{"id":10711,"date":"2026-03-29T20:08:12","date_gmt":"2026-03-29T20:08:12","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/cross-device-frequency\/"},"modified":"2026-03-29T20:08:12","modified_gmt":"2026-03-29T20:08:12","slug":"cross-device-frequency","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/cross-device-frequency\/","title":{"rendered":"Cross-device Frequency: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Programmatic Advertising"},"content":{"rendered":"\n

Modern consumers don\u2019t stay on one screen. They browse on a phone during a commute, compare options on a laptop at work, and finally purchase on a tablet or connected TV at night. Cross-device Frequency<\/strong> is the practice of measuring and controlling how often the same person (or household) sees your ads across multiple devices and environments. In Paid Marketing<\/strong>, it\u2019s a critical lever for improving efficiency, avoiding ad fatigue, and delivering a more consistent customer experience.<\/p>\n\n\n\n

In Programmatic Advertising<\/strong>, where impressions are bought and optimized at scale, frequency management can easily become fragmented by device, browser, and app. Cross-device Frequency<\/strong> helps unify exposure across these touchpoints so you can cap, pace, and optimize messaging based on total exposure\u2014not just exposure on a single device.<\/p>\n\n\n\n

2. What Is Cross-device Frequency?<\/h2>\n\n\n\n

Cross-device Frequency<\/strong> is the total number of ad exposures attributed to the same user (or household) across multiple devices, browsers, and apps over a defined time window. Instead of treating a mobile user and a desktop user as two separate people, it attempts to recognize them as one and sum impressions accordingly.<\/p>\n\n\n\n

At its core, it answers a simple business question: \u201cHow many times did we reach the same person across all screens?\u201d<\/strong> That business meaning matters because most budgets are wasted not by \u201ctoo little reach,\u201d but by too much repeated exposure to the same people<\/strong> while others never see the ad.<\/p>\n\n\n\n

In Paid Marketing<\/strong>, frequency is one of the most important control knobs alongside targeting, bidding, and creative. Within Programmatic Advertising<\/strong>, it influences how DSPs bid, how ad servers prioritize delivery, and how audiences are sequenced across channels (display, video, CTV, audio, in-app, and more).<\/p>\n\n\n\n

3. Why Cross-device Frequency Matters in Paid Marketing<\/h2>\n\n\n\n

When frequency is measured per device, you can unintentionally overexpose high-intent users who use multiple devices\u2014while thinking you are \u201cefficiently scaling.\u201d Cross-device Frequency<\/strong> matters because it aligns media delivery with real human exposure.<\/p>\n\n\n\n

Key reasons it\u2019s strategically important in Paid Marketing<\/strong>:<\/p>\n\n\n\n

    \n
  • Prevents waste and saturation:<\/strong> Without a unified view, frequency caps are too weak, causing redundant impressions across devices.<\/li>\n
  • Improves conversion efficiency:<\/strong> Many campaigns have an optimal frequency range; beyond it, incremental conversions flatten while costs continue.<\/li>\n
  • Supports sequential messaging:<\/strong> You can move users from awareness to consideration to action without repeating the same creative everywhere.<\/li>\n
  • Protects brand experience:<\/strong> Repetitive ads can feel invasive or annoying, especially when they \u201cfollow\u201d people across screens.<\/li>\n
  • Creates competitive advantage:<\/strong> Teams that control frequency well often get better ROAS at the same CPM because they reduce low-value repeat impressions.<\/li>\n<\/ul>\n\n\n\n

    In Programmatic Advertising<\/strong>, these gains compound because even small efficiency improvements applied across millions of impressions can materially shift outcomes.<\/p>\n\n\n\n

    4. How Cross-device Frequency Works<\/h2>\n\n\n\n

    Cross-device Frequency<\/strong> is partly measurement and partly control. In practice, it usually follows this workflow:<\/p>\n\n\n\n

