{"id":9379,"date":"2026-03-27T19:27:24","date_gmt":"2026-03-27T19:27:24","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/store-sales-measurement\/"},"modified":"2026-03-27T19:27:24","modified_gmt":"2026-03-27T19:27:24","slug":"store-sales-measurement","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/store-sales-measurement\/","title":{"rendered":"Store Sales Measurement: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Local Marketing"},"content":{"rendered":"\n

Store Sales Measurement is the discipline of connecting what people do online to what they buy in physical locations. In Organic Marketing<\/strong>, it answers a hard but essential question: Did our unpaid search visibility, local listings, and content actually drive revenue in-store?<\/em> In Local Marketing<\/strong>, it becomes even more important because the customer journey often starts with \u201cnear me\u201d intent and ends at a cash register.<\/p>\n\n\n\n

Modern Organic Marketing<\/strong> is evaluated on outcomes, not just traffic. Rankings and impressions matter, but leaders want proof of business impact\u2014especially for multi-location brands where a small lift in store conversions can outweigh large swings in website sessions. Store Sales Measurement provides the methods, data, and governance to translate local visibility into financial results.<\/p>\n\n\n\n

What Is Store Sales Measurement?<\/h2>\n\n\n\n

Store Sales Measurement<\/strong> is the process of quantifying and attributing in-store revenue (or proxy outcomes like purchases, sign-ups, or appointments that happen at a location) to marketing activities that occurred before the visit. It can include direct tracking (such as redeemed offers) and modeled approaches (such as controlled tests) to estimate incremental sales.<\/p>\n\n\n\n

At its core, Store Sales Measurement answers three practical business questions:<\/p>\n\n\n\n

    \n
  • How much in-store revenue did our marketing influence?<\/strong><\/li>\n
  • Which channels, campaigns, and locations drove the most incremental lift?<\/strong><\/li>\n
  • What should we do next to increase profit, not just engagement?<\/strong><\/li>\n<\/ul>\n\n\n\n

    In Organic Marketing<\/strong>, Store Sales Measurement typically focuses on influence from unpaid channels like local SEO, content, digital PR, social visibility, and local listings. In Local Marketing<\/strong>, it helps evaluate location-level performance\u2014by store, region, or trade area\u2014so teams can prioritize operational and marketing investments where they matter most.<\/p>\n\n\n\n

    Why Store Sales Measurement Matters in Organic Marketing<\/h2>\n\n\n\n

    Store Sales Measurement is strategically important because organic performance is often undervalued when it\u2019s measured only with online metrics<\/strong>. A store visit that leads to a high-value purchase may look like \u201cjust another website session\u201d unless you connect the dots.<\/p>\n\n\n\n

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

      \n
    • Proves ROI where attribution is hardest.<\/strong> Organic discovery often influences decisions early, and the sale happens later offline. Store Sales Measurement makes that influence visible.<\/li>\n
    • Improves prioritization.<\/strong> It helps decide which local pages, topics, and location efforts are worth scaling in Organic Marketing<\/strong>.<\/li>\n
    • Creates competitive advantage.<\/strong> Many brands still optimize for rankings alone. Measuring store sales lift enables smarter content, local listing strategies, and operational alignment.<\/li>\n
    • Aligns marketing with operations.<\/strong> When Local Marketing<\/strong> teams can show revenue impact per location, it becomes easier to justify staffing, inventory changes, or extended hours that amplify results.<\/li>\n<\/ul>\n\n\n\n

      How Store Sales Measurement Works<\/h2>\n\n\n\n

      Store Sales Measurement can be implemented in multiple ways, but in practice it follows a common workflow from signals to outcomes:<\/p>\n\n\n\n

        \n
      1. \n

        Input (customer signals and marketing touchpoints)<\/strong>\n You collect evidence of intent and engagement that often precedes a store visit: local search impressions, listing interactions, calls, direction requests, product views, appointment requests, email sign-ups, and loyalty identification.<\/p>\n<\/li>\n

