{"id":7669,"date":"2026-03-24T22:00:27","date_gmt":"2026-03-24T22:00:27","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/customer-data-platform\/"},"modified":"2026-03-24T22:00:27","modified_gmt":"2026-03-24T22:00:27","slug":"customer-data-platform","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/customer-data-platform\/","title":{"rendered":"Customer Data Platform: What It Is, Key Features, Benefits, Use Cases, and How It Fits in CRM Marketing"},"content":{"rendered":"\n

A Customer Data Platform<\/strong> is the system many modern teams rely on to turn scattered customer signals\u2014web visits, app events, purchases, support tickets, email engagement\u2014into a usable, consent-aware customer view. In Direct & Retention Marketing<\/strong>, that \u201cusable\u201d part is everything: if you can\u2019t confidently identify people, understand their lifecycle stage, and activate relevant messages, retention programs become guesswork.<\/p>\n\n\n\n

In CRM Marketing<\/strong>, a Customer Data Platform often sits between data collection and campaign execution. It helps ensure that the segments you build (and the journeys you trigger) reflect real customer behavior across channels\u2014not just what happened in one tool. As privacy expectations rise and customer journeys become more multi-touch, a Customer Data Platform has become a foundational capability for teams that want personalization without chaos.<\/p>\n\n\n\n

What Is Customer Data Platform?<\/h2>\n\n\n\n

A Customer Data Platform (CDP)<\/strong> is a software system designed to collect<\/strong>, unify<\/strong>, and activate<\/strong> first-party customer data from multiple sources into persistent customer profiles that can be used for marketing, analytics, and customer experience.<\/p>\n\n\n\n

The core concept is simple: instead of each channel (email, mobile, web, support, retail) maintaining its own partial truth, the Customer Data Platform creates a shared, continuously updated profile<\/strong> that teams can segment and use for targeting.<\/p>\n\n\n\n

From a business perspective, a Customer Data Platform is less about \u201cstoring data\u201d and more about operationalizing customer understanding<\/strong>. In Direct & Retention Marketing<\/strong>, that means orchestrating timely lifecycle messages, controlling frequency across channels, and measuring incremental impact with cleaner inputs. Inside CRM Marketing<\/strong>, it typically improves segmentation quality, personalization depth, and audience governance\u2014so campaigns are both more relevant and more compliant.<\/p>\n\n\n\n

Why Customer Data Platform Matters in Direct & Retention Marketing<\/h2>\n\n\n\n

Direct & Retention Marketing<\/strong> succeeds when it responds to customer behavior quickly and consistently. A Customer Data Platform matters because it reduces the common blockers that derail retention programs:<\/p>\n\n\n\n

    \n
  • Fragmented identity<\/strong>: one person looks like five \u201ccustomers\u201d across devices and systems.<\/li>\n
  • Inconsistent segmentation<\/strong>: different teams define \u201cactive,\u201d \u201cchurn risk,\u201d or \u201cVIP\u201d differently.<\/li>\n
  • Slow execution<\/strong>: campaigns lag because data needs manual exports and transformations.<\/li>\n
  • Measurement noise<\/strong>: attribution and lift analysis suffer when data is incomplete or duplicated.<\/li>\n<\/ul>\n\n\n\n

    The strategic value is competitive: companies that use a Customer Data Platform well can run more precise lifecycle programs (onboarding, upsell, renewal, win-back), learn faster, and waste less budget on irrelevant messaging. In CRM Marketing<\/strong>, the advantage shows up as better list hygiene, better personalization, and fewer conflicts between email, SMS, push, and paid retargeting.<\/p>\n\n\n\n

    How Customer Data Platform Works<\/h2>\n\n\n\n

    A Customer Data Platform is easiest to understand as a workflow that turns raw signals into activated audiences.<\/p>\n\n\n\n

    1) Inputs (collection and ingestion)<\/h3>\n\n\n\n

    Data enters the Customer Data Platform from sources such as:\n– Websites and apps (events like product views, searches, add-to-cart)\n– Transaction systems (orders, subscriptions, refunds)\n– CRM records (lead\/account\/contact attributes)\n– Customer support systems (tickets, satisfaction ratings)\n– Email\/SMS\/push engagement (opens, clicks, sends, unsubscribes)<\/p>\n\n\n\n

