{"id":8388,"date":"2026-03-26T01:29:01","date_gmt":"2026-03-26T01:29:01","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/referral-dashboard\/"},"modified":"2026-03-26T01:29:01","modified_gmt":"2026-03-26T01:29:01","slug":"referral-dashboard","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/referral-dashboard\/","title":{"rendered":"Referral Dashboard: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Referral Marketing"},"content":{"rendered":"\n

A Referral Dashboard<\/strong> is the centralized reporting and decision-making view that shows how your referral program is performing\u2014who is sharing, who is converting, what incentives are being claimed, and where growth or leakage is happening. In Direct & Retention Marketing<\/strong>, it acts like a control center: it connects customer behavior (sharing and inviting) to business outcomes (new customers, revenue, repeat purchases, and loyalty).<\/p>\n\n\n\n

Because Referral Marketing<\/strong> relies on customers and partners to spread your message, results can change quickly based on offer design, seasonality, channel mix, and fraud pressure. A well-built Referral Dashboard<\/strong> matters because it turns a referral program from a \u201cset it and forget it\u201d widget into an accountable, optimizable growth lever that supports retention, acquisition efficiency, and customer experience.<\/p>\n\n\n\n

What Is Referral Dashboard?<\/h2>\n\n\n\n

A Referral Dashboard<\/strong> is a structured collection of metrics, visualizations, and diagnostic views used to monitor, analyze, and improve a referral program. For beginners, the simplest definition is: a dashboard that tells you how many people shared a referral, how many invites were accepted, how many new customers joined, and what it cost you in incentives.<\/em><\/p>\n\n\n\n

The core concept is visibility with context. It doesn\u2019t just report totals; it helps you answer practical questions such as:<\/p>\n\n\n\n

    \n
  • Which channels drive the highest-quality referred customers?<\/li>\n
  • Are rewards motivating advocates or attracting low-quality signups?<\/li>\n
  • Where do people drop off in the share-to-conversion journey?<\/li>\n<\/ul>\n\n\n\n

    From a business perspective, a Referral Dashboard<\/strong> makes Referral Marketing<\/strong> measurable and manageable. In Direct & Retention Marketing<\/strong>, it supports lifecycle strategy by tying advocacy to retention signals (repeat purchases, churn reduction, customer lifetime value) and by reducing paid media dependence through more efficient customer acquisition.<\/p>\n\n\n\n

    Why Referral Dashboard Matters in Direct & Retention Marketing<\/h2>\n\n\n\n

    In Direct & Retention Marketing<\/strong>, referral programs sit at the intersection of acquisition and loyalty. A Referral Dashboard<\/strong> matters because it creates a feedback loop between customer experience and growth.<\/p>\n\n\n\n

    Key reasons it\u2019s strategically important:<\/p>\n\n\n\n

      \n
    • Protects unit economics:<\/strong> Referral incentives can quietly erode margin if not monitored. A Referral Dashboard<\/strong> helps you track cost per acquisition (CPA) and reward liability in near real time.<\/li>\n
    • Improves retention outcomes:<\/strong> Strong Referral Marketing<\/strong> often correlates with high customer satisfaction and engagement. Dashboards can surface whether advocates are also your best repeat buyers.<\/li>\n
    • Enables faster iteration:<\/strong> You can test reward types, messaging, and placement (post-purchase, account page, onboarding) and see impacts without waiting weeks.<\/li>\n
    • Creates competitive advantage:<\/strong> Many brands run referral programs, but fewer optimize them. A robust Referral Dashboard<\/strong> supports disciplined experimentation and better customer targeting.<\/li>\n<\/ul>\n\n\n\n

      How Referral Dashboard Works<\/h2>\n\n\n\n

      A Referral Dashboard<\/strong> works in practice by connecting program events to customer identity and business outcomes, then turning that data into usable insights. A realistic workflow looks like this:<\/p>\n\n\n\n