      2. \n

        Processing (identity resolution and matching)<\/strong>\n Data is normalized and matched across systems. This may include matching purchases to a loyalty ID, mapping phone calls to store outcomes, or aggregating store-level sales to compare against periods of increased Organic Marketing<\/strong> activity. When direct matching isn\u2019t possible, statistical methods estimate incremental lift.<\/p>\n<\/li>\n

      3. \n

        Application (attribution and analysis)<\/strong>\n You attribute or model how much store revenue is associated with specific activities\u2014often by location, time window, and intent type. In Local Marketing<\/strong>, this is where you compare stores, regions, or store clusters to find what\u2019s working.<\/p>\n<\/li>\n

      4. \n

        Output (decisions and optimization)<\/strong>\n The output is actionable reporting: incremental store sales, revenue per visit, category-level lift, and insights that guide local SEO strategy, content planning, listing optimization, and store operations.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

        The goal isn\u2019t \u201cperfect certainty.\u201d The goal is decision-grade measurement<\/strong> that\u2019s consistent, repeatable, and accurate enough to improve outcomes.<\/p>\n\n\n\n

        Key Components of Store Sales Measurement<\/h2>\n\n\n\n

        Strong Store Sales Measurement programs combine data, process, and accountability:<\/p>\n\n\n\n

        Data inputs<\/h3>\n\n\n\n
          \n
        • Point-of-sale (POS) transactions (revenue, product category, timestamp, store ID)<\/li>\n
        • Customer data (loyalty membership, email\/phone when consented)<\/li>\n
        • Local listing interactions (calls, directions, clicks)<\/li>\n
        • Website behavior (store locator usage, local page engagement, inventory checks)<\/li>\n
        • Call and appointment logs<\/li>\n
        • Promo or offer redemption data (when used)<\/li>\n<\/ul>\n\n\n\n

          Systems and integrations<\/h3>\n\n\n\n
            \n
          • POS and order management systems<\/li>\n
          • Customer relationship management (CRM) or customer data platforms<\/li>\n
          • Analytics tagging for local pages and store-locator flows<\/li>\n
          • Location management data (store IDs, addresses, hours, categories)<\/li>\n<\/ul>\n\n\n\n

            Processes and governance<\/h3>\n\n\n\n
              \n
            • A shared store ID standard across marketing and operations<\/li>\n
            • Defined attribution windows (same-day, 7-day, 30-day)<\/li>\n
            • Consent and privacy controls (especially for identity matching)<\/li>\n
            • A reporting cadence that supports Organic Marketing<\/strong> iteration and Local Marketing<\/strong> planning<\/li>\n<\/ul>\n\n\n\n

              People and responsibilities<\/h3>\n\n\n\n
                \n
              • Marketing owns strategy and experimentation<\/li>\n
              • Analytics owns methodology, QA, and interpretation<\/li>\n
              • Store operations validates reality (foot traffic, staffing, local factors)<\/li>\n
              • Leadership agrees on KPIs and acceptable uncertainty<\/li>\n<\/ul>\n\n\n\n

                Types of Store Sales Measurement<\/h2>\n\n\n\n

                Store Sales Measurement doesn\u2019t have one universal method. The most useful distinctions are based on how directly you can connect the online touchpoint to the offline transaction<\/em>.<\/p>\n\n\n\n

                1) Deterministic (direct) measurement<\/h3>\n\n\n\n

                You can directly tie a marketing interaction to a purchase using an explicit identifier, such as:\n– Redeemed offer code unique to a local page\n– Loyalty or membership ID captured at checkout\n– Appointment booked online and completed in-store<\/p>\n\n\n\n

                This approach is precise but often incomplete, because not all customers identify themselves.<\/p>\n\n\n\n

                2) Probabilistic or modeled measurement<\/h3>\n\n\n\n

                When direct matching is limited, you estimate impact using patterns and statistical techniques:\n– Pre\/post comparisons with controls\n– Geo-based experiments (test vs holdout locations)\n– Time-series models accounting for seasonality and promotions<\/p>\n\n\n\n

