{"id":6867,"date":"2026-03-23T15:41:13","date_gmt":"2026-03-23T15:41:13","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/first-user-source\/"},"modified":"2026-03-23T15:41:13","modified_gmt":"2026-03-23T15:41:13","slug":"first-user-source","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/first-user-source\/","title":{"rendered":"First User Source: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Analytics"},"content":{"rendered":"\n

In modern Conversion & Measurement<\/strong>, it\u2019s not enough to know what caused a conversion today\u2014you also need to understand what originally brought a user into your business. First User Source<\/strong> is the concept that captures that original acquisition point, helping teams connect early marketing touchpoints to downstream outcomes like sign-ups, purchases, renewals, and lifetime value.<\/p>\n\n\n\n

In Analytics<\/strong>, this idea is foundational for answering questions such as: \u201cWhich channels bring in the highest-quality customers over time?\u201d and \u201cAre we investing in sources that create long-term growth, not just short-term conversions?\u201d When used correctly, First User Source<\/strong> improves attribution reasoning, cohort analysis, and budget decisions across your Conversion & Measurement<\/strong> strategy.<\/p>\n\n\n\n

\n\n\n\n

What Is First User Source?<\/h2>\n\n\n\n

First User Source<\/strong> is the original traffic source (or acquisition origin) that first introduced a user to your website, app, or digital property\u2014typically the first known source associated with that user in your measurement system.<\/p>\n\n\n\n

At a beginner level, it answers: \u201cWhere did this user come from the very first time we saw them?\u201d<\/strong> That might be organic search, a paid campaign, a referral site, an email newsletter, or direct traffic.<\/p>\n\n\n\n

At a business level, First User Source<\/strong> is about customer acquisition origin<\/em>, not just conversion origin<\/em>. It helps you understand which marketing investments create new users who later become customers\u2014even if the purchase happens days or months later through a different channel.<\/p>\n\n\n\n

Within Conversion & Measurement<\/strong>, First User Source<\/strong> is commonly used to:\n– Segment users into acquisition cohorts (e.g., \u201cusers first acquired via organic search\u201d)\n– Evaluate downstream conversion rates by acquisition origin\n– Compare customer quality (repeat purchase rate, retention, LTV) by source<\/p>\n\n\n\n

Inside Analytics<\/strong>, it functions as a user-level acquisition attribute that complements session-level dimensions (like session source) and conversion-level reporting (like last touch).<\/p>\n\n\n\n

\n\n\n\n

Why First User Source Matters in Conversion & Measurement<\/h2>\n\n\n\n

First User Source<\/strong> matters because acquisition decisions compound over time. If you only optimize to the last click before a purchase, you can end up over-investing in \u201ccloser\u201d channels and under-investing in the channels that introduce net-new users.<\/p>\n\n\n\n

Key reasons it\u2019s strategically important in Conversion & Measurement<\/strong>:<\/p>\n\n\n\n

    \n
  • Budget allocation with a longer lens:<\/strong> It highlights sources that generate customers later, not just immediately.<\/li>\n
  • Better funnel accountability:<\/strong> Top-of-funnel efforts (SEO, partnerships, awareness campaigns) can be evaluated based on the long-term conversions they initiate.<\/li>\n
  • Cohort-based performance insights:<\/strong> In Analytics<\/strong>, acquisition cohorts based on First User Source<\/strong> can reveal meaningful differences in conversion velocity, retention, and monetization.<\/li>\n
  • Competitive advantage:<\/strong> Teams that understand the true origin of high-value users can scale the right channels earlier and more confidently.<\/li>\n<\/ul>\n\n\n\n

    For many organizations, improving Conversion & Measurement<\/strong> means moving from \u201cWhat converted?\u201d to \u201cWhat created<\/em> the customer?\u201d First User Source<\/strong> is one of the cleanest building blocks for that shift.<\/p>\n\n\n\n

