{"id":7177,"date":"2026-03-24T03:05:51","date_gmt":"2026-03-24T03:05:51","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/pricing-test\/"},"modified":"2026-03-24T03:05:51","modified_gmt":"2026-03-24T03:05:51","slug":"pricing-test","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/pricing-test\/","title":{"rendered":"Pricing Test: What It Is, Key Features, Benefits, Use Cases, and How It Fits in CRO"},"content":{"rendered":"\n

Pricing is one of the most powerful levers in growth because it affects revenue per customer, perceived value, and who decides to buy at all. A Pricing Test<\/strong> is the disciplined practice of experimenting with prices, packaging, discounts, or billing terms to learn what improves business outcomes\u2014without relying on opinions or gut feel.<\/p>\n\n\n\n

In Conversion & Measurement<\/strong>, a Pricing Test is treated like any other experiment: you define a hypothesis, expose comparable audiences to different pricing conditions, and measure the impact on conversion and downstream revenue. Within CRO<\/strong>, it\u2019s a high-impact but high-responsibility area because changes can shift demand, brand perception, and customer quality\u2014not just conversion rate.<\/p>\n\n\n\n

Modern teams use a Pricing Test to balance short-term conversion lifts with long-term goals like retention, profitability, and customer trust. When done well, it becomes a repeatable way to reduce pricing risk while improving performance across the funnel.<\/p>\n\n\n\n

What Is Pricing Test?<\/h2>\n\n\n\n

A Pricing Test<\/strong> is a structured experiment designed to evaluate how changes to price-related variables affect user behavior and business performance. Those variables can include the headline price, currency display, billing cadence (monthly vs annual), tier boundaries, feature bundling, discounting rules, shipping thresholds, or even price presentation (anchoring, \u201cmost popular\u201d tier, or per-user framing).<\/p>\n\n\n\n

The core concept is simple: pricing is a hypothesis about value. A Pricing Test checks that hypothesis with real customer behavior, not assumptions. The business meaning is straightforward: you\u2019re validating which pricing approach maximizes outcomes such as revenue, profit, conversion rate, retention, or customer lifetime value.<\/p>\n\n\n\n

In Conversion & Measurement<\/strong>, Pricing Test work sits at the intersection of analytics, experimentation, attribution, and financial modeling. Inside CRO<\/strong>, it\u2019s a specialized form of optimization that often requires stronger governance than UI tests because the downside risk can be real if the wrong users see the wrong price.<\/p>\n\n\n\n

Why Pricing Test Matters in Conversion & Measurement<\/h2>\n\n\n\n

A Pricing Test matters because pricing can improve multiple parts of the funnel at once\u2014sometimes in conflicting ways. Lower prices may increase trial starts but reduce profitability; higher prices may reduce sign-ups but improve customer quality. Strong Conversion & Measurement<\/strong> practice ensures you can see the full picture.<\/p>\n\n\n\n

Key reasons a Pricing Test delivers strategic value:<\/p>\n\n\n\n

    \n
  • Direct impact on revenue efficiency:<\/strong> Small price changes can outperform many acquisition optimizations, especially when traffic is already expensive.<\/li>\n
  • Better product-market fit signals:<\/strong> If conversion collapses at a certain tier, it may indicate packaging issues or misaligned value communication.<\/li>\n
  • Competitive advantage:<\/strong> Competitors can copy features; it\u2019s harder to copy a pricing system that\u2019s continuously tested and refined.<\/li>\n
  • More reliable planning:<\/strong> Pricing experiments create empirical baselines that improve forecasts, budget allocation, and growth strategy.<\/li>\n
  • Stronger CRO prioritization:<\/strong> In CRO<\/strong>, pricing experiments often rank among the highest expected impact initiatives, provided measurement is robust.<\/li>\n<\/ul>\n\n\n\n

    How Pricing Test Works<\/h2>\n\n\n\n

    A Pricing Test is practical experimentation applied to monetization. While details differ by business model, the workflow usually looks like this:<\/p>\n\n\n\n