                This is common in Organic Marketing<\/strong>, where users may discover you via search but never click a trackable element.<\/p>\n\n\n\n

                3) Proxy-based measurement (leading indicators)<\/h3>\n\n\n\n

                Sometimes you measure behaviors strongly correlated with store sales:\n– Calls to a location\n– \u201cGet directions\u201d actions\n– Store-locator usage\n– In-stock checks or product detail views tied to nearby stores<\/p>\n\n\n\n

                Proxy metrics are not the same as revenue, but they are valuable for Local Marketing<\/strong> optimization when calibrated against sales trends.<\/p>\n\n\n\n

                Real-World Examples of Store Sales Measurement<\/h2>\n\n\n\n

                Example 1: Multi-location retailer improving local SEO<\/h3>\n\n\n\n

                A retailer invests in local landing pages, FAQ content, and improved location data consistency. Store Sales Measurement combines:\n– Local page engagement and store-locator usage\n– Direction requests and calls\n– POS sales by store and category<\/p>\n\n\n\n

                By comparing stores that received content upgrades vs similar stores that did not, the brand estimates incremental revenue lift and prioritizes rollout to high-potential markets\u2014turning Organic Marketing<\/strong> work into a measurable Local Marketing<\/strong> growth plan.<\/p>\n\n\n\n

                Example 2: Restaurant chain connecting listings to revenue<\/h3>\n\n\n\n

                A restaurant sees rising visibility in local search and listings. Store Sales Measurement focuses on:\n– Calls and reservation requests from local listings\n– Walk-in traffic patterns by daypart\n– In-store sales during windows following spikes in listing interactions<\/p>\n\n\n\n

                The team learns that photos and menu updates increase high-intent actions on weekends, and adjusts publishing cadence accordingly\u2014improving both customer experience and store revenue.<\/p>\n\n\n\n

                Example 3: Service business measuring offline conversions from content<\/h3>\n\n\n\n

                A home services brand publishes \u201ccost\u201d and \u201chow-to-choose\u201d content targeting local intent. Store Sales Measurement ties:\n– Form fills and calls to CRM opportunities\n– Booked appointments to completed jobs\n– Revenue back to the content and location pages that influenced the lead<\/p>\n\n\n\n

                This connects Organic Marketing<\/strong> education content to Local Marketing<\/strong> performance by territory and helps allocate effort to the best-converting topics.<\/p>\n\n\n\n

                Benefits of Using Store Sales Measurement<\/h2>\n\n\n\n

                Store Sales Measurement delivers benefits that go beyond reporting:<\/p>\n\n\n\n

                  \n
                • Better budgeting:<\/strong> You can defend investment in local SEO and content with revenue-based outcomes.<\/li>\n
                • More efficient optimization:<\/strong> Teams stop chasing vanity metrics and focus on actions that increase store conversion.<\/li>\n
                • Higher-quality customer journeys:<\/strong> Measurement reveals friction points (wrong hours, missing inventory info, confusing directions) that hurt in-store outcomes.<\/li>\n
                • Improved location strategy:<\/strong> Local Marketing<\/strong> decisions become evidence-based\u2014supporting smarter rollouts, staffing, and local promotions.<\/li>\n
                • Faster learning cycles:<\/strong> When outcomes are measurable, experimentation becomes safer and more productive.<\/li>\n<\/ul>\n\n\n\n

