise relevance and conversions; authority-building should improve competitiveness on valuable queries. Organic Search Analysis<\/strong> is how you confirm those effects.<\/p>\n\n\n\n

    Why Organic Search Analysis Matters in Organic Marketing<\/h2>\n\n\n\n

    Strong Organic Marketing is not just about traffic volume; it\u2019s about attracting the right demand and converting it efficiently. Organic Search Analysis<\/strong> delivers strategic value in several ways:<\/p>\n\n\n\n

      \n
    • Prioritization with impact<\/strong>: It highlights the pages and queries where small changes (titles, internal links, content depth, structured formatting) can produce outsized gains.<\/li>\n
    • Quality over vanity metrics<\/strong>: It helps you distinguish \u201ctraffic\u201d from \u201cqualified traffic,\u201d connecting organic visits to engagement and revenue.<\/li>\n
    • Competitive advantage<\/strong>: By analyzing gaps\u2014topics you don\u2019t cover, intents you under-serve, SERP features you\u2019re missing\u2014you can outmaneuver competitors with smarter focus.<\/li>\n
    • Risk reduction<\/strong>: Regular analysis makes performance drops diagnosable, so you can respond to technical issues, content decay, or algorithm shifts faster.<\/li>\n<\/ul>\n\n\n\n

      In short, Organic Search Analysis<\/strong> turns SEO<\/strong> into an accountable discipline inside Organic Marketing\u2014one that can be planned, measured, and improved.<\/p>\n\n\n\n

      How Organic Search Analysis Works<\/h2>\n\n\n\n

      In practice, Organic Search Analysis<\/strong> is a workflow that turns search data into actions and actions into outcomes:<\/p>\n\n\n\n

        \n
      1. \n

        Input \/ trigger (data collection)<\/strong>\n – Search performance data (queries, impressions, clicks, average positions)\n – Site analytics data (sessions, engagement, conversions)\n – Technical signals (crawl errors, index coverage, site speed)\n – Content inventory (topics, templates, update history)\n – Business context (pipeline targets, seasonal demand, product priorities)<\/p>\n<\/li>\n

      2. \n

        Analysis \/ processing (diagnosis and insight)<\/strong>\n – Segment by page type, intent, device, geography, and brand vs non-brand\n – Identify opportunities (high impressions\/low CTR, ranking 8\u201320, thin content)\n – Diagnose issues (indexation gaps, cannibalization, mismatched intent)\n – Map performance to funnel stages and conversion paths<\/p>\n<\/li>\n

      3. \n

        Execution \/ application (optimization)<\/strong>\n – Update content for intent match and completeness\n – Improve snippets (titles\/meta descriptions) for higher CTR\n – Strengthen internal linking and information architecture\n – Fix technical problems impacting crawling, rendering, or duplication\n – Create new content to close topic and query gaps<\/p>\n<\/li>\n

      4. \n

        Output \/ outcome (measurement and iteration)<\/strong>\n – Track changes in visibility, traffic quality, and conversions\n – Validate improvements with before\/after comparisons\n – Feed learning back into your Organic Marketing roadmap and SEO<\/strong> backlog<\/p>\n<\/li>\n<\/ol>\n\n\n\n

        The key is consistency: Organic Search Analysis<\/strong> is not a one-time report; it\u2019s an operating rhythm.<\/p>\n\n\n\n

        Key Components of Organic Search Analysis<\/h2>\n\n\n\n

        Effective Organic Search Analysis<\/strong> combines data, process, and accountability:<\/p>\n\n\n\n

        Data inputs<\/h3>\n\n\n\n
          \n
        • Search query and landing-page performance data<\/li>\n
        • Site analytics and conversion tracking<\/li>\n
        • Crawl\/indexation and site health diagnostics<\/li>\n
        • Content metadata (publish date, author, category, template)<\/li>\n
        • SERP context (intent shifts, snippet formats, competitors)<\/li>\n<\/ul>\n\n\n\n

          Processes<\/h3>\n\n\n\n
            \n
          • Regular reporting cadence (weekly checks, monthly deep dives, quarterly planning)<\/li>\n
          • Segmentation frameworks (brand\/non-brand, intent categories, product lines)<\/li>\n
          • Experimentation (controlled updates, annotation of changes, impact validation)<\/li>\n
          • Documentation (what changed, why, when, and what happened)<\/li>\n<\/ul>\n\n\n\n