      \n
    1. \n

      Input (question + hypothesis)<\/strong>\n – Example: \u201cIf we raise the Pro plan from $29 to $39, overall revenue will increase without harming retention.\u201d\n – Define what \u201csuccess\u201d means in Conversion & Measurement<\/strong> terms: conversion, revenue, margin, refunds, churn, and brand risk thresholds.<\/p>\n<\/li>\n

    2. \n

      Analysis (design + segmentation)<\/strong>\n – Identify who is eligible to see the test (new visitors only, new sign-ups only, specific geos, or specific channels).\n – Choose a test design: randomized experiment, geo split, time-based holdout, or staged rollout.\n – Decide your measurement window (immediate purchase vs 30\/60\/90-day retention outcomes).<\/p>\n<\/li>\n

    3. \n

      Execution (exposure + instrumentation)<\/strong>\n – Implement price variants consistently across pricing page, checkout, invoices, emails, and in-app upgrade flows.\n – Instrument key events: price viewed, plan selected, checkout started, purchase completed, refund requested, subscription canceled.<\/p>\n<\/li>\n

    4. \n

      Output (decision + rollout)<\/strong>\n – Evaluate results with guardrails (e.g., conversion can drop slightly if revenue and retention increase).\n – Make a decision: ship, iterate, or revert.\n – Document learnings so future CRO<\/strong> work doesn\u2019t repeat the same assumptions.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

      The most important practical point: a Pricing Test should measure downstream outcomes, not only the immediate conversion rate. In Conversion & Measurement<\/strong>, monetization decisions demand longer feedback loops than button-color tests.<\/p>\n\n\n\n

      Key Components of Pricing Test<\/h2>\n\n\n\n

      A reliable Pricing Test needs more than an A\/B tool and a new price point. The major components include:<\/p>\n\n\n\n

      Experiment design and governance<\/h3>\n\n\n\n
        \n
      • Clear hypotheses, eligibility rules, and stopping criteria<\/li>\n
      • Risk review (legal, finance, customer support readiness, brand guidelines)<\/li>\n
      • Approval workflow for sensitive pricing changes<\/li>\n<\/ul>\n\n\n\n

        Data inputs<\/h3>\n\n\n\n
          \n
        • Historical conversion rates and revenue<\/li>\n
        • Customer segments (new vs returning, SMB vs enterprise, region, device, channel)<\/li>\n
        • Cost structure (COGS, payment processing fees, fulfillment or support costs)<\/li>\n<\/ul>\n\n\n\n

          Instrumentation and tracking<\/h3>\n\n\n\n
            \n
          • Consistent event definitions across web and product analytics<\/li>\n
          • Identity resolution (anonymous visitor \u2192 lead \u2192 customer)<\/li>\n
          • Logging of \u201cprice shown\u201d to avoid ambiguity in analysis<\/li>\n<\/ul>\n\n\n\n

            Metrics framework (primary + guardrails)<\/h3>\n\n\n\n
              \n
            • Primary metrics: revenue per visitor, net revenue, profit contribution<\/li>\n
            • Guardrails: refunds, chargebacks, churn, support tickets, complaint rate<\/li>\n<\/ul>\n\n\n\n

              Team responsibilities<\/h3>\n\n\n\n
                \n
              • Marketing: messaging, channel mix, landing pages<\/li>\n
              • Product: paywall\/in-app upgrades, entitlements, plan rules<\/li>\n
              • Data\/Analytics: experiment design, quality checks, statistical review<\/li>\n
              • Finance: margin analysis, revenue recognition considerations<\/li>\n
              • Support\/Sales: handling objections and ensuring pricing consistency<\/li>\n<\/ul>\n\n\n\n

                This cross-functional alignment is a hallmark of mature Conversion & Measurement<\/strong> and advanced CRO<\/strong> programs.<\/p>\n\n\n\n

                Types of Pricing Test<\/h2>\n\n\n\n

                \u201cTypes\u201d of Pricing Test are best understood by what you vary and how you run the experiment.<\/p>\n\n\n\n