        \n
      1. \n

        Input \/ Triggers (data collection)<\/strong>\n – Referral link shares, invite sends, clicks, landing page visits\n – Account creations, purchases, subscriptions, renewals\n – Reward events (issued, pending, approved, revoked)\n – Fraud flags (duplicate identities, suspicious patterns)<\/p>\n<\/li>\n

      2. \n

        Processing (identity + attribution)<\/strong>\n – Matching the referrer (advocate) to the referred user\n – Applying attribution rules (last click vs referral code vs holdout logic)\n – Deduplicating conversions (preventing double-crediting)\n – Validating eligibility (new customer, minimum order, payment success)<\/p>\n<\/li>\n

      3. \n

        Execution (program operations)<\/strong>\n – Reward approval workflows (delayed payout, validation windows)\n – Segmentation (new advocates, power advocates, at-risk advocates)\n – Alerts for spikes in referrals, drops in conversion, or fraud anomalies<\/p>\n<\/li>\n

      4. \n

        Output \/ Outcomes (reporting + decisions)<\/strong>\n – Performance views by channel, cohort, and campaign\n – Profitability reporting and forecasted incentive costs\n – Insights that drive changes to offers, messaging, and placements<\/p>\n<\/li>\n<\/ol>\n\n\n\n

        In Direct & Retention Marketing<\/strong>, the \u201cworks\u201d part is less about charts and more about making referrals operational: accurate attribution, controlled rewards, and actionable insights for growth.<\/p>\n\n\n\n

        Key Components of Referral Dashboard<\/h2>\n\n\n\n

        A high-quality Referral Dashboard<\/strong> typically includes these building blocks:<\/p>\n\n\n\n

        Data inputs and tracking<\/h3>\n\n\n\n
          \n
        • Referral events (share, click, code applied, conversion)<\/li>\n
        • Customer identity data (account IDs, email hashes, device signals where allowed)<\/li>\n
        • Transaction data (order value, subscription status, refunds, chargebacks)<\/li>\n
        • Messaging source (email, SMS, in-app, post-purchase, QR codes)<\/li>\n<\/ul>\n\n\n\n

          Metrics and reporting views<\/h3>\n\n\n\n
            \n
          • Funnel view from share \u2192 click \u2192 signup \u2192 first purchase<\/li>\n
          • Cohort views (by signup month, by advocate segment)<\/li>\n
          • Channel and placement views (where the referral prompt appeared)<\/li>\n<\/ul>\n\n\n\n

            Governance and responsibilities<\/h3>\n\n\n\n
              \n
            • Marketing<\/strong> owns program strategy and tests (offers, creative, placements)<\/li>\n
            • Analytics<\/strong> ensures definitions, attribution logic, and data quality<\/li>\n
            • Engineering<\/strong> maintains instrumentation and integrations<\/li>\n
            • Finance\/Operations<\/strong> monitors reward liability and approval rules<\/li>\n
            • Support<\/strong> uses dashboard insights to resolve reward disputes<\/li>\n<\/ul>\n\n\n\n

              In Referral Marketing<\/strong>, clarity on ownership prevents common issues like mismatched metric definitions or incentive overspend.<\/p>\n\n\n\n

              Types of Referral Dashboard<\/h2>\n\n\n\n

              \u201cReferral Dashboard\u201d doesn\u2019t have rigid formal types, but in real organizations the most useful distinctions are based on audience and purpose:<\/p>\n\n\n\n

                \n
              1. \n

                Executive referral dashboard<\/strong>\n – High-level KPIs: referred revenue, CAC vs paid, LTV, ROI, fraud loss\n – Built for leadership in Direct & Retention Marketing<\/strong> planning<\/p>\n<\/li>\n

              2. \n

                Growth\/marketing optimization dashboard<\/strong>\n – Experiment reporting, channel breakdowns, placement performance\n – Used to iterate on Referral Marketing<\/strong> creatives and incentives<\/p>\n<\/li>\n