            Metrics and interpretation<\/h3>\n\n\n\n
              \n
            • Visibility metrics (impressions, positions, share of relevant queries)<\/li>\n
            • Engagement and outcome metrics (conversion rate, assisted conversions, revenue)<\/li>\n
            • Efficiency metrics (time-to-rank, cost per lead equivalent, content ROI)<\/li>\n<\/ul>\n\n\n\n

              Governance and responsibilities<\/h3>\n\n\n\n
                \n
              • Clear owners for technical SEO<\/strong>, content optimization, and analytics instrumentation<\/li>\n
              • A definition of \u201csuccess\u201d aligned to Organic Marketing goals (not just rankings)<\/li>\n
              • Change management (especially for large sites): approvals, QA, release notes<\/li>\n<\/ul>\n\n\n\n

                Types of Organic Search Analysis<\/h2>\n\n\n\n

                There aren\u2019t universally \u201cofficial\u201d types, but in real SEO<\/strong> work, Organic Search Analysis<\/strong> usually falls into distinct approaches:<\/p>\n\n\n\n

                  \n
                1. \n

                  Query-level analysis<\/strong>\n Focuses on the searches people use, intent patterns, and how your listings perform (CTR, position, SERP feature exposure).<\/p>\n<\/li>\n

                2. \n

                  Landing-page analysis<\/strong>\n Evaluates which pages attract organic traffic, how well they satisfy intent, and how they convert (or fail to).<\/p>\n<\/li>\n

                3. \n

                  Technical performance analysis<\/strong>\n Concentrates on crawlability, indexation, rendering, site speed, duplication, and architecture issues that constrain Organic Marketing growth.<\/p>\n<\/li>\n

                4. \n

                  Content gap and decay analysis<\/strong>\n Identifies topics you\u2019re missing, subtopics competitors cover better, and older pages losing relevance over time.<\/p>\n<\/li>\n

                5. \n

                  Conversion and funnel analysis for organic traffic<\/strong>\n Connects SEO<\/strong> sessions to micro-conversions and revenue outcomes, accounting for multi-touch journeys where possible.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                  Real-World Examples of Organic Search Analysis<\/h2>\n\n\n\n

                  Example 1: Improving CTR on high-impression pages<\/h3>\n\n\n\n

                  A SaaS company notices several product and comparison pages have high impressions but low clicks. Organic Search Analysis<\/strong> reveals titles are generic and don\u2019t match dominant intent (users want \u201cpricing,\u201d \u201calternatives,\u201d and \u201cuse cases\u201d). They rewrite titles and descriptions, add concise on-page answers, and improve internal linking from related guides. Result: higher CTR and more qualified Organic Marketing traffic without publishing new pages.<\/p>\n\n\n\n

                  Example 2: Fixing cannibalization in a content hub<\/h3>\n\n\n\n

                  A publisher has three articles competing for the same query theme. Rankings fluctuate, and none reach top positions. Organic Search Analysis<\/strong> shows overlapping intent and similar headings. The team consolidates into one definitive page, 301s or repurposes the others, and reworks internal links. Result: stronger topical authority and more stable SEO<\/strong> performance.<\/p>\n\n\n\n

                  Example 3: Diagnosing a traffic drop after a site release<\/h3>\n\n\n\n

                  After a redesign, organic sessions fall. Organic Search Analysis<\/strong> finds blocked resources, missing canonical tags, and broken internal links on key templates. Technical fixes restore crawl paths and indexation signals. Result: recovery of visibility and protected pipeline contribution from Organic Marketing.<\/p>\n\n\n\n

                  Benefits of Using Organic Search Analysis<\/h2>\n\n\n\n

                  When done well, Organic Search Analysis<\/strong> delivers practical gains:<\/p>\n\n\n\n

                    \n
                  • Performance improvements<\/strong>: Better rankings, higher CTR, improved engagement, and stronger conversion rates from organic traffic.<\/li>\n
                  • Cost savings<\/strong>: Reduced reliance on paid acquisition by growing durable, compounding demand through SEO<\/strong>.<\/li>\n
                  • Efficiency gains<\/strong>: Clearer prioritization prevents wasted work (e.g., publishing content that targets the wrong intent).<\/li>\n
                  • Better audience experience<\/strong>: Content and pages align with user needs, reducing pogo-sticking and increasing trust.<\/li>\n
                  • Stronger decision-making<\/strong>: Organic Marketing planning becomes evidence-based\u2014what to build, what to update, what to retire.<\/li>\n<\/ul>\n\n\n\n