    \n\n\n\n

    How First User Source Works<\/h2>\n\n\n\n

    While implementations vary by platform, First User Source<\/strong> typically works like this in practice:<\/p>\n\n\n\n

      \n
    1. \n

      Input \/ Trigger (user acquisition event)<\/strong>\n A new user arrives via a channel: organic search, paid ad, social, referral, email, etc. The visit may include campaign parameters (like UTM tags) or referrer information that indicates the source.<\/p>\n<\/li>\n

    2. \n

      Processing (identity and persistence)<\/strong>\n The measurement system determines whether the visitor is \u201cnew\u201d and then attempts to persist the acquisition origin at the user level. Persistence might rely on device identifiers, first-party cookies, or authenticated user IDs.<\/p>\n<\/li>\n

    3. \n

      Application (reporting and segmentation)<\/strong>\n In Analytics<\/strong>, you can segment users, sessions, and conversions using First User Source<\/strong> to see how downstream outcomes differ by original acquisition channel.<\/p>\n<\/li>\n

    4. \n

      Output \/ Outcome (decision-making)<\/strong>\n Marketers use those insights to optimize channel mix, improve acquisition creative, refine landing pages, and align Conversion & Measurement<\/strong> reporting with business outcomes like revenue quality and retention.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

      A critical nuance: First User Source is not \u201cwhat brought the conversion.\u201d<\/strong> It\u2019s \u201cwhat brought the user into your ecosystem initially.\u201d<\/p>\n\n\n\n

      \n\n\n\n

      Key Components of First User Source<\/h2>\n\n\n\n

      A reliable First User Source<\/strong> depends on multiple components working together across Conversion & Measurement<\/strong> and Analytics<\/strong>:<\/p>\n\n\n\n

      Data inputs<\/h3>\n\n\n\n
        \n
      • Referrer data<\/strong> (where the click came from)<\/li>\n
      • Campaign parameters<\/strong> (tagged campaigns for paid, email, partners)<\/li>\n
      • Deep links<\/strong> (for apps) and attribution parameters<\/li>\n
      • Offline-to-online connectors<\/strong> (e.g., QR codes, vanity domains) when applicable<\/li>\n<\/ul>\n\n\n\n

        Identity and persistence<\/h3>\n\n\n\n
          \n
        • First-party identifiers<\/strong> (cookies or local storage, where allowed)<\/li>\n
        • Authenticated user ID<\/strong> (best for cross-device continuity)<\/li>\n
        • Rules that determine whether the system treats someone as \u201cnew\u201d vs. \u201creturning\u201d<\/li>\n<\/ul>\n\n\n\n

          Processes and governance<\/h3>\n\n\n\n
            \n
          • A consistent campaign tagging taxonomy<\/strong> (source\/medium\/campaign naming conventions)<\/li>\n
          • QA procedures for tracking changes and marketing launches<\/li>\n
          • Clear ownership: marketing operations, analytics engineers, or growth teams typically steward these definitions<\/li>\n<\/ul>\n\n\n\n

            Reporting usage<\/h3>\n\n\n\n
              \n
            • Cohort dashboards that compare conversion rate, CAC, and LTV by First User Source<\/strong><\/li>\n
            • Documentation so stakeholders interpret user acquisition vs. session acquisition correctly in Analytics<\/strong><\/li>\n<\/ul>\n\n\n\n
              \n\n\n\n

              Types of First User Source<\/h2>\n\n\n\n

              First User Source<\/strong> doesn\u2019t always have formal \u201ctypes,\u201d but there are practical distinctions that materially affect Conversion & Measurement<\/strong> accuracy:<\/p>\n\n\n\n

              1) Deterministic vs. probabilistic user identity<\/h3>\n\n\n\n
                \n
              • Deterministic:<\/strong> Based on login or stable user ID; best for cross-device attribution in Analytics<\/strong>.<\/li>\n
              • Probabilistic:<\/strong> Inferred identity without login; more fragile and sensitive to privacy changes.<\/li>\n<\/ul>\n\n\n\n