    In Direct & Retention Marketing<\/strong>, the quality of these inputs determines how reliably you can trigger lifecycle messaging.<\/p>\n\n\n\n

    2) Processing (unification and identity resolution)<\/h3>\n\n\n\n

    The platform standardizes events and attributes, then performs identity resolution<\/strong> to connect identifiers (email, phone, customer ID, device IDs, cookies where applicable) into a single profile. This step is where many retention programs either become powerful\u2014or remain siloed.<\/p>\n\n\n\n

    In CRM Marketing<\/strong>, this is what enables consistent segmentation across systems without endless spreadsheet reconciliation.<\/p>\n\n\n\n

    3) Execution (segmentation and activation)<\/h3>\n\n\n\n

    Teams create audiences (segments) using behavior, attributes, and calculated traits (for example, \u201chigh intent,\u201d \u201clikely to churn,\u201d or \u201crepeat buyer\u201d). The Customer Data Platform then syncs those audiences and profile attributes to downstream tools for messaging, experimentation, and analytics.<\/p>\n\n\n\n

    4) Outputs (outcomes and learning loop)<\/h3>\n\n\n\n

    The outputs are both operational and analytical:\n– Campaign triggers and journeys run with better targeting\n– Frequency and suppression rules become consistent across channels\n– Reporting improves because segments map to clear definitions\n– Learnings feed back into new rules, models, and experiments<\/p>\n\n\n\n

    This loop is why a Customer Data Platform becomes central to scalable Direct & Retention Marketing<\/strong>.<\/p>\n\n\n\n

    Key Components of Customer Data Platform<\/h2>\n\n\n\n

    While implementations vary, most Customer Data Platform setups include these core elements:<\/p>\n\n\n\n

    Data collection and connectors<\/h3>\n\n\n\n

    SDKs, APIs, and integrations bring data in from web, apps, CRM systems, and transactional databases. Strong connector coverage reduces engineering effort and lowers activation latency for CRM Marketing<\/strong> programs.<\/p>\n\n\n\n

    Identity resolution and profile stitching<\/h3>\n\n\n\n

    Rules and logic reconcile identifiers into persistent profiles. This includes merge rules, conflict handling, and support for householding or account-based relationships when relevant.<\/p>\n\n\n\n

    Profile store and event history<\/h3>\n\n\n\n

    A persistent store holds customer attributes plus behavioral timelines. This supports lifecycle logic like \u201cfirst purchase date,\u201d \u201cdays since last active,\u201d or \u201clast category browsed,\u201d which are essential to Direct & Retention Marketing<\/strong> triggers.<\/p>\n\n\n\n

    Segmentation and audience building<\/h3>\n\n\n\n

    A UI (and often APIs) for defining segments using events, properties, and computed fields. Good segmentation tooling reduces dependency on analysts for everyday targeting.<\/p>\n\n\n\n

    Activation and downstream sync<\/h3>\n\n\n\n

    The ability to push segments and attributes to email, SMS, push notification tools, ad platforms, onsite personalization systems, and analytics tools\u2014without manual exports.<\/p>\n\n\n\n

    Governance, privacy, and consent<\/h3>\n\n\n\n

    Consent flags, data retention rules, access controls, and audit trails. In CRM Marketing<\/strong>, governance is what keeps personalization aligned with policy and customer expectations.<\/p>\n\n\n\n

    Data quality and monitoring<\/h3>\n\n\n\n

    Validation, schema management, duplicate handling, and pipeline alerts. Retention campaigns fail quietly when tracking breaks; monitoring prevents that.<\/p>\n\n\n\n

    Types of Customer Data Platform<\/h2>\n\n\n\n

    \u201cTypes\u201d of Customer Data Platform usually refer to architecture and emphasis rather than formal categories:<\/p>\n\n\n\n

    Packaged vs composable<\/h3>\n\n\n\n
      \n
    • Packaged CDP<\/strong>: an all-in-one system that handles collection, unification, segmentation, and activation within one product.<\/li>\n
    • Composable CDP<\/strong>: a modular approach that combines a warehouse\/lake, identity tooling, transformation layers, and activation connectors.<\/li>\n<\/ul>\n\n\n\n