                    Challenges of Organic Search Analysis<\/h2>\n\n\n\n

                    Even experienced teams hit limitations:<\/p>\n\n\n\n

                      \n
                    • Attribution complexity<\/strong>: Organic search often assists conversions that happen later via other channels; last-click reporting can undercount Organic Marketing impact.<\/li>\n
                    • Data sampling and privacy constraints<\/strong>: Some analytics data is aggregated, thresholded, or modeled, which reduces granularity.<\/li>\n
                    • SERP volatility<\/strong>: Rankings and CTR can change due to layout shifts, new SERP features, or competitor actions\u2014without any change on your site.<\/li>\n
                    • Measurement drift<\/strong>: Tracking changes, consent modes, and tagging inconsistencies can break trend lines if governance is weak.<\/li>\n
                    • \u201cActionability gap\u201d<\/strong>: Reports that don\u2019t translate into prioritized tasks fail to improve SEO<\/strong> outcomes.<\/li>\n<\/ul>\n\n\n\n

                      Acknowledging these constraints is part of doing Organic Search Analysis<\/strong> responsibly.<\/p>\n\n\n\n

                      Best Practices for Organic Search Analysis<\/h2>\n\n\n\n

                      To keep analysis useful and scalable:<\/p>\n\n\n\n

                        \n
                      • Start with business questions, not dashboards<\/strong>: Define what success means (pipeline, sales, trials, bookings) and map organic metrics to it.<\/li>\n
                      • Segment relentlessly<\/strong>: Separate brand vs non-brand, new vs returning, mobile vs desktop, and intent categories (informational, navigational, transactional).<\/li>\n
                      • Annotate changes<\/strong>: Document content updates, releases, migrations, and major campaigns so you can interpret performance shifts.<\/li>\n
                      • Prioritize by opportunity size and effort<\/strong>: Target pages with high impressions, rankings just outside top results, or high conversion potential.<\/li>\n
                      • Validate intent match<\/strong>: If a page ranks but doesn\u2019t convert, it may satisfy the wrong intent; optimize the page purpose or target a different query set.<\/li>\n
                      • Use cohorts and time comparisons<\/strong>: Compare like-for-like periods (seasonality) and evaluate pre\/post changes with enough time for search to respond.<\/li>\n
                      • Operationalize insights<\/strong>: Turn findings into tickets, briefs, and acceptance criteria that engineering and content teams can execute.<\/li>\n<\/ul>\n\n\n\n

                        These practices keep Organic Search Analysis<\/strong> tightly integrated with Organic Marketing<\/strong> execution and SEO<\/strong> delivery.<\/p>\n\n\n\n

                        Tools Used for Organic Search Analysis<\/h2>\n\n\n\n

                        You don\u2019t need a huge stack, but you do need coverage across search performance, behavior, and technical health. Common tool categories include:<\/p>\n\n\n\n

                          \n
                        • Search performance consoles<\/strong>: Query and page visibility, impressions, clicks, CTR trends, indexing feedback.<\/li>\n
                        • Web analytics tools<\/strong>: Sessions, engagement, events, conversion paths, and audience segmentation for organic traffic.<\/li>\n
                        • SEO tools<\/strong>: Rank monitoring, crawl diagnostics, competitor comparisons, backlink and content research.<\/li>\n
                        • Crawlers and site auditing systems<\/strong>: Identify broken links, redirect chains, duplicate content patterns, and template issues at scale.<\/li>\n
                        • Reporting dashboards \/ BI tools<\/strong>: Centralize Organic Marketing and SEO<\/strong> KPIs, build segmented views, and automate recurring reporting.<\/li>\n
                        • CRM and marketing automation<\/strong>: Connect organic sessions to leads, lifecycle stages, and revenue outcomes.<\/li>\n
                        • Experimentation and QA tools<\/strong>: Support controlled updates, release validation, and monitoring after deployments.<\/li>\n<\/ul>\n\n\n\n