      \n
    1. \n

      Input \/ trigger: ad exposure events<\/strong>\n Each impression, view, or served ad generates event data (timestamp, placement, device\/app context, and an identifier of some kind).<\/p>\n<\/li>\n

    2. \n

      Analysis \/ processing: identity and deduplication<\/strong>\n Systems attempt to map different identifiers (cookies, mobile ad IDs, logged-in IDs, hashed emails, publisher IDs) to a single user or household. This is where \u201ccross-device\u201d recognition happens and where deduplication rules are applied.<\/p>\n<\/li>\n

    3. \n

      Execution \/ application: frequency rules and decisioning<\/strong>\n Frequency caps, pacing rules, and sequencing logic are enforced in buying platforms, ad servers, or intermediary decisioning layers. For example: \u201cNo more than 5 impressions per user in 7 days across all devices.\u201d<\/p>\n<\/li>\n

    4. \n

      Output \/ outcome: controlled delivery + reporting<\/strong>\n Delivery changes (fewer redundant impressions, different creative rotation, shifted spend), and reporting reflects frequency distributions, reach, and performance by exposure level.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

      Because identity is never perfect, Cross-device Frequency<\/strong> is best treated as a probabilistic control lever with measured confidence\u2014not a flawless count of every impression.<\/p>\n\n\n\n

      5. Key Components of Cross-device Frequency<\/h2>\n\n\n\n

      Successfully managing Cross-device Frequency<\/strong> in Paid Marketing<\/strong> requires more than a single platform setting. The major components include:<\/p>\n\n\n\n

      Identity and matching layer<\/h3>\n\n\n\n

      A way to connect exposures across devices, such as deterministic matching (login-based) or probabilistic modeling (pattern-based). This is often the \u201cengine\u201d behind cross-device measurement.<\/p>\n\n\n\n

      Ad decisioning and delivery controls<\/h3>\n\n\n\n

      Frequency capping and pacing can live in DSPs, ad servers, or campaign orchestration tools. In Programmatic Advertising<\/strong>, you often need to align settings across multiple buying paths to avoid loopholes.<\/p>\n\n\n\n

      Data inputs and governance<\/h3>\n\n\n\n
        \n
      • Consent signals and privacy preferences <\/li>\n
      • First-party IDs (where available) <\/li>\n
      • Campaign metadata (flight dates, creative versions, channels) <\/li>\n
      • Clear definitions for \u201cuser\u201d vs \u201chousehold\u201d and \u201cimpression\u201d vs \u201cviewable impression\u201d<\/li>\n<\/ul>\n\n\n\n

        Reporting and measurement framework<\/h3>\n\n\n\n

        Dashboards that show frequency distribution, deduplicated reach, and outcomes by exposure level\u2014so teams can optimize rather than guess.<\/p>\n\n\n\n

        Team responsibilities<\/h3>\n\n\n\n

        Cross-device control usually spans multiple owners: media buying, analytics, ad ops, privacy\/legal, and sometimes engineering. Clear ownership prevents \u201cfrequency drift\u201d where caps exist in theory but not in practice.<\/p>\n\n\n\n

        6. Types of Cross-device Frequency<\/h2>\n\n\n\n

        There aren\u2019t universal \u201cofficial\u201d types, but there are practical distinctions that matter:<\/p>\n\n\n\n

        Deterministic vs probabilistic cross-device frequency<\/h3>\n\n\n\n
          \n
        • Deterministic:<\/strong> Based on strong signals like login IDs or authenticated publisher IDs. More accurate, but limited to logged-in environments.<\/li>\n
        • Probabilistic:<\/strong> Uses models to infer connections (device graphs). Broader reach, but introduces uncertainty and requires careful validation.<\/li>\n<\/ul>\n\n\n\n

          Person-level vs household-level frequency<\/h3>\n\n\n\n
            \n
          • Person-level<\/strong> aims to control exposure per individual. <\/li>\n
          • Household-level<\/strong> is common in CTV and shared-device environments, but can over-cap if multiple people share a screen.<\/li>\n<\/ul>\n\n\n\n