      For Direct & Retention Marketing<\/strong>, packaged systems often speed time-to-value; composable approaches can offer more flexibility and stronger data ownership.<\/p>\n\n\n\n

      Real-time vs batch-oriented<\/h3>\n\n\n\n

      Some Customer Data Platform implementations support near-real-time event streaming for triggers (for example, browse abandonment). Others operate on scheduled batches, which may be sufficient for weekly lifecycle campaigns but limiting for immediate interventions.<\/p>\n\n\n\n

      Activation-focused vs analytics-focused<\/h3>\n\n\n\n

      Certain platforms prioritize audience activation and journey triggers; others emphasize data modeling, analysis, and governance. Strong CRM Marketing<\/strong> teams typically need both\u2014activation for execution and analytics for measurement.<\/p>\n\n\n\n

      Real-World Examples of Customer Data Platform<\/h2>\n\n\n\n

      Example 1: Ecommerce lifecycle and frequency control<\/h3>\n\n\n\n

      An ecommerce brand uses a Customer Data Platform to unify browsing events, purchase history, and email\/SMS engagement. The retention team builds segments like \u201cviewed product twice in 7 days,\u201d \u201cfirst-time buyer,\u201d and \u201chigh-return-risk.\u201d They apply suppression rules so customers don\u2019t receive overlapping offers across channels.<\/p>\n\n\n\n

      Result: Direct & Retention Marketing<\/strong> becomes more coordinated, reducing unsubscribes while improving repeat purchase rate\u2014core CRM Marketing<\/strong> outcomes.<\/p>\n\n\n\n

      Example 2: Subscription churn prevention<\/h3>\n\n\n\n

      A subscription service streams in app usage, billing status, and support interactions. The Customer Data Platform computes \u201cdays since last meaningful action\u201d and \u201crecent ticket severity,\u201d then triggers a save journey: educational content first, then a targeted incentive only if engagement doesn\u2019t recover.<\/p>\n\n\n\n

      Result: the team avoids discounting everyone, improving retention margin while keeping CRM Marketing<\/strong> segmentation consistent.<\/p>\n\n\n\n

      Example 3: B2B SaaS trial nurture and handoff<\/h3>\n\n\n\n

      A B2B SaaS company unifies product telemetry (feature usage), marketing touchpoints, and CRM stage data. Trial users are segmented by activation milestones and routed into personalized onboarding sequences; sales sees enriched profiles with product signals for better prioritization.<\/p>\n\n\n\n

      Result: tighter Direct & Retention Marketing<\/strong> alignment with sales follow-up, and cleaner funnel measurement inside CRM Marketing<\/strong>.<\/p>\n\n\n\n

      Benefits of Using Customer Data Platform<\/h2>\n\n\n\n

      A well-implemented Customer Data Platform commonly improves:<\/p>\n\n\n\n

        \n
      • Personalization quality<\/strong>: messages reflect full customer context, not a single-channel snapshot.<\/li>\n
      • Retention performance<\/strong>: better onboarding, reactivation, and churn mitigation through accurate triggers.<\/li>\n
      • Operational efficiency<\/strong>: fewer manual exports, fewer one-off lists, less rework across teams.<\/li>\n
      • Lower media waste<\/strong>: suppression of existing customers from acquisition ads; smarter retargeting audiences.<\/li>\n
      • Improved customer experience<\/strong>: consistent messaging and frequency across email, SMS, push, and paid.<\/li>\n
      • More trustworthy reporting<\/strong>: shared definitions for lifecycle stages strengthen CRM Marketing<\/strong> measurement.<\/li>\n<\/ul>\n\n\n\n

        In Direct & Retention Marketing<\/strong>, these benefits often compound because every incremental improvement in segmentation and timing lifts multiple campaigns at once.<\/p>\n\n\n\n

        Challenges of Customer Data Platform<\/h2>\n\n\n\n

        A Customer Data Platform is not a magic switch. Common challenges include:<\/p>\n\n\n\n