                By what you change<\/h3>\n\n\n\n
                  \n
                • Price point tests:<\/strong> Same package, different price (e.g., $49 vs $59).<\/li>\n
                • Packaging tests:<\/strong> Move features between tiers, create a new tier, or redefine tier boundaries.<\/li>\n
                • Billing cadence tests:<\/strong> Monthly vs annual default, annual discount levels, installment options.<\/li>\n
                • Discount and promotion tests:<\/strong> Coupon value, eligibility rules, time limits, bundles.<\/li>\n
                • Price presentation tests:<\/strong> Anchoring with a higher tier, \u201cmost popular\u201d labeling, unit framing (per seat vs per month), or showing savings.<\/li>\n<\/ul>\n\n\n\n

                  By experimental design<\/h3>\n\n\n\n
                    \n
                  • Randomized A\/B or multivariate tests:<\/strong> Best for digital funnels where traffic can be randomized.<\/li>\n
                  • Geo-based tests:<\/strong> Useful when pricing must be consistent within a region or regulated environment.<\/li>\n
                  • Holdout tests:<\/strong> Maintain a control group for longer-term retention and LTV measurement.<\/li>\n
                  • Staged rollouts:<\/strong> Start with a small percentage to reduce risk, then expand.<\/li>\n<\/ul>\n\n\n\n

                    A strong Pricing Test<\/strong> program often blends these approaches based on risk, traffic, and the time required to measure outcomes\u2014key concerns in Conversion & Measurement<\/strong>.<\/p>\n\n\n\n

                    Real-World Examples of Pricing Test<\/h2>\n\n\n\n

                    Example 1: SaaS plan price increase with retention guardrails<\/h3>\n\n\n\n

                    A B2B SaaS company tests raising the mid-tier plan from $30 to $36 for new sign-ups only. The Conversion & Measurement<\/strong> plan tracks trial-to-paid conversion, revenue per visitor, and 60-day churn. The result shows a small drop in paid conversion but a larger increase in net revenue, with no churn impact. The CRO<\/strong> decision is to ship the increase and run a follow-up test on annual plan messaging.<\/p>\n\n\n\n

                    Example 2: Ecommerce free-shipping threshold test<\/h3>\n\n\n\n

                    An online retailer tests free shipping at $50 vs $75. The Pricing Test<\/strong> measures conversion rate, average order value, margin per order (shipping cost), and return rate. Conversion & Measurement<\/strong> reveals that the higher threshold raises AOV but reduces conversion; net margin improves slightly for paid search traffic but declines for organic. CRO<\/strong> action: set different thresholds by channel or introduce \u201cfree shipping for members\u201d packaging.<\/p>\n\n\n\n

                    Example 3: Service business tiered packages vs custom quotes<\/h3>\n\n\n\n

                    A home services company tests replacing a single \u201cCall for pricing\u201d flow with three packaged options: Basic, Standard, Premium. The Pricing Test<\/strong> evaluates lead-to-booking conversion, average job value, cancellation rate, and call volume. Conversion & Measurement<\/strong> shows fewer low-quality leads and higher booked revenue. In CRO<\/strong>, the business keeps packages and tests add-ons at checkout.<\/p>\n\n\n\n

                    Benefits of Using Pricing Test<\/h2>\n\n\n\n

                    A well-run Pricing Test can produce benefits beyond a simple conversion lift:<\/p>\n\n\n\n

                      \n
                    • Revenue growth without more traffic:<\/strong> Improve revenue per visitor, per lead, or per account.<\/li>\n
                    • Profit and margin optimization:<\/strong> Better alignment between price and cost-to-serve.<\/li>\n
                    • Higher-quality customers:<\/strong> Some price changes reduce churn by filtering for better-fit buyers.<\/li>\n
                    • Better user experience:<\/strong> Clearer tiers and transparent pricing reduce confusion and support burden.<\/li>\n
                    • Faster learning loops:<\/strong> Pricing experiments create a knowledge base that strengthens CRO<\/strong> prioritization and forecasting in Conversion & Measurement<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                      Challenges of Pricing Test<\/h2>\n\n\n\n