            Measurement-only vs enforcement<\/h3>\n\n\n\n
              \n
            • Measurement-only<\/strong> means you can report Cross-device Frequency<\/strong> after the fact. <\/li>\n
            • Enforcement<\/strong> means you can actually cap or pace delivery based on total exposure in near real time. Enforcement is harder but more valuable in Paid Marketing<\/strong> operations.<\/li>\n<\/ul>\n\n\n\n

              Channel-limited vs omnichannel<\/h3>\n\n\n\n

              Some setups manage frequency across display and video but exclude walled-garden environments or certain apps. Understanding what\u2019s included is essential to interpreting results.<\/p>\n\n\n\n

              7. Real-World Examples of Cross-device Frequency<\/h2>\n\n\n\n

              Example 1: E-commerce retargeting across mobile and desktop<\/h3>\n\n\n\n

              A retailer runs dynamic retargeting. Users browse products on mobile but purchase on desktop. Without Cross-device Frequency<\/strong>, the user may see 8 ads on mobile and 8 on desktop\u201416 total exposures\u2014causing fatigue and wasted spend. With cross-device caps, the team limits total exposure to, say, 6\u20138 per week, reallocating budget to incremental reach and improving ROAS in Paid Marketing<\/strong>.<\/p>\n\n\n\n

              Example 2: B2B SaaS awareness + consideration sequencing<\/h3>\n\n\n\n

              A SaaS brand uses Programmatic Advertising<\/strong> for awareness video, then follow-up display with proof points, then a demo CTA. Cross-device Frequency<\/strong> enables sequencing rules like: \u201cAfter 2 video exposures, switch to consideration creative, regardless of device.\u201d This reduces repetitive top-funnel messaging and increases qualified site visits.<\/p>\n\n\n\n

              Example 3: CTV campaign with mobile support<\/h3>\n\n\n\n

              A brand runs CTV ads and supports them with mobile display for recall and site traffic. Household exposure on CTV plus individual exposure on mobile can easily double-count. Cross-device reporting helps the team understand true deduplicated reach and manage total exposure, improving brand lift efficiency without overspending.<\/p>\n\n\n\n

              8. Benefits of Using Cross-device Frequency<\/h2>\n\n\n\n

              When implemented well, Cross-device Frequency<\/strong> can produce measurable improvements:<\/p>\n\n\n\n

                \n
              • Higher media efficiency:<\/strong> Fewer redundant impressions to the same people, more spend allocated to incremental reach.<\/li>\n
              • Lower effective CPA \/ higher ROAS:<\/strong> By staying closer to optimal exposure levels, you avoid paying for low-increment impressions.<\/li>\n
              • Better creative performance:<\/strong> Sequencing and rotation reduce fatigue and allow messages to match intent stage.<\/li>\n
              • Improved audience experience:<\/strong> Users see fewer repetitive ads across screens, which supports brand trust.<\/li>\n
              • Cleaner learning loops:<\/strong> In Programmatic Advertising<\/strong>, better frequency data improves optimization signals and reduces misleading conclusions.<\/li>\n<\/ul>\n\n\n\n

                9. Challenges of Cross-device Frequency<\/h2>\n\n\n\n

                Despite its value, Cross-device Frequency<\/strong> is hard in real-world Paid Marketing<\/strong> for several reasons:<\/p>\n\n\n\n

                  \n
                • Identity fragmentation:<\/strong> Cookies, mobile ad IDs, and publisher identifiers don\u2019t naturally unify. Cross-device graphs vary in quality.<\/li>\n
                • Privacy and consent constraints:<\/strong> Opt-outs, consent rules, and regional regulations can limit what can be matched and stored.<\/li>\n
                • Walled gardens and data silos:<\/strong> Some platforms restrict cross-platform user-level measurement, making true omnichannel frequency difficult.<\/li>\n
                • Latency and real-time enforcement:<\/strong> Reporting may be delayed, so \u201ccaps\u201d can be exceeded before updates propagate.<\/li>\n
                • Definition disputes:<\/strong> Teams may disagree on whether to cap by person vs household, what time window to use, and whether viewability matters.<\/li>\n
                • Attribution bias:<\/strong> Overexposed users are often more likely to convert anyway; without careful analysis, frequency can be wrongly credited for performance.<\/li>\n<\/ul>\n\n\n\n