        Identity and match-rate limitations<\/h3>\n\n\n\n

        If customers don\u2019t log in, or identifiers are inconsistent, profiles remain fragmented. This reduces the reliability of personalization and cross-channel suppression\u2014two pillars of Direct & Retention Marketing<\/strong>.<\/p>\n\n\n\n

        Data quality and taxonomy drift<\/h3>\n\n\n\n

        Event naming inconsistency (\u201cAddToCart\u201d vs \u201cadd_to_cart\u201d), missing properties, or duplicated events can break segments and triggers. Without governance, CRM Marketing<\/strong> teams end up debugging campaigns instead of optimizing them.<\/p>\n\n\n\n

        Privacy, consent, and compliance complexity<\/h3>\n\n\n\n

        Consent must be captured, stored, and respected across activations. Teams must avoid over-collecting and ensure retention policies align with legal and brand standards.<\/p>\n\n\n\n

        Implementation and change management<\/h3>\n\n\n\n

        A Customer Data Platform touches engineering, analytics, marketing ops, and legal. Unclear ownership leads to stalled rollouts or \u201cshadow segments\u201d that undermine governance.<\/p>\n\n\n\n

        Cost and tool overlap<\/h3>\n\n\n\n

        Some organizations already have warehouses, CRM tools, and automation platforms. The value of a Customer Data Platform must be justified through improved activation speed, better targeting, and measurable uplift.<\/p>\n\n\n\n

        Best Practices for Customer Data Platform<\/h2>\n\n\n\n

        To make a Customer Data Platform successful in Direct & Retention Marketing<\/strong> and CRM Marketing<\/strong>, focus on execution discipline:<\/p>\n\n\n\n

          \n
        1. \n

          Start with priority use cases<\/strong>\n Pick 3\u20135 high-impact scenarios (onboarding, cart\/browse abandonment, churn risk, cross-sell) and build the data requirements from there.<\/p>\n<\/li>\n

        2. \n

          Define a tracking plan and event taxonomy<\/strong>\n Standardize event names, required properties, and customer identifiers. Document \u201csource of truth\u201d fields (for example, revenue from billing system).<\/p>\n<\/li>\n

        3. \n

          Treat identity resolution as a product<\/strong>\n Establish merge rules, test edge cases, and monitor match rates. Bad stitching creates bad personalization.<\/p>\n<\/li>\n

        4. \n

          Build governance into daily workflows<\/strong>\n Role-based access, segment approval processes for sensitive audiences, and clear rules for PII handling strengthen CRM Marketing<\/strong> reliability.<\/p>\n<\/li>\n

        5. \n

          Operationalize QA and monitoring<\/strong>\n Validate key events and segments continuously. Alert on drops in event volume or unusual spikes that could trigger unwanted campaigns.<\/p>\n<\/li>\n

        6. \n

          Measure incrementality, not just engagement<\/strong>\n Use holdouts or controlled experiments where feasible. In Direct & Retention Marketing<\/strong>, opens and clicks can be misleading if you don\u2019t track lift in revenue or retention.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

          Tools Used for Customer Data Platform<\/h2>\n\n\n\n

          A Customer Data Platform rarely operates alone; it sits in a broader stack. Common tool categories include:<\/p>\n\n\n\n

            \n
          • Analytics tools<\/strong>: product analytics and web analytics to understand behavior and validate event collection.<\/li>\n
          • Marketing automation tools<\/strong>: email, SMS, push, and journey orchestration platforms that receive segments and profile attributes.<\/li>\n
          • CRM systems<\/strong>: contact\/account management, pipeline stages, and customer service context\u2014core to CRM Marketing<\/strong> alignment.<\/li>\n
          • Ad platforms<\/strong>: retargeting and suppression audiences, especially for preventing waste and improving lifecycle acquisition.<\/li>\n
          • Data warehouses and transformation tools<\/strong>: storage and modeling layers that support composable approaches and advanced analytics.<\/li>\n
          • Reporting dashboards and BI<\/strong>: unified performance reporting for lifecycle cohorts and customer segments.<\/li>\n
          • SEO and content measurement tools<\/strong>: while not CDP tools, they help evaluate how content-led acquisition influences downstream retention and customer value when integrated into broader reporting.<\/li>\n<\/ul>\n\n\n\n