                2) First-ever vs. first-known source<\/h3>\n\n\n\n
                  \n
                • First-ever:<\/strong> Truly the first acquisition event, preserved indefinitely.<\/li>\n
                • First-known:<\/strong> The earliest source captured within your current measurement window<\/em> (e.g., after tracking started, or after a storage reset).<\/li>\n<\/ul>\n\n\n\n

                  3) Web vs. app acquisition context<\/h3>\n\n\n\n
                    \n
                  • Web relies heavily on referrers and campaign parameters.<\/li>\n
                  • Apps may rely more on deep links, install attribution, and post-install events.<\/li>\n<\/ul>\n\n\n\n

                    4) \u201cSticky\u201d source vs. reset rules<\/h3>\n\n\n\n

                    Some organizations keep First User Source<\/strong> permanently; others reset it after long inactivity or when a user explicitly re-consents. These rules should be documented because they directly impact Conversion & Measurement<\/strong> interpretations.<\/p>\n\n\n\n

                    \n\n\n\n

                    Real-World Examples of First User Source<\/h2>\n\n\n\n

                    Example 1: SEO-driven user acquisition with delayed conversion<\/h3>\n\n\n\n

                    A SaaS company acquires users via non-branded organic search. Many visitors don\u2019t sign up immediately; they return later via direct traffic and convert. Session-level reports credit \u201cdirect,\u201d but First User Source<\/strong> shows organic search initiated the relationship\u2014supporting investment in SEO as part of Conversion & Measurement<\/strong> planning and Analytics<\/strong> reporting.<\/p>\n\n\n\n

                    Example 2: Paid social introduces users; email closes the deal<\/h3>\n\n\n\n

                    An ecommerce brand runs prospecting ads on social platforms and later converts users through email promotions. Last-click reporting might over-credit email. First User Source<\/strong> allows the team to evaluate whether paid social is bringing in high-value cohorts and how those users behave over time in Analytics<\/strong>.<\/p>\n\n\n\n

                    Example 3: Partner referrals with variable conversion quality<\/h3>\n\n\n\n

                    A B2B company runs multiple referral partnerships. First User Source<\/strong> lets analysts compare lead-to-opportunity rate and sales cycle length by partner origin, improving Conversion & Measurement<\/strong> from \u201cmore leads\u201d to \u201cbetter pipeline.\u201d<\/p>\n\n\n\n

                    \n\n\n\n

                    Benefits of Using First User Source<\/h2>\n\n\n\n

                    When applied thoughtfully, First User Source<\/strong> delivers measurable improvements across Conversion & Measurement<\/strong>:<\/p>\n\n\n\n

                      \n
                    • Higher-quality acquisition decisions:<\/strong> You optimize for sources that generate valuable users, not just cheap clicks.<\/li>\n
                    • More accurate cohort insights in Analytics:<\/strong> You can track retention, repeat purchase, and LTV by acquisition origin.<\/li>\n
                    • Cost efficiency:<\/strong> By identifying low-quality sources early, you reduce wasted spend and improve CAC-to-LTV ratios.<\/li>\n
                    • Better customer experience:<\/strong> Knowing acquisition origin helps tailor onboarding and messaging\u2014especially when combined with landing page intent and content engagement.<\/li>\n
                    • Stronger cross-team alignment:<\/strong> Marketing, product, and sales can align around which sources create long-term customers, improving how Analytics<\/strong> is used for planning.<\/li>\n<\/ul>\n\n\n\n
                      \n\n\n\n

                      Challenges of First User Source<\/h2>\n\n\n\n

                      Despite its value, First User Source<\/strong> can be misunderstood or degraded by real-world constraints:<\/p>\n\n\n\n