              3. \n

                Operational rewards dashboard<\/strong>\n – Pending rewards, approvals, reversals, customer disputes, payout timing\n – Critical for keeping customer trust high<\/p>\n<\/li>\n

              4. \n

                Fraud and compliance dashboard<\/strong>\n – Duplicate patterns, suspicious conversion clusters, self-referrals\n – Protects budget and data integrity<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                Many teams combine these into one Referral Dashboard<\/strong> with role-based views.<\/p>\n\n\n\n

                Real-World Examples of Referral Dashboard<\/h2>\n\n\n\n

                Example 1: E-commerce brand improving post-purchase referrals<\/h3>\n\n\n\n

                An e-commerce team in Direct & Retention Marketing<\/strong> adds a referral prompt to the order confirmation page. Their Referral Dashboard<\/strong> shows high share volume but low conversion. By segmenting the funnel, they find most referred visitors bounce on mobile. They optimize landing speed and simplify the first-order discount redemption. Conversion improves, and Referral Marketing<\/strong> becomes a reliable acquisition channel during peak seasons.<\/p>\n\n\n\n

                Example 2: SaaS company tracking referred trial quality<\/h3>\n\n\n\n

                A SaaS business offers \u201cGive 20%, Get 20%\u201d for referrals. The Referral Dashboard<\/strong> reveals referred trials convert to paid at a higher rate than paid search, but only for referrals from power users. The team creates an in-app referral nudge targeted to highly engaged accounts and delays reward issuance until month two of subscription. This ties Referral Marketing<\/strong> directly to retention, a core Direct & Retention Marketing<\/strong> goal.<\/p>\n\n\n\n

                Example 3: Marketplace balancing growth and fraud control<\/h3>\n\n\n\n

                A marketplace sees a sudden surge in referrals after increasing rewards. The Referral Dashboard<\/strong> fraud view flags abnormal clusters: many referrals share device fingerprints and show low purchase completion. The team tightens eligibility (first purchase must clear return window) and adds velocity limits per advocate. Legitimate Referral Marketing<\/strong> performance remains strong while incentive waste drops.<\/p>\n\n\n\n

                Benefits of Using Referral Dashboard<\/h2>\n\n\n\n

                A well-designed Referral Dashboard<\/strong> delivers benefits beyond reporting:<\/p>\n\n\n\n

                  \n
                • Better performance:<\/strong> Identifies the highest-converting placements, advocates, and offers.<\/li>\n
                • Lower acquisition costs:<\/strong> Helps prove when referrals outperform paid channels on CAC and payback period.<\/li>\n
                • Operational efficiency:<\/strong> Reduces manual reward audits by tracking pending\/approved\/reversed states.<\/li>\n
                • Improved customer experience:<\/strong> Fewer \u201cwhere is my reward?\u201d tickets when statuses are transparent and rules are consistent.<\/li>\n
                • Stronger retention:<\/strong> Surfaces whether advocates are more loyal and how referrals influence repeat purchase behavior\u2014core to Direct & Retention Marketing<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                  Challenges of Referral Dashboard<\/h2>\n\n\n\n

                  Despite the upside, Referral Dashboard<\/strong> implementations often fail for predictable reasons:<\/p>\n\n\n\n

                    \n
                  • Attribution ambiguity:<\/strong> Referrals compete with email, SMS, paid, and organic. Without clear rules, Referral Marketing<\/strong> gets over- or under-credited.<\/li>\n
                  • Identity and deduplication issues:<\/strong> One person can look like multiple users across devices; multiple people can share an IP. Getting \u201cunique\u201d right is hard.<\/li>\n
                  • Reward liability complexity:<\/strong> Rewards may be pending, partially eligible, or reversed due to refunds or cancellations.<\/li>\n
                  • Fraud and gaming:<\/strong> Self-referrals, coupon abuse, and coordinated behavior can inflate results.<\/li>\n
                  • Data latency:<\/strong> If purchase or refund data arrives late, dashboards can mislead decision-making in Direct & Retention Marketing<\/strong> planning.<\/li>\n<\/ul>\n\n\n\n