                  Challenges of Store Sales Measurement<\/h2>\n\n\n\n

                  Store Sales Measurement is powerful, but it has real constraints:<\/p>\n\n\n\n

                    \n
                  • Identity and privacy limitations:<\/strong> Many customers won\u2019t identify themselves in-store; consent requirements limit matching.<\/li>\n
                  • Data silos:<\/strong> POS, CRM, analytics, and listing data often live in separate systems with inconsistent store IDs.<\/li>\n
                  • Attribution bias:<\/strong> Customers may interact with multiple channels; over-crediting one touchpoint is common.<\/li>\n
                  • External factors:<\/strong> Weather, local events, competitor actions, and inventory issues can distort results.<\/li>\n
                  • Small sample sizes for single locations:<\/strong> Some stores don\u2019t have enough volume for confident modeling, especially over short windows.<\/li>\n<\/ul>\n\n\n\n

                    Good programs acknowledge these limitations and use a mix of direct, modeled, and proxy approaches.<\/p>\n\n\n\n

                    Best Practices for Store Sales Measurement<\/h2>\n\n\n\n
                      \n
                    1. \n

                      Start with a clear measurement question.<\/strong>\n Examples: \u201cDid optimizing location pages increase incremental store sales?\u201d or \u201cWhich markets gained revenue after listing improvements?\u201d<\/p>\n<\/li>\n

                    2. \n

                      Standardize store identifiers across systems.<\/strong>\n A shared store ID and clean location hierarchy are foundational for Local Marketing<\/strong> reporting.<\/p>\n<\/li>\n

                    3. \n

                      Use multiple methods, not just one.<\/strong>\n Combine deterministic signals (offer redemption, loyalty) with modeled lift and calibrated proxies.<\/p>\n<\/li>\n

                    4. \n

                      Define attribution windows by business reality.<\/strong>\n Grocery might convert quickly; furniture may take weeks. Align windows to your category and buying cycle.<\/p>\n<\/li>\n

                    5. \n

                      Control for seasonality and promos.<\/strong>\n Always annotate campaigns, holidays, promotions, and price changes so analysis doesn\u2019t misattribute lift.<\/p>\n<\/li>\n

                    6. \n

                      Measure incrementality where possible.<\/strong>\n Use holdouts, matched markets, or phased rollouts to estimate what would have happened without the Organic Marketing<\/strong> change.<\/p>\n<\/li>\n

                    7. \n

                      Operationalize reporting.<\/strong>\n Build a recurring cadence: location-level dashboards, monthly reviews, and a documented methodology so results are trusted.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                      Tools Used for Store Sales Measurement<\/h2>\n\n\n\n

                      Store Sales Measurement is usually implemented with a stack of complementary tool types:<\/p>\n\n\n\n

                        \n
                      • Analytics tools:<\/strong> Track local page engagement, store-locator behavior, and conversion events like calls or appointment requests.<\/li>\n
                      • Tag management and event tracking:<\/strong> Ensure consistent measurement across location templates and mobile experiences.<\/li>\n
                      • CRM systems:<\/strong> Connect leads, appointments, and customer records to outcomes\u2014especially valuable for service-based Local Marketing<\/strong>.<\/li>\n
                      • POS and order systems:<\/strong> The source of truth for store revenue, returns, and product categories.<\/li>\n
                      • Call tracking and appointment systems:<\/strong> Capture high-intent offline actions and connect them to marketing sources.<\/li>\n
                      • SEO tools:<\/strong> Monitor local visibility, query trends, and location page performance to tie organic exposure to store outcomes.<\/li>\n
                      • Reporting dashboards and BI tools:<\/strong> Combine POS, analytics, and location data into store-level and market-level views.<\/li>\n<\/ul>\n\n\n\n

                        No single tool \u201csolves\u201d Store Sales Measurement. The advantage comes from clean data design and consistent methodology.<\/p>\n\n\n\n

                        Metrics Related to Store Sales Measurement<\/h2>\n\n\n\n

                        The right metrics depend on your model, but these are commonly useful:<\/p>\n\n\n\n

                        Revenue and outcome metrics<\/h3>\n\n\n\n
                          \n
                        • Incremental store revenue (estimated lift)<\/li>\n
                        • In-store conversion rate (when trackable)<\/li>\n
                        • Average order value (AOV) and margin impact<\/li>\n
                        • Revenue per store visit or per high-intent action<\/li>\n<\/ul>\n\n\n\n