                        \n
                      • Identity fragmentation:<\/strong> Users switch devices or browsers; without login, the \u201cfirst\u201d source may be lost, impacting Analytics<\/strong> accuracy.<\/li>\n
                      • Privacy and consent constraints:<\/strong> Storage limits, consent requirements, and tracking restrictions can reduce persistence and lead to \u201cunknown\u201d or \u201cdirect\u201d inflation.<\/li>\n
                      • Campaign tagging inconsistency:<\/strong> Inconsistent source naming breaks comparisons and undermines Conversion & Measurement<\/strong> reporting credibility.<\/li>\n
                      • Misinterpretation by stakeholders:<\/strong> Teams may confuse user acquisition source with session source or last touch, leading to incorrect optimization decisions.<\/li>\n
                      • Data drift over time:<\/strong> Tracking updates, site migrations, and channel changes can alter how First User Source<\/strong> is recorded unless governed carefully.<\/li>\n<\/ul>\n\n\n\n
                        \n\n\n\n

                        Best Practices for First User Source<\/h2>\n\n\n\n

                        To make First User Source<\/strong> dependable and useful in Conversion & Measurement<\/strong>, focus on these practical actions:<\/p>\n\n\n\n

                          \n
                        1. \n

                          Standardize campaign tagging<\/strong>\n – Define naming conventions for source, medium, campaign, and content.\n – Enforce consistency across paid, email, affiliates, influencers, and partnerships.<\/p>\n<\/li>\n

                        2. \n

                          Prioritize first-party, consented measurement<\/strong>\n – Use consent-aware tracking patterns.\n – Where feasible, encourage authentication to strengthen user identity in Analytics<\/strong>.<\/p>\n<\/li>\n

                        3. \n

                          Document attribution definitions<\/strong>\n – Clarify how First User Source<\/strong> differs from session source and conversion attribution.\n – Include rules for \u201cnew user,\u201d source persistence, and any reset logic.<\/p>\n<\/li>\n

                        4. \n

                          QA before and after launches<\/strong>\n – Validate that campaigns resolve into the expected source values.\n – Monitor spikes in \u201cdirect,\u201d \u201cunknown,\u201d or malformed sources that can distort Conversion & Measurement<\/strong>.<\/p>\n<\/li>\n

                        5. \n

                          Use cohorts, not just totals<\/strong>\n – Compare conversion rate, revenue, retention, and LTV by First User Source<\/strong> cohort to get decision-grade insights.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                          \n\n\n\n

                          Tools Used for First User Source<\/h2>\n\n\n\n

                          You don\u2019t \u201cbuy\u201d First User Source<\/strong> as a standalone tool; you operationalize it across your Analytics<\/strong> and Conversion & Measurement<\/strong> stack:<\/p>\n\n\n\n

                            \n
                          • Analytics tools:<\/strong> Capture acquisition dimensions, user identifiers, and event streams; enable segmentation and cohort reporting.<\/li>\n
                          • Tag management systems:<\/strong> Manage marketing tags, consent logic, and deployment governance.<\/li>\n
                          • Ad platforms:<\/strong> Provide campaign metadata and click identifiers that help classify acquisition origin.<\/li>\n
                          • CRM systems:<\/strong> Connect user acquisition to lead status, pipeline stages, and revenue outcomes.<\/li>\n
                          • Marketing automation tools:<\/strong> Tie acquisition origin to nurture sequences and lifecycle messaging.<\/li>\n
                          • Data warehouses \/ ELT pipelines:<\/strong> Unify user identity, stitch touchpoints, and build durable cohort models for advanced Analytics<\/strong>.<\/li>\n
                          • Reporting dashboards:<\/strong> Standardize stakeholder views so First User Source<\/strong> is interpreted correctly in Conversion & Measurement<\/strong> discussions.<\/li>\n<\/ul>\n\n\n\n
                            \n\n\n\n

                            Metrics Related to First User Source<\/h2>\n\n\n\n

                            First User Source<\/strong> becomes powerful when paired with metrics that reflect both conversion efficiency and customer quality:<\/p>\n\n\n\n