                    Best Practices for Referral Dashboard<\/h2>\n\n\n\n

                    Use these practices to make a Referral Dashboard<\/strong> reliable and actionable:<\/p>\n\n\n\n

                      \n
                    1. \n

                      Define metrics in writing<\/strong>\n – What counts as a referral conversion?\n – When is a reward \u201cearned\u201d vs \u201cissued\u201d?\n – How do refunds affect referral credit?<\/p>\n<\/li>\n

                    2. \n

                      Build a funnel with clear stages<\/strong>\n – Share \u2192 Click \u2192 Signup \u2192 Qualified conversion \u2192 Reward approval\n – Track drop-offs and time-to-convert by cohort<\/p>\n<\/li>\n

                    3. \n

                      Separate volume from quality<\/strong>\n – Track referred LTV, repeat purchase rate, churn, and refund rate\n – Don\u2019t optimize Referral Marketing<\/strong> only for signups<\/p>\n<\/li>\n

                    4. \n

                      Use holdouts or comparisons where possible<\/strong>\n – Compare referred vs non-referred cohorts\n – Compare placements (post-purchase vs account page) using controlled tests<\/p>\n<\/li>\n

                    5. \n

                      Design for action, not just reporting<\/strong>\n – Add thresholds and alerts (conversion drops, reward spikes, fraud signals)\n – Maintain a \u201cdecision log\u201d so Direct & Retention Marketing<\/strong> learns over time<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                      Tools Used for Referral Dashboard<\/h2>\n\n\n\n

                      A Referral Dashboard<\/strong> typically sits across a small stack rather than one tool. Common tool categories include:<\/p>\n\n\n\n

                        \n
                      • Analytics tools:<\/strong> Event tracking, funnel analysis, cohort reporting, experimentation measurement.<\/li>\n
                      • Customer data platforms (or equivalent pipelines):<\/strong> Identity resolution, event collection, and data routing.<\/li>\n
                      • CRM systems:<\/strong> Customer profiles, segmentation, lifecycle status, and communication history\u2014central to Direct & Retention Marketing<\/strong>.<\/li>\n
                      • Marketing automation tools:<\/strong> Email\/SMS\/in-app orchestration for referral prompts and reward notifications.<\/li>\n
                      • Data warehouse + BI\/reporting dashboards:<\/strong> Source of truth for finance-grade reporting and reconciliations.<\/li>\n
                      • Payment\/subscription systems:<\/strong> Needed to validate \u201cqualified\u201d conversions and handle cancellations\/refunds.<\/li>\n
                      • Fraud detection processes:<\/strong> Rule-based checks and anomaly monitoring to protect Referral Marketing<\/strong> budgets.<\/li>\n<\/ul>\n\n\n\n

                        The key is integration and consistent definitions, not any specific vendor.<\/p>\n\n\n\n

                        Metrics Related to Referral Dashboard<\/h2>\n\n\n\n

                        A practical Referral Dashboard<\/strong> should cover the full funnel, economics, and quality:<\/p>\n\n\n\n

                        Funnel and engagement<\/h3>\n\n\n\n
                          \n
                        • Referral shares \/ invites sent<\/li>\n
                        • Click-through rate (CTR) on referral links<\/li>\n
                        • Signup or lead conversion rate from referred visits<\/li>\n
                        • Time to convert (median days from click to purchase)<\/li>\n<\/ul>\n\n\n\n

                          Acquisition and revenue<\/h3>\n\n\n\n
                            \n
                          • Referred first-purchase conversion rate<\/li>\n
                          • Referred revenue and average order value (AOV)<\/li>\n
                          • Cost per referred acquisition (including incentives and operational costs)<\/li>\n
                          • Payback period compared to other Direct & Retention Marketing<\/strong> channels<\/li>\n<\/ul>\n\n\n\n