                  10. Best Practices for Cross-device Frequency<\/h2>\n\n\n\n

                  Actionable ways to improve Cross-device Frequency<\/strong> outcomes:<\/p>\n\n\n\n

                  Start with clear objectives<\/h3>\n\n\n\n

                  Decide whether the priority is:\n– protecting user experience,\n– maximizing incremental reach,\n– improving conversion efficiency,\n– enabling sequential storytelling.<\/p>\n\n\n\n

                  Different goals imply different caps and windows.<\/p>\n\n\n\n

                  Use frequency distribution, not just averages<\/h3>\n\n\n\n

                  Average frequency can hide problems. Monitor how many users fall into 1\u20132, 3\u20135, 6\u201310, and 10+ exposure buckets and how performance changes across buckets.<\/p>\n\n\n\n

                  Align caps with funnel stage and channel<\/h3>\n\n\n\n

                  Prospecting often benefits from lower caps; retargeting may tolerate higher caps (within reason). In Programmatic Advertising<\/strong>, apply caps thoughtfully per tactic and ensure they add up to a sensible cross-device total.<\/p>\n\n\n\n

                  Treat identity confidence as a variable<\/h3>\n\n\n\n

                  If your cross-device matching is partly probabilistic, avoid overly strict caps that might under-deliver. Use testing to find safe ranges.<\/p>\n\n\n\n

                  Coordinate creative sequencing<\/h3>\n\n\n\n

                  Map exposure thresholds to creative changes (e.g., after 2 impressions show a new angle). This can outperform hard caps alone in Paid Marketing<\/strong>.<\/p>\n\n\n\n

                  Validate with experiments<\/h3>\n\n\n\n

                  Use holdouts or split tests where feasible: different caps, windows, or sequencing rules. Evaluate incremental lift, not just last-click outcomes.<\/p>\n\n\n\n

                  11. Tools Used for Cross-device Frequency<\/h2>\n\n\n\n

                  There isn\u2019t one \u201cCross-device Frequency tool.\u201d It\u2019s usually a stack:<\/p>\n\n\n\n

                    \n
                  • Ad platforms (DSPs) and buying tools:<\/strong> Set frequency caps, pacing, and sometimes cross-device constraints within their identity frameworks.<\/li>\n
                  • Ad servers and ad ops systems:<\/strong> Manage delivery rules, creative rotation, and reporting consistency.<\/li>\n
                  • Identity resolution and first-party data systems:<\/strong> CDPs, identity graphs, and authenticated ID frameworks that help unify users across devices.<\/li>\n
                  • Analytics tools and measurement frameworks:<\/strong> Web\/app analytics, conversion APIs, and incrementality testing to connect frequency to outcomes.<\/li>\n
                  • Privacy and consent management systems:<\/strong> Ensure frequency measurement aligns with consent choices and governance.<\/li>\n
                  • Reporting dashboards \/ BI:<\/strong> Centralize frequency distributions, deduped reach, and performance by exposure across Paid Marketing<\/strong> channels.<\/li>\n<\/ul>\n\n\n\n

                    In Programmatic Advertising<\/strong>, the key is interoperability: frequency controls are only as good as the identifiers and data flows that connect platforms.<\/p>\n\n\n\n

                    12. Metrics Related to Cross-device Frequency<\/h2>\n\n\n\n

                    To manage Cross-device Frequency<\/strong> effectively, track metrics that reveal both exposure and impact:<\/p>\n\n\n\n