                              \n
                            • User-to-signup conversion rate by source<\/strong><\/li>\n
                            • First purchase rate and time-to-convert by source<\/strong><\/li>\n
                            • Cost per acquired user (blended) by source<\/strong><\/li>\n
                            • Customer acquisition cost (CAC) by source cohort<\/strong><\/li>\n
                            • Lifetime value (LTV) by source cohort<\/strong><\/li>\n
                            • Retention \/ repeat purchase rate by source<\/strong><\/li>\n
                            • Pipeline metrics (B2B):<\/strong> lead-to-opportunity rate, win rate, sales cycle length by source<\/li>\n
                            • Data quality indicators:<\/strong> percentage of users with known First User Source<\/strong>, share of \u201cdirect\/unknown,\u201d campaign taxonomy error rate<\/li>\n<\/ul>\n\n\n\n

                              These metrics keep Analytics<\/strong> tied to outcomes that matter, strengthening Conversion & Measurement<\/strong> beyond surface-level attribution.<\/p>\n\n\n\n

                              \n\n\n\n

                              Future Trends of First User Source<\/h2>\n\n\n\n

                              Several shifts are changing how First User Source<\/strong> is captured and used within Conversion & Measurement<\/strong>:<\/p>\n\n\n\n

                                \n
                              • Privacy-first measurement:<\/strong> Expect more consent-aware tracking, modeled data, and a stronger focus on first-party identifiers\u2014raising the value of clean campaign taxonomy and authenticated experiences.<\/li>\n
                              • Automation and AI-assisted insights:<\/strong> Analytics<\/strong> platforms and BI tools increasingly surface cohort anomalies and predict LTV by acquisition origin, making First User Source<\/strong> more actionable.<\/li>\n
                              • More emphasis on quality signals:<\/strong> Teams are moving from channel-level optimization to user-level quality optimization (retention, margin, propensity), where First User Source<\/strong> is a key dimension.<\/li>\n
                              • Cross-channel identity resolution:<\/strong> As organizations mature, they\u2019ll rely more on unified identity strategies (within privacy limits) to preserve acquisition origin across devices and platforms.<\/li>\n<\/ul>\n\n\n\n

                                The net effect: First User Source<\/strong> is evolving from a simple dimension into a central pillar of strategic Conversion & Measurement<\/strong>.<\/p>\n\n\n\n

                                \n\n\n\n

                                First User Source vs Related Terms<\/h2>\n\n\n\n

                                First User Source vs Session Source<\/h3>\n\n\n\n
                                  \n
                                • First User Source:<\/strong> Where the user originally came from the first time they were acquired.<\/li>\n
                                • Session source:<\/strong> Where the user came from for a specific visit<\/em>.\nUse session source for immediate campaign performance; use First User Source<\/strong> for cohort quality and long-term attribution thinking in Analytics<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                                  First User Source vs Last Click (Last Touch) Attribution<\/h3>\n\n\n\n
                                    \n
                                  • Last click:<\/strong> Credits the final interaction before conversion.<\/li>\n
                                  • First User Source:<\/strong> Credits the original acquisition of the user, regardless of the conversion path.\nIn Conversion & Measurement<\/strong>, last click helps optimize closers; First User Source<\/strong> helps optimize openers.<\/li>\n<\/ul>\n\n\n\n

                                    First User Source vs First Touch Attribution<\/h3>\n\n\n\n

                                    They are closely related, but not always identical:\n– First touch attribution<\/strong> is an attribution model that assigns credit to the first touchpoint in a defined path.\n– First User Source<\/strong> is a user acquisition attribute stored at the user level and used broadly in Analytics<\/strong> for segmentation and cohort analysis.<\/p>\n\n\n\n