                            Retention and quality<\/h3>\n\n\n\n
                              \n
                            • Referred customer lifetime value (LTV)<\/li>\n
                            • Repeat purchase rate \/ renewal rate for referred cohorts<\/li>\n
                            • Refund, cancellation, or chargeback rate for referred customers<\/li>\n
                            • Advocate activation rate (percent of customers who refer at least once)<\/li>\n<\/ul>\n\n\n\n

                              Incentives and risk<\/h3>\n\n\n\n
                                \n
                              • Reward redemption rate<\/li>\n
                              • Reward liability (pending vs approved vs issued)<\/li>\n
                              • Fraud rate or suspicious referral share<\/li>\n
                              • Duplicate referral attempts \/ self-referral rate<\/li>\n<\/ul>\n\n\n\n

                                These metrics make Referral Marketing<\/strong> comparable to other growth initiatives, not a silo.<\/p>\n\n\n\n

                                Future Trends of Referral Dashboard<\/h2>\n\n\n\n

                                Several trends are shaping how a Referral Dashboard<\/strong> evolves within Direct & Retention Marketing<\/strong>:<\/p>\n\n\n\n

                                  \n
                                • AI-assisted anomaly detection:<\/strong> More teams will use automated pattern detection to flag fraud, sudden funnel breaks, and reward abuse earlier.<\/li>\n
                                • More personalization:<\/strong> Dashboards will support offer personalization (different rewards by segment) and measure incremental lift by cohort.<\/li>\n
                                • Privacy-driven measurement changes:<\/strong> As tracking becomes more constrained, first-party events, clean identity practices, and transparent attribution rules become more important.<\/li>\n
                                • Incrementality focus:<\/strong> Leadership will demand evidence that Referral Marketing<\/strong> drives net-new customers, not just reallocating credit from other channels.<\/li>\n
                                • Real-time operations:<\/strong> Faster data pipelines will make reward approvals, alerting, and customer support workflows more responsive.<\/li>\n<\/ul>\n\n\n\n

                                  Referral Dashboard vs Related Terms<\/h2>\n\n\n\n

                                  Referral Dashboard vs Referral Program<\/h3>\n\n\n\n

                                  A referral program is the strategy and mechanics (offers, rules, placements). A Referral Dashboard<\/strong> is how you measure and manage that program. You can have a program without a dashboard, but you can\u2019t sustainably optimize Referral Marketing<\/strong> without measurement.<\/p>\n\n\n\n

                                  Referral Dashboard vs Affiliate Dashboard<\/h3>\n\n\n\n

                                  Affiliate dashboards usually track partners\/publishers, commissions, and paid placements. A Referral Dashboard<\/strong> focuses on customer advocacy and direct sharing. In Direct & Retention Marketing<\/strong>, referral reporting ties more closely to loyalty, customer experience, and lifecycle behavior.<\/p>\n\n\n\n

                                  Referral Dashboard vs Attribution Dashboard<\/h3>\n\n\n\n

                                  An attribution dashboard looks across channels (paid, organic, email, social) to assign credit for conversions. A Referral Dashboard<\/strong> is specialized: it goes deeper on referral mechanics (advocates, reward states, fraud controls). Ideally, they reconcile\u2014so Referral Marketing<\/strong> credit is consistent across both.<\/p>\n\n\n\n

                                  Who Should Learn Referral Dashboard<\/h2>\n\n\n\n

                                  Understanding Referral Dashboard<\/strong> concepts pays off across roles:<\/p>\n\n\n\n