                      Pricing experimentation is powerful, but it comes with real risks and measurement pitfalls:<\/p>\n\n\n\n

                        \n
                      • Customer trust and fairness concerns:<\/strong> If users discover different prices, it can create backlash, especially in consumer markets.<\/li>\n
                      • Implementation complexity:<\/strong> Pricing must be consistent across pages, devices, emails, invoices, and sales conversations.<\/li>\n
                      • Statistical sensitivity:<\/strong> Pricing changes can produce large behavior shifts, making outliers and seasonality more influential.<\/li>\n
                      • Downstream measurement lag:<\/strong> Retention and LTV require time; short tests can mislead.<\/li>\n
                      • Segment interaction effects:<\/strong> A \u201cwinning\u201d price overall may harm an important segment (e.g., enterprise leads).<\/li>\n
                      • Operational constraints:<\/strong> Legal requirements, MAP policies, taxes, and regional pricing regulations can limit what you can test.<\/li>\n<\/ul>\n\n\n\n

                        These are Conversion & Measurement<\/strong> problems as much as they are pricing problems, and they require mature CRO<\/strong> processes to manage.<\/p>\n\n\n\n

                        Best Practices for Pricing Test<\/h2>\n\n\n\n

                        To make Pricing Test efforts reliable and scalable:<\/p>\n\n\n\n

                          \n
                        1. \n

                          Start with a clear objective and hierarchy of metrics<\/strong>\n – Pick one primary metric (e.g., net revenue per visitor) and define guardrails (refund rate, churn, complaint rate).<\/p>\n<\/li>\n

                        2. \n

                          Test one major pricing idea at a time<\/strong>\n – If you change price, packaging, and messaging simultaneously, you won\u2019t know what caused the outcome.<\/p>\n<\/li>\n

                        3. \n

                          Segment intentionally<\/strong>\n – Common splits: new vs returning, channel, geo, device, customer size. Plan segmentation before launch to avoid fishing.<\/p>\n<\/li>\n

                        4. \n

                          Ensure price consistency across the journey<\/strong>\n – The price shown on a landing page must match checkout, invoices, and confirmation emails.<\/p>\n<\/li>\n

                        5. \n

                          Use longer windows when necessary<\/strong>\n – For subscriptions, measure at least one meaningful retention checkpoint (e.g., 30\u201390 days) before declaring a winner.<\/p>\n<\/li>\n

                        6. \n

                          Document learnings<\/strong>\n – In CRO<\/strong>, experiment documentation prevents repeated debates and accelerates future Conversion & Measurement<\/strong> work.<\/p>\n<\/li>\n

                        7. \n

                          Design for reversibility<\/strong>\n – Use staged rollout, holdouts, and clear rollback plans to reduce operational risk.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                          Tools Used for Pricing Test<\/h2>\n\n\n\n

                          Pricing Test is not about one tool; it\u2019s a workflow across systems. Common tool categories used in Conversion & Measurement<\/strong> and CRO<\/strong> include:<\/p>\n\n\n\n

                            \n
                          • Experimentation platforms:<\/strong> Run A\/B tests, manage randomization, and control exposure. For sensitive pricing, tools must support strict targeting and QA.<\/li>\n
                          • Web and product analytics:<\/strong> Track funnel behavior from price view to purchase to retention, and validate event integrity.<\/li>\n
                          • Data warehouses and BI dashboards:<\/strong> Combine experiment exposure with revenue, churn, refunds, and support data for a complete view.<\/li>\n
                          • CRM and marketing automation:<\/strong> Track lead quality, sales cycle length, and lifecycle outcomes influenced by pricing.<\/li>\n
                          • Payments\/subscription systems:<\/strong> Capture plan changes, proration, payment failures, refunds, and billing cadence effects.<\/li>\n
                          • Customer support systems:<\/strong> Monitor ticket volume, reasons for contact, and sentiment shifts during a Pricing Test.<\/li>\n<\/ul>\n\n\n\n