                                    \n\n\n\n

                                    Who Should Learn First User Source<\/h2>\n\n\n\n
                                      \n
                                    • Marketers:<\/strong> To invest in channels that create valuable users and justify top-of-funnel spend within Conversion & Measurement<\/strong>.<\/li>\n
                                    • Analysts:<\/strong> To build cohort reporting, improve attribution interpretation, and ensure Analytics<\/strong> answers business questions accurately.<\/li>\n
                                    • Agencies:<\/strong> To demonstrate long-term impact and avoid misleading conclusions from last-click-only reporting.<\/li>\n
                                    • Business owners and founders:<\/strong> To understand which acquisition bets produce durable growth, not just one-time conversions.<\/li>\n
                                    • Developers and data teams:<\/strong> To implement identity, consent, tagging, and data pipelines that keep First User Source<\/strong> reliable and useful.<\/li>\n<\/ul>\n\n\n\n
                                      \n\n\n\n

                                      Summary of First User Source<\/h2>\n\n\n\n

                                      First User Source<\/strong> identifies the original acquisition origin of a user\u2014the channel or source that first introduced them to your brand. It matters because strong Conversion & Measurement<\/strong> requires more than knowing what closed the sale; it requires knowing what created the customer in the first place. Used well, First User Source<\/strong> strengthens cohort analysis, improves budget allocation, and elevates Analytics<\/strong> from reporting clicks to measuring long-term business impact.<\/p>\n\n\n\n

                                      \n\n\n\n

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

                                      1) What does First User Source tell me that other reports don\u2019t?<\/h3>\n\n\n\n

                                      It tells you where a user was originally acquired, which is essential for cohort analysis and understanding which channels create long-term customers\u2014even if conversions happen later via other channels.<\/p>\n\n\n\n

                                      2) Is First User Source the same as \u201cdirect\u201d traffic?<\/h3>\n\n\n\n

                                      No. \u201cDirect\u201d is often a session-level classification. First User Source<\/strong> can be direct if that truly was the first known acquisition, but many users convert on a direct session after being initially acquired elsewhere.<\/p>\n\n\n\n

                                      3) How should I use First User Source in Conversion & Measurement planning?<\/h3>\n\n\n\n

                                      Use it to compare downstream conversion rate, CAC, retention, and LTV by acquisition cohort. That helps you fund channels that create high-quality users, not just quick wins.<\/p>\n\n\n\n

                                      4) Why does my Analytics report show many users with an \u201cunknown\u201d or \u201cdirect\u201d first source?<\/h3>\n\n\n\n

                                      Common causes include missing campaign tags, referrer loss, consent restrictions, cookie deletion, cross-device behavior, and tracking changes. Improving tagging discipline and identity strategies typically reduces this.<\/p>\n\n\n\n

                                      5) Can First User Source change over time?<\/h3>\n\n\n\n

                                      Depending on your setup, it can be designed to remain \u201csticky\u201d (unchanged) or be reset under specific rules (e.g., after long inactivity or after re-consent). Whatever the rule is, document it so Analytics<\/strong> interpretation stays consistent.<\/p>\n\n\n\n

                                      6) What\u2019s the best way to validate First User Source accuracy?<\/h3>\n\n\n\n

                                      Run controlled tests with tagged campaigns, confirm the first recorded acquisition values for new users, and monitor anomalies like sudden spikes in \u201cdirect\/unknown.\u201d Ongoing QA is part of strong Conversion & Measurement<\/strong> hygiene.<\/p>\n\n\n\n

                                      7) Should I optimize campaigns based only on First User Source?<\/h3>\n\n\n\n

                                      Not by itself. Combine First User Source<\/strong> with session performance, incrementality thinking, and downstream quality metrics (retention, revenue, margin). That balanced view is where Analytics<\/strong> delivers the best decisions.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                      In modern **Conversion & Measurement**, it\u2019s not enough to know what caused a conversion today\u2014you also need to understand what originally brought a user into your business. **First User Source** is the concept that captures that original acquisition point, helping teams connect early marketing touchpoints to downstream outcomes like sign-ups, purchases, renewals, and lifetime value.<\/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":[1887],"tags":[],"class_list":["post-6867","post","type-post","status-publish","format-standard","hentry","category-analytics"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/6867","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=6867"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/6867\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=6867"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=6867"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=6867"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}