                          The best tooling choice is the one that produces reliable, explainable decisions\u2014not the one with the most charts.<\/p>\n\n\n\n

                          Metrics Related to Organic Search Analysis<\/h2>\n\n\n\n

                          A well-rounded Organic Search Analysis<\/strong> program tracks metrics across visibility, behavior, and outcomes:<\/p>\n\n\n\n

                          Visibility and demand capture<\/h3>\n\n\n\n
                            \n
                          • Impressions (query and page level)<\/li>\n
                          • Clicks and click-through rate (CTR)<\/li>\n
                          • Average position and ranking distribution (top 3, top 10, etc.)<\/li>\n
                          • Share of voice across a defined keyword set (when available)<\/li>\n<\/ul>\n\n\n\n

                            Engagement and quality<\/h3>\n\n\n\n
                              \n
                            • Engagement rate \/ bounce proxies (interpreted carefully)<\/li>\n
                            • Time on page and scroll depth (as directional signals)<\/li>\n
                            • Pages per session for organic cohorts<\/li>\n
                            • Returning visitors from organic entry points<\/li>\n<\/ul>\n\n\n\n

                              Conversion and ROI<\/h3>\n\n\n\n
                                \n
                              • Conversion rate from organic sessions (macro and micro conversions)<\/li>\n
                              • Assisted conversions and multi-touch influence (where measurement supports it)<\/li>\n
                              • Revenue or pipeline attributed to organic (with agreed attribution rules)<\/li>\n
                              • Lead quality indicators (qualification rate, sales acceptance rate)<\/li>\n<\/ul>\n\n\n\n

                                Technical health indicators (supporting SEO<\/strong>)<\/h3>\n\n\n\n
                                  \n
                                • Index coverage trends<\/li>\n
                                • Crawl errors and response codes<\/li>\n
                                • Core performance metrics (speed and stability signals)<\/li>\n
                                • Internal link depth and orphaned pages<\/li>\n<\/ul>\n\n\n\n

                                  Tracking fewer metrics well is better than tracking everything poorly.<\/p>\n\n\n\n

                                  Future Trends of Organic Search Analysis<\/h2>\n\n\n\n

                                  Organic Search Analysis<\/strong> is evolving alongside search behavior and measurement constraints:<\/p>\n\n\n\n

                                    \n
                                  • AI-assisted workflows<\/strong>: Teams increasingly use automation to cluster queries by intent, detect anomalies, and draft optimization hypotheses\u2014while still requiring human validation.<\/li>\n
                                  • More emphasis on intent and usefulness<\/strong>: As search engines get better at interpreting satisfaction, analysis will focus more on whether pages truly solve problems, not just whether they rank.<\/li>\n
                                  • Privacy-driven measurement changes<\/strong>: Aggregation and modeling will push Organic Marketing teams to rely on blended evidence\u2014search console trends, cohort analysis, and CRM outcomes.<\/li>\n
                                  • SERP feature optimization<\/strong>: Visibility is no longer \u201c10 blue links.\u201d Analysis will increasingly track rich results, featured formats, and how they affect CTR.<\/li>\n
                                  • Content lifecycle management<\/strong>: Refreshing, consolidating, and pruning will become as important as publishing new pages for sustainable SEO<\/strong> growth.<\/li>\n<\/ul>\n\n\n\n

                                    Organic Search Analysis vs Related Terms<\/h2>\n\n\n\n

                                    Organic Search Analysis vs Keyword Research<\/strong>\nKeyword research identifies what people search for and how competitive it might be. Organic Search Analysis<\/strong> evaluates how your site is actually performing for real queries and pages, then guides improvements based on results.<\/p>\n\n\n\n

                                    Organic Search Analysis vs Rank Tracking<\/strong>\nRank tracking monitors positions for a selected set of keywords. Organic Search Analysis<\/strong> is broader: it includes impressions, CTR, landing-page performance, conversions, and technical factors\u2014plus interpretation and prioritization.<\/p>\n\n\n\n

                                    Organic Search Analysis vs SEO Audit<\/strong>\nAn SEO<\/strong> audit is typically a point-in-time assessment of technical and on-page issues. Organic Search Analysis<\/strong> is ongoing, performance-driven, and tightly connected to outcomes in Organic Marketing<\/strong>.<\/p>\n\n\n\n