                            The goal is end-to-end traceability: who saw what price, what they did, and what they were worth over time\u2014core to Conversion & Measurement<\/strong>.<\/p>\n\n\n\n

                            Metrics Related to Pricing Test<\/h2>\n\n\n\n

                            A Pricing Test should be evaluated with a balanced set of metrics:<\/p>\n\n\n\n

                            Conversion and funnel metrics<\/h3>\n\n\n\n
                              \n
                            • Pricing page view-to-click rate<\/li>\n
                            • Checkout start rate and checkout completion rate<\/li>\n
                            • Lead-to-customer conversion (for sales-assisted models)<\/li>\n<\/ul>\n\n\n\n

                              Revenue and profitability metrics<\/h3>\n\n\n\n
                                \n
                              • Revenue per visitor \/ revenue per session<\/li>\n
                              • Average order value (AOV) or average revenue per account (ARPA)<\/li>\n
                              • Gross margin per order \/ contribution margin<\/li>\n
                              • Discount rate and effective price paid<\/li>\n<\/ul>\n\n\n\n

                                Retention and quality metrics<\/h3>\n\n\n\n
                                  \n
                                • Trial-to-paid activation quality (usage milestones)<\/li>\n
                                • Renewal rate, churn rate, and expansion revenue<\/li>\n
                                • Refund rate, chargebacks, payment failure rate<\/li>\n
                                • Customer lifetime value (LTV) and LTV:CAC (when CAC is stable or controlled)<\/li>\n<\/ul>\n\n\n\n

                                  Experience and brand guardrails<\/h3>\n\n\n\n
                                    \n
                                  • Support ticket volume and pricing-related contact reasons<\/li>\n
                                  • NPS or CSAT shifts (if measured reliably)<\/li>\n
                                  • Complaint rate or negative feedback rate<\/li>\n<\/ul>\n\n\n\n

                                    In Conversion & Measurement<\/strong>, the right choice of primary metric depends on the business model. In CRO<\/strong>, the key is avoiding \u201clocal wins\u201d that hurt long-term value.<\/p>\n\n\n\n

                                    Future Trends of Pricing Test<\/h2>\n\n\n\n

                                    Pricing Test practices are evolving quickly, influenced by AI, personalization, and privacy changes:<\/p>\n\n\n\n

                                      \n
                                    • AI-assisted hypothesis generation:<\/strong> Teams increasingly use models to identify segments likely to respond differently to pricing and packaging.<\/li>\n
                                    • Dynamic packaging and personalized offers (with caution):<\/strong> More businesses tailor bundles or incentives, but governance and fairness become critical in Conversion & Measurement<\/strong>.<\/li>\n
                                    • Incrementality and causal measurement maturity:<\/strong> As attribution becomes noisier, more organizations lean on experiments and holdouts to prove pricing impact.<\/li>\n
                                    • Privacy and platform constraints:<\/strong> Less granular tracking pushes teams to improve first-party data quality and server-side event collection.<\/li>\n
                                    • More focus on long-term outcomes:<\/strong> Subscription businesses increasingly treat Pricing Test as a retention and margin optimization discipline, not just an acquisition lever.<\/li>\n<\/ul>\n\n\n\n

                                      The best programs will integrate Pricing Test into a broader CRO<\/strong> roadmap and treat it as a continuous system within Conversion & Measurement<\/strong>, not a one-off project.<\/p>\n\n\n\n

                                      Pricing Test vs Related Terms<\/h2>\n\n\n\n

                                      Pricing Test vs A\/B Testing<\/h3>\n\n\n\n

                                      A\/B testing is a general experimentation method; Pricing Test<\/strong> is a specific application focused on monetization variables. All Pricing Test work can use A\/B methods, but not all A\/B tests are pricing-related. Pricing tests typically require stronger guardrails and longer measurement windows in Conversion & Measurement<\/strong>.<\/p>\n\n\n\n