                          Local intent and proxy metrics<\/h3>\n\n\n\n
                            \n
                          • Calls to locations (qualified vs unqualified)<\/li>\n
                          • Direction requests and store-locator usage<\/li>\n
                          • Appointment bookings and show rates<\/li>\n
                          • In-stock checks or product availability interactions<\/li>\n<\/ul>\n\n\n\n

                            Efficiency and ROI-style metrics<\/h3>\n\n\n\n
                              \n
                            • Cost per incremental store sale (especially when labor\/content costs are included)<\/li>\n
                            • Time-to-impact for Organic Marketing<\/strong> improvements<\/li>\n
                            • Revenue per content update or per optimized location<\/li>\n<\/ul>\n\n\n\n

                              Quality and trust metrics<\/h3>\n\n\n\n
                                \n
                              • Data match rate (how many sales can be linked deterministically)<\/li>\n
                              • Model confidence intervals or error ranges (for lift studies)<\/li>\n
                              • Coverage by location (how many stores are reliably measurable)<\/li>\n<\/ul>\n\n\n\n

                                Future Trends of Store Sales Measurement<\/h2>\n\n\n\n

                                Store Sales Measurement is evolving quickly, especially within Organic Marketing<\/strong>:<\/p>\n\n\n\n

                                  \n
                                • More automation in data pipelines:<\/strong> Faster, cleaner integration across POS, CRM, and analytics reduces reporting lag.<\/li>\n
                                • Better experimentation frameworks:<\/strong> Geo-tests and incrementality methods will become more common to prove lift without relying on personal identifiers.<\/li>\n
                                • AI-assisted anomaly detection and forecasting:<\/strong> Teams will use forecasting to spot unusual store performance and connect it to local search demand shifts.<\/li>\n
                                • Privacy-first measurement:<\/strong> Expect more aggregation, modeling, and consent-driven matching rather than one-to-one tracking.<\/li>\n
                                • Personalization tied to local context:<\/strong> Content and local experiences will adapt by region, inventory, and intent\u2014raising the need for store-level measurement in Local Marketing<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                                  The direction is clear: less reliance on fragile identifiers, more emphasis on incrementality and operational decision-making.<\/p>\n\n\n\n

                                  Store Sales Measurement vs Related Terms<\/h2>\n\n\n\n

                                  Store Sales Measurement vs foot traffic measurement<\/h3>\n\n\n\n

                                  Foot traffic measurement focuses on visits (people entering a location), often without confirming purchases. Store Sales Measurement aims to quantify sales outcomes<\/strong>, not just visits\u2014though visits may be an input or proxy.<\/p>\n\n\n\n

                                  Store Sales Measurement vs offline conversion tracking<\/h3>\n\n\n\n

                                  Offline conversion tracking typically connects a digital interaction to an offline outcome (sale, appointment) using identifiers. Store Sales Measurement is broader: it includes offline conversion tracking and<\/em> modeled incrementality, store-level lift analysis, and revenue-focused governance.<\/p>\n\n\n\n

                                  Store Sales Measurement vs marketing mix modeling (MMM)<\/h3>\n\n\n\n

                                  MMM estimates channel impact at an aggregated level (often regional or national) over time. Store Sales Measurement is usually more location-centric and tactical, supporting Local Marketing<\/strong> decisions and Organic Marketing<\/strong> optimization at the store or market level.<\/p>\n\n\n\n

                                  Who Should Learn Store Sales Measurement<\/h2>\n\n\n\n
                                    \n
                                  • Marketers:<\/strong> To prove the business value of Organic Marketing<\/strong> efforts and prioritize what drives real revenue.<\/li>\n
                                  • Analysts:<\/strong> To design measurement frameworks, validate data quality, and quantify incrementality.<\/li>\n
                                  • Agencies:<\/strong> To connect local SEO deliverables to outcomes clients care about\u2014store sales and profitability.<\/li>\n
                                  • Business owners and founders:<\/strong> To understand which local investments create sustainable growth, not just online activity.<\/li>\n
                                  • Developers and data teams:<\/strong> To implement clean event tracking, integrate POS\/CRM data, and maintain privacy-compliant pipelines.<\/li>\n<\/ul>\n\n\n\n