                      \n
                    • Deduplicated reach:<\/strong> Unique people\/households reached across devices (as best as measurable).<\/li>\n
                    • Average frequency:<\/strong> Total impressions divided by deduped reach (use cautiously).<\/li>\n
                    • Frequency distribution:<\/strong> Percent of audience at each exposure level (most actionable).<\/li>\n
                    • Impressions per unique user (cross-device):<\/strong> A more explicit framing than \u201cfrequency.\u201d<\/li>\n
                    • Incremental reach:<\/strong> New unique users reached when adding channels\/devices.<\/li>\n
                    • Conversion rate by frequency bucket:<\/strong> Helps locate diminishing returns.<\/li>\n
                    • CPA\/ROAS by frequency bucket:<\/strong> Shows where spend becomes inefficient.<\/li>\n
                    • Viewable frequency (where available):<\/strong> Exposure adjusted to viewability, useful for brand outcomes.<\/li>\n
                    • Brand lift or recall by frequency (if measured):<\/strong> Helps define \u201ceffective frequency\u201d for awareness goals.<\/li>\n<\/ul>\n\n\n\n

                      13. Future Trends of Cross-device Frequency<\/h2>\n\n\n\n

                      Several trends are reshaping Cross-device Frequency<\/strong> in Paid Marketing<\/strong>:<\/p>\n\n\n\n

                        \n
                      • Privacy-driven identity shifts:<\/strong> As identifiers change, cross-device measurement relies more on consented first-party signals and privacy-preserving approaches.<\/li>\n
                      • Clean rooms and aggregated measurement:<\/strong> More analysis may happen in controlled environments with limited user-level outputs, changing how frequency is estimated and activated.<\/li>\n
                      • AI-assisted optimization:<\/strong> Machine learning will increasingly recommend frequency caps and sequencing based on predicted fatigue, incremental lift, and creative response curves.<\/li>\n
                      • Better omnichannel coordination:<\/strong> Advertisers will push for unified planning across CTV, digital video, display, and retail media\u2014forcing clearer definitions of cross-device reach and exposure.<\/li>\n
                      • Creative personalization with guardrails:<\/strong> Dynamic creative will adapt per user, but Cross-device Frequency<\/strong> will remain essential to prevent overexposure even with varied ads.<\/li>\n<\/ul>\n\n\n\n

                        In Programmatic Advertising<\/strong>, the winners will be teams that combine privacy-safe identity, disciplined measurement, and practical activation.<\/p>\n\n\n\n

                        14. Cross-device Frequency vs Related Terms<\/h2>\n\n\n\n

                        Cross-device Frequency vs frequency capping<\/h3>\n\n\n\n

                        Frequency capping<\/strong> is the rule (\u201cno more than X impressions per Y time\u201d). Cross-device Frequency<\/strong> is the measurement and control of that exposure across devices<\/strong>, not just within one browser or app.<\/p>\n\n\n\n

                        Cross-device Frequency vs deduplicated reach<\/h3>\n\n\n\n

                        Deduplicated reach<\/strong> focuses on how many unique people<\/em> you reached across platforms. Cross-device Frequency<\/strong> focuses on how often those people<\/em> were exposed across platforms. You typically need both to manage waste and scale.<\/p>\n\n\n\n

                        Cross-device Frequency vs cross-device attribution<\/h3>\n\n\n\n

                        Cross-device attribution<\/strong> tries to assign credit for conversions across devices and touchpoints. Cross-device Frequency<\/strong> is about managing exposure levels. Attribution might tell you \u201cwhat drove the conversion,\u201d while frequency tells you \u201chow much is too much.\u201d<\/p>\n\n\n\n