                                    Who Should Learn Organic Search Analysis<\/h2>\n\n\n\n
                                      \n
                                    • Marketers<\/strong> benefit by planning Organic Marketing campaigns that are measurable and aligned to demand and intent.<\/li>\n
                                    • Analysts<\/strong> gain a structured domain for turning noisy search and analytics data into business insight.<\/li>\n
                                    • Agencies<\/strong> use Organic Search Analysis<\/strong> to prove value, prioritize retainers, and communicate impact clearly to clients.<\/li>\n
                                    • Business owners and founders<\/strong> can evaluate whether SEO<\/strong> investment is paying off and where the next growth levers are.<\/li>\n
                                    • Developers<\/strong> who understand the analysis can ship changes that protect crawling, performance, and indexation\u2014reducing expensive rework after releases.<\/li>\n<\/ul>\n\n\n\n

                                      Summary of Organic Search Analysis<\/h2>\n\n\n\n

                                      Organic Search Analysis<\/strong> is the discipline of measuring and interpreting organic search performance to improve results. It matters because it connects SEO<\/strong> activities to real business outcomes and keeps Organic Marketing<\/strong> focused on what drives qualified demand. By combining search visibility data, on-site behavior, technical diagnostics, and conversion metrics, teams can prioritize smarter, fix issues faster, and build compounding growth from organic search.<\/p>\n\n\n\n

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

                                      1) What is Organic Search Analysis and what questions does it answer?<\/h3>\n\n\n\n

                                      Organic Search Analysis<\/strong> examines how your site performs in unpaid search and what to improve. It answers which queries and pages drive visibility, clicks, engagement, and conversions\u2014and why performance changes over time.<\/p>\n\n\n\n

                                      2) How often should I run Organic Search Analysis?<\/h3>\n\n\n\n

                                      For most teams, a weekly check for anomalies plus a monthly deep dive works well. Larger sites often add quarterly reviews for content decay, technical health, and Organic Marketing planning.<\/p>\n\n\n\n

                                      3) Which is more important: rankings or conversions?<\/h3>\n\n\n\n

                                      Conversions are the business outcome, but rankings and CTR influence traffic volume and quality. Strong SEO<\/strong> measurement connects all three: visibility \u2192 clicks \u2192 outcomes, segmented by intent.<\/p>\n\n\n\n

                                      4) Why do impressions increase but clicks stay flat?<\/h3>\n\n\n\n

                                      Common causes include lower average positions, SERP features reducing clicks, weaker titles\/snippets, or showing for broader (less relevant) queries. Organic Search Analysis<\/strong> should isolate which pages and queries changed, then test snippet and intent improvements.<\/p>\n\n\n\n

                                      5) How do I measure Organic Marketing impact if attribution is messy?<\/h3>\n\n\n\n

                                      Use multiple views: search console trends, organic landing-page conversions, assisted conversion reporting where available, and CRM outcomes by first-touch\/last-touch models. Consistency in definitions matters more than a \u201cperfect\u201d model.<\/p>\n\n\n\n

                                      6) What data should I trust most for organic search decisions?<\/h3>\n\n\n\n

                                      Trust the data that\u2019s closest to the source for each question: search performance consoles for query visibility and clicks, analytics for on-site behavior and conversions, and crawlers\/audits for technical issues. Organic Search Analysis<\/strong> works best when these datasets are reconciled rather than viewed in isolation.<\/p>\n\n\n\n

                                      7) What\u2019s a good first project for improving SEO using analysis?<\/h3>\n\n\n\n

                                      Start with pages that have high impressions and low CTR, or pages ranking just outside the top results for valuable queries. These usually offer the fastest wins because demand already exists\u2014you\u2019re simply capturing more of it through targeted SEO<\/strong> and content refinements.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                      Organic Search Analysis is the practice of examining how people discover your site through unpaid search results, what they do after they land, and which optimizations will most reliably improve outcomes. In **Organic Marketing**, it\u2019s the measurement layer that turns \u201cwe publish content\u201d into \u201cwe know which topics, pages, and intents drive qualified demand.\u201d Within **SEO**, it\u2019s how you validate technical fixes, content strategy, and authority-building efforts using evidence instead of assumptions.<\/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-9801","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\/9801","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=9801"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/9801\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=9801"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=9801"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=9801"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}