                                    Summary of Store Sales Measurement<\/h2>\n\n\n\n

                                    Store Sales Measurement is the practice of connecting digital touchpoints to in-store revenue using direct matching, modeled lift, and calibrated proxy metrics. It matters because Organic Marketing<\/strong> often drives high-intent local discovery, but the purchase happens offline\u2014making value easy to underestimate. Within Local Marketing<\/strong>, Store Sales Measurement enables store-level decisions, smarter rollouts, and better alignment between marketing and operations. Done well, it turns local visibility into measurable, repeatable revenue growth.<\/p>\n\n\n\n

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

                                    1) What is Store Sales Measurement and what does it include?<\/h3>\n\n\n\n

                                    Store Sales Measurement includes the methods used to quantify how marketing influences in-store revenue, including direct linkage (loyalty, offer redemption, appointments), modeled lift studies, and proxy metrics like calls and directions calibrated against sales.<\/p>\n\n\n\n

                                    2) How does Store Sales Measurement apply to Organic Marketing specifically?<\/h3>\n\n\n\n

                                    In Organic Marketing<\/strong>, direct attribution is often limited, so Store Sales Measurement frequently combines local search visibility data, location page engagement, listing interactions, and store-level sales trends to estimate incremental impact and guide optimization.<\/p>\n\n\n\n

                                    3) What\u2019s the difference between measuring store visits and measuring store sales?<\/h3>\n\n\n\n

                                    Store visits show intent and traffic, but they don\u2019t confirm revenue. Store Sales Measurement focuses on purchase outcomes (or closely linked conversions) and is therefore better aligned with business performance.<\/p>\n\n\n\n

                                    4) Which Local Marketing activities benefit most from Store Sales Measurement?<\/h3>\n\n\n\n

                                    Local Marketing<\/strong> activities like location page optimization, local listing improvements, review strategy, store-locator UX, and local content can all be evaluated with Store Sales Measurement to determine which actions increase in-store conversions and revenue.<\/p>\n\n\n\n

                                    5) Do I need customer-level data to do Store Sales Measurement?<\/h3>\n\n\n\n

                                    No. Customer-level matching can improve precision, but you can also use aggregated store-level modeling, controlled rollouts, and proxy metrics to estimate incremental sales while respecting privacy constraints.<\/p>\n\n\n\n

                                    6) How long does it take to see results from Store Sales Measurement efforts?<\/h3>\n\n\n\n

                                    It depends on sales cycle and data readiness. Some proxy signals (calls, direction requests) move quickly, while revenue lift from Organic Marketing<\/strong> improvements may require several weeks to separate signal from seasonality and noise.<\/p>\n\n\n\n

                                    7) What\u2019s a practical first step to implement Store Sales Measurement?<\/h3>\n\n\n\n

                                    Start by standardizing store IDs and ensuring you can report weekly store sales by location alongside key local intent signals (calls, directions, store-locator usage). Then run a phased rollout of a local SEO improvement to measure incremental lift across test vs comparison locations.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                    Store Sales Measurement is the discipline of connecting what people do online to what they buy in physical locations. In **Organic Marketing**, it answers a hard but essential question: *Did our unpaid search visibility, local listings, and content actually drive revenue in-store?* In **Local Marketing**, it becomes even more important because the customer journey often starts with \u201cnear me\u201d intent and ends at a cash register.<\/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":[1904],"tags":[],"class_list":["post-9379","post","type-post","status-publish","format-standard","hentry","category-local-marketing"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/9379","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=9379"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/9379\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=9379"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=9379"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=9379"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}