                        15. Who Should Learn Cross-device Frequency<\/h2>\n\n\n\n

                        Cross-device Frequency<\/strong> is useful across roles:<\/p>\n\n\n\n

                          \n
                        • Marketers:<\/strong> To set smarter caps, improve sequencing, and protect brand experience in Paid Marketing<\/strong>.<\/li>\n
                        • Analysts:<\/strong> To interpret performance correctly and avoid misleading conclusions caused by device-level double counting.<\/li>\n
                        • Agencies:<\/strong> To coordinate settings across platforms and prove efficiency gains to clients.<\/li>\n
                        • Business owners and founders:<\/strong> To understand why spend can rise without proportional growth, especially in Programmatic Advertising<\/strong>.<\/li>\n
                        • Developers and marketing engineers:<\/strong> To implement identity-safe data pipelines, event collection, and reporting that make cross-device control possible.<\/li>\n<\/ul>\n\n\n\n

                          16. Summary of Cross-device Frequency<\/h2>\n\n\n\n

                          Cross-device Frequency<\/strong> measures and manages how often the same person or household sees ads across multiple devices and environments. It matters because modern journeys span screens, and device-level frequency caps can cause overexposure, wasted spend, and poor user experience. In Paid Marketing<\/strong>, it supports better efficiency, sequencing, and audience management. In Programmatic Advertising<\/strong>, it becomes a powerful optimization lever\u2014when identity, governance, and reporting are aligned.<\/p>\n\n\n\n

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

                          1) What is Cross-device Frequency in simple terms?<\/h3>\n\n\n\n

                          It\u2019s the total number of times a person (or household) sees your ads across different devices\u2014like mobile, desktop, tablet, and connected TV\u2014within a set time period.<\/p>\n\n\n\n

                          2) How is Cross-device Frequency different from standard frequency?<\/h3>\n\n\n\n

                          Standard frequency is often calculated per device or per identifier (like a browser cookie). Cross-device Frequency<\/strong> attempts to unify those exposures so you can understand and control total exposure across screens.<\/p>\n\n\n\n

                          3) Does Cross-device Frequency always improve performance?<\/h3>\n\n\n\n

                          Not automatically. It improves performance when you use it to reduce waste, prevent fatigue, and shift budget toward incremental reach or better sequencing. Poor identity matching or overly strict caps can also reduce delivery and learning.<\/p>\n\n\n\n

                          4) What frequency cap should I use in Paid Marketing?<\/h3>\n\n\n\n

                          There\u2019s no universal number. Caps depend on funnel stage, purchase cycle, and creative variety. A practical approach is to test multiple caps, analyze frequency buckets, and optimize toward incremental lift rather than clicks alone.<\/p>\n\n\n\n

                          5) Why is Cross-device Frequency hard in Programmatic Advertising?<\/h3>\n\n\n\n

                          Because identity is fragmented across cookies, mobile ad IDs, apps, and publisher systems\u2014and some platforms limit user-level sharing. That makes it difficult to deduplicate reach and enforce one cap everywhere.<\/p>\n\n\n\n

                          6) Can I measure Cross-device Frequency without being able to enforce it?<\/h3>\n\n\n\n

                          Yes. Many teams start with cross-device reporting (measurement-only) to understand exposure and inefficiency, then add enforcement where platforms and identifiers allow.<\/p>\n\n\n\n

                          7) What\u2019s the biggest mistake teams make with cross-device frequency?<\/h3>\n\n\n\n

                          Relying on averages. Average frequency can look fine while a meaningful share of the audience is being hammered with 10\u201320+ exposures across devices. Always review frequency distributions and outcomes by bucket.<\/p>\n","protected":false},"excerpt":{"rendered":"

                          Modern consumers don\u2019t stay on one screen. They browse on a phone during a commute, compare options on a laptop at work, and finally purchase on a tablet or connected TV at night. **Cross-device Frequency** is the practice of measuring and controlling how often the same person (or household) sees your ads across multiple devices and environments. In **Paid Marketing**, it\u2019s a critical lever for improving efficiency, avoiding ad fatigue, and delivering a more consistent customer experience.<\/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":[1911],"tags":[],"class_list":["post-10711","post","type-post","status-publish","format-standard","hentry","category-programmatic-advertising"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/10711","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=10711"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/10711\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=10711"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=10711"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=10711"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}