                                    \n
                                  • Marketers:<\/strong> Build better referral offers, placements, and lifecycle messaging in Direct & Retention Marketing<\/strong>.<\/li>\n
                                  • Analysts:<\/strong> Create trustworthy definitions, cohorts, incrementality views, and forecasting for Referral Marketing<\/strong>.<\/li>\n
                                  • Agencies:<\/strong> Deliver measurable referral optimization and communicate results credibly to clients.<\/li>\n
                                  • Business owners\/founders:<\/strong> Monitor unit economics, incentive costs, and sustainable growth beyond paid acquisition.<\/li>\n
                                  • Developers:<\/strong> Implement clean event tracking, identity mapping, and reliable reward logic that makes the dashboard accurate.<\/li>\n<\/ul>\n\n\n\n

                                    Summary of Referral Dashboard<\/h2>\n\n\n\n

                                    A Referral Dashboard<\/strong> is the central view for monitoring and improving referral performance\u2014spanning funnel metrics, incentive economics, retention quality, and fraud risk. It matters because it turns Referral Marketing<\/strong> into an accountable growth channel with clear levers to optimize. In Direct & Retention Marketing<\/strong>, it connects advocacy to lifecycle outcomes like repeat purchase, renewal, and customer lifetime value, enabling faster iteration and smarter budgeting.<\/p>\n\n\n\n

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

                                    1) What should a Referral Dashboard include at minimum?<\/h3>\n\n\n\n

                                    At minimum: shares\/invites, clicks, referred conversions, referred revenue, reward issued vs pending, and conversion rate. If you can add one more layer, include referred LTV or repeat purchase rate to connect Referral Marketing<\/strong> to Direct & Retention Marketing<\/strong> outcomes.<\/p>\n\n\n\n

                                    2) How do I know if Referral Marketing is actually driving incremental growth?<\/h3>\n\n\n\n

                                    Use comparisons such as holdout groups, time-boxed tests on placements, or cohort comparisons between referred and non-referred customers. Your Referral Dashboard<\/strong> should separate \u201ccredited\u201d conversions from \u201cincremental\u201d lift where possible.<\/p>\n\n\n\n

                                    3) What\u2019s the difference between referred conversions and referred customers?<\/h3>\n\n\n\n

                                    \u201cReferred conversions\u201d are the successful actions credited to a referral (signup, purchase). \u201cReferred customers\u201d are unique individuals who became customers via referral. A Referral Dashboard<\/strong> should track both to avoid double-counting.<\/p>\n\n\n\n

                                    4) How often should I review a Referral Dashboard?<\/h3>\n\n\n\n

                                    For active programs: weekly for optimization and monthly for executive reporting. In high-volume businesses or when incentives change, daily monitoring helps catch fraud and funnel breaks quickly\u2014especially within Direct & Retention Marketing<\/strong> operations.<\/p>\n\n\n\n

                                    5) Why do referral numbers differ between my Referral Dashboard and my analytics reports?<\/h3>\n\n\n\n

                                    Differences usually come from attribution rules, deduplication, identity resolution, and timing (refunds or cancellations arriving later). Align definitions and ensure your Referral Dashboard<\/strong> uses the same \u201csource of truth\u201d events as finance-grade reporting.<\/p>\n\n\n\n

                                    6) What are the most common metrics mistakes in referral reporting?<\/h3>\n\n\n\n

                                    Common mistakes include counting signups instead of qualified purchases, ignoring refunds\/chargebacks, optimizing for volume over quality, and failing to track reward liability. These errors can make Referral Marketing<\/strong> look profitable when it isn\u2019t, or hide what\u2019s actually working.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                    A **Referral Dashboard** is the centralized reporting and decision-making view that shows how your referral program is performing\u2014who is sharing, who is converting, what incentives are being claimed, and where growth or leakage is happening. In **Direct & Retention Marketing**, it acts like a control center: it connects customer behavior (sharing and inviting) to business outcomes (new customers, revenue, repeat purchases, and loyalty).<\/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":[1896],"tags":[],"class_list":["post-8388","post","type-post","status-publish","format-standard","hentry","category-referral-marketing"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/8388","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=8388"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/8388\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=8388"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=8388"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=8388"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}