            The key is interoperability: the Customer Data Platform should reduce friction between systems, not add another silo.<\/p>\n\n\n\n

            Metrics Related to Customer Data Platform<\/h2>\n\n\n\n

            To manage a Customer Data Platform effectively, track metrics across data health, activation performance, and business outcomes:<\/p>\n\n\n\n

            Data and identity metrics<\/h3>\n\n\n\n
              \n
            • Match rate \/ identity resolution rate<\/strong><\/li>\n
            • Profile coverage<\/strong> (percent of customers with required attributes)<\/li>\n
            • Event freshness<\/strong> (latency from event to availability for segmentation)<\/li>\n
            • Schema compliance<\/strong> (events with required properties present)<\/li>\n
            • Duplicate rate<\/strong> (duplicate profiles or duplicate events)<\/li>\n<\/ul>\n\n\n\n

              Activation and operations metrics<\/h3>\n\n\n\n
                \n
              • Time to launch<\/strong> a new segment or trigger<\/li>\n
              • Sync success rate<\/strong> to downstream tools<\/li>\n
              • Audience accuracy checks<\/strong> (spot audits against known cohorts)<\/li>\n
              • Suppression effectiveness<\/strong> (reduced overlapping sends)<\/li>\n<\/ul>\n\n\n\n

                Direct & Retention Marketing outcomes<\/h3>\n\n\n\n
                  \n
                • Repeat purchase rate \/ reorder rate<\/strong><\/li>\n
                • Churn rate<\/strong> and retention rate<\/strong> by cohort<\/li>\n
                • Customer lifetime value (LTV)<\/strong><\/li>\n
                • Incremental revenue lift<\/strong> from lifecycle campaigns<\/li>\n
                • CAC-to-LTV ratio improvements<\/strong> from better suppression and targeting<\/li>\n<\/ul>\n\n\n\n

                  These metrics connect Customer Data Platform health directly to CRM Marketing<\/strong> performance.<\/p>\n\n\n\n

                  Future Trends of Customer Data Platform<\/h2>\n\n\n\n

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

                    \n
                  • Privacy-first data design<\/strong>: stronger consent enforcement, data minimization, and shorter retention windows where appropriate.<\/li>\n
                  • Server-side and first-party event collection<\/strong>: more durable tracking approaches to maintain measurement quality as client-side signals become less reliable.<\/li>\n
                  • AI-assisted segmentation and personalization<\/strong>: predictive traits (churn risk, next-best action) and automated audience recommendations\u2014paired with governance to avoid opaque decisions.<\/li>\n
                  • Real-time orchestration<\/strong>: faster triggers and decisioning for in-session personalization and immediate lifecycle interventions.<\/li>\n
                  • Better interoperability and \u201ccomposable\u201d architectures<\/strong>: organizations choosing flexible components while maintaining a unified profile layer.<\/li>\n
                  • Experimentation baked into lifecycle marketing<\/strong>: more systematic holdouts and incremental measurement in CRM Marketing<\/strong> programs.<\/li>\n<\/ul>\n\n\n\n

                    Customer Data Platform vs Related Terms<\/h2>\n\n\n\n

                    Customer Data Platform vs CRM<\/h3>\n\n\n\n

                    A CRM system is primarily for managing customer relationships, pipeline, and communications history\u2014often optimized for sales and service workflows. A Customer Data Platform is designed to unify behavioral and transactional data across systems and activate it broadly. In practice, CRM Marketing<\/strong> benefits when the CRM holds relationship records while the Customer Data Platform powers segmentation and cross-channel triggers.<\/p>\n\n\n\n

                    Customer Data Platform vs DMP (Data Management Platform)<\/h3>\n\n\n\n

                    A DMP traditionally focuses on advertising audiences, often relying on third-party or cookie-based identifiers and shorter-lived profiles. A Customer Data Platform centers on first-party data and persistent profiles used for retention and customer experience\u2014more aligned with Direct & Retention Marketing<\/strong> than pure ad targeting.<\/p>\n\n\n\n

                    Customer Data Platform vs Data Warehouse<\/h3>\n\n\n\n

                    A data warehouse stores and models data for analysis and reporting, but it doesn\u2019t necessarily provide real-time segmentation, identity tooling, and activation connectors out of the box. A Customer Data Platform is built to operationalize data for campaigns and personalization, though many teams use both together.<\/p>\n\n\n\n

                    Who Should Learn Customer Data Platform<\/h2>\n\n\n\n
                      \n
                    • Marketers<\/strong>: to design lifecycle programs that are consistent across channels and grounded in real customer behavior.<\/li>\n
                    • Analysts<\/strong>: to build reliable segments, validate identity logic, and connect Direct & Retention Marketing<\/strong> actions to outcomes.<\/li>\n
                    • Agencies<\/strong>: to implement scalable retention frameworks and reduce dependency on manual list pulls.<\/li>\n
                    • Business owners and founders<\/strong>: to understand the data capabilities needed for sustainable growth and improved retention economics.<\/li>\n
                    • Developers and marketing engineers<\/strong>: to implement tracking plans, data pipelines, consent handling, and integrations that make CRM Marketing<\/strong> automation trustworthy.<\/li>\n<\/ul>\n\n\n\n

                      Summary of Customer Data Platform<\/h2>\n\n\n\n

                      A Customer Data Platform (CDP)<\/strong> collects and unifies first-party customer data into persistent profiles that can be segmented and activated across marketing channels. It matters because Direct & Retention Marketing<\/strong> depends on accurate identity, timely triggers, and consistent personalization. In CRM Marketing<\/strong>, a Customer Data Platform improves segmentation integrity, governance, and measurement\u2014helping teams move faster while maintaining control.<\/p>\n\n\n\n

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

                      1) What is a Customer Data Platform (CDP) in simple terms?<\/h3>\n\n\n\n

                      A Customer Data Platform is a system that gathers customer data from many places, connects it into unified profiles, and makes it usable for segmentation and marketing activation.<\/p>\n\n\n\n

                      2) Do I need a Customer Data Platform if I already have a CRM?<\/h3>\n\n\n\n

                      Often, yes\u2014if your customer behavior data (web\/app usage, transactions, support, marketing engagement) lives outside the CRM. A CRM is great for relationship records; a Customer Data Platform helps unify and activate cross-channel behavior for Direct & Retention Marketing<\/strong>.<\/p>\n\n\n\n

                      3) How does a Customer Data Platform support CRM Marketing specifically?<\/h3>\n\n\n\n

                      In CRM Marketing<\/strong>, a Customer Data Platform improves audience definitions, reduces duplicate records, enables richer personalization attributes, and syncs consistent segments into lifecycle tools like email and SMS platforms.<\/p>\n\n\n\n

                      4) What data should be connected first for Direct & Retention Marketing?<\/h3>\n\n\n\n

                      Start with identifiers (email\/phone\/customer ID), purchase\/subscription events, core web\/app events, and messaging engagement data. These typically unlock onboarding, win-back, and suppression use cases quickly.<\/p>\n\n\n\n

                      5) What\u2019s the biggest implementation risk with a CDP?<\/h3>\n\n\n\n

                      Poor data quality and weak identity resolution. If tracking is inconsistent or profiles stitch incorrectly, segmentation becomes unreliable and personalization can backfire.<\/p>\n\n\n\n

                      6) How do you measure success after implementing a Customer Data Platform?<\/h3>\n\n\n\n

                      Track both platform health (match rate, event freshness, sync reliability) and business lift (retention rate, churn reduction, repeat purchase rate, incremental revenue from lifecycle campaigns). Success should show up in improved Direct & Retention Marketing<\/strong> outcomes, not just more data collected.<\/p>\n","protected":false},"excerpt":{"rendered":"

                      A **Customer Data Platform** is the system many modern teams rely on to turn scattered customer signals\u2014web visits, app events, purchases, support tickets, email engagement\u2014into a usable, consent-aware customer view. In **Direct & Retention Marketing**, that \u201cusable\u201d part is everything: if you can\u2019t confidently identify people, understand their lifecycle stage, and activate relevant messages, retention programs become guesswork.<\/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":[1893],"tags":[],"class_list":["post-7669","post","type-post","status-publish","format-standard","hentry","category-crm-marketing"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7669","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=7669"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7669\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=7669"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=7669"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=7669"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}