                                      Pricing Test vs Price Optimization<\/h3>\n\n\n\n

                                      Price optimization is the broader discipline of setting prices using research, competitive inputs, cost models, and analytics. A Pricing Test is one of the most reliable ways to validate price optimization decisions with real behavior. In CRO<\/strong>, testing complements modeling by proving outcomes under real conditions.<\/p>\n\n\n\n

                                      Pricing Test vs Promotion Testing<\/h3>\n\n\n\n

                                      Promotion testing focuses on discounts and limited-time offers. It overlaps with Pricing Test but is narrower. Promotions can inflate conversion while training customers to wait for deals, so Conversion & Measurement<\/strong> must include post-purchase behavior and repeat rate to assess true value.<\/p>\n\n\n\n

                                      Who Should Learn Pricing Test<\/h2>\n\n\n\n
                                        \n
                                      • Marketers:<\/strong> Pricing changes impact acquisition efficiency, landing page performance, and messaging strategy\u2014central to CRO<\/strong> and Conversion & Measurement<\/strong> planning.<\/li>\n
                                      • Analysts and data teams:<\/strong> Pricing tests demand strong experimental design, clean instrumentation, and careful interpretation of revenue and retention outcomes.<\/li>\n
                                      • Agencies and consultants:<\/strong> Clients often ask for \u201cconversion improvements,\u201d and pricing experiments can deliver outsized results when managed responsibly.<\/li>\n
                                      • Business owners and founders:<\/strong> Pricing is strategy. A Pricing Test provides evidence to support critical decisions without betting the business on intuition.<\/li>\n
                                      • Developers and product teams:<\/strong> Implementing consistent pricing logic, entitlements, and tracking is technical work that enables trustworthy Conversion & Measurement<\/strong>.<\/li>\n<\/ul>\n\n\n\n

                                        Summary of Pricing Test<\/h2>\n\n\n\n

                                        A Pricing Test<\/strong> is a structured way to experiment with price points, packaging, billing terms, discounts, and price presentation to learn what improves business results. It matters because pricing directly affects conversion, revenue, profitability, and customer quality. Within Conversion & Measurement<\/strong>, it demands rigorous instrumentation and longer-term evaluation. Within CRO<\/strong>, it\u2019s one of the highest-impact levers\u2014when governed carefully and measured beyond the immediate conversion rate.<\/p>\n\n\n\n

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

                                        1) What is a Pricing Test and when should I run one?<\/h3>\n\n\n\n

                                        A Pricing Test is an experiment that measures how pricing changes affect conversion and business outcomes. Run one when you have enough traffic or sales volume to learn reliably, and when you can track downstream outcomes like refunds, churn, or repeat purchases.<\/p>\n\n\n\n

                                        2) What\u2019s the biggest mistake teams make with Pricing Test?<\/h3>\n\n\n\n

                                        Declaring a winner based only on short-term conversion rate. In Conversion & Measurement<\/strong>, pricing often changes customer quality and retention, so you need revenue and post-purchase guardrails.<\/p>\n\n\n\n

                                        3) How long should a Pricing Test run?<\/h3>\n\n\n\n

                                        Long enough to cover demand cycles and reach a pre-defined sample size, plus any required lagging outcomes. Ecommerce tests might conclude faster; subscription Pricing Test work often needs weeks plus retention checkpoints.<\/p>\n\n\n\n

                                        4) Can Pricing Test hurt my brand or customer trust?<\/h3>\n\n\n\n

                                        Yes, if customers perceive pricing as unfair or inconsistent. Reduce risk with clear rules (e.g., test only new visitors), consistent experiences, and careful messaging\u2014especially important in CRO<\/strong> programs.<\/p>\n\n\n\n

                                        5) How does Pricing Test relate to CRO?<\/h3>\n\n\n\n

                                        CRO<\/strong> focuses on improving conversion and value from existing traffic. Pricing Test is a specialized CRO method that optimizes monetization\u2014often with larger upside, but also higher governance and measurement requirements.<\/p>\n\n\n\n

                                        6) Should I test pricing by segment (geo, channel, device)?<\/h3>\n\n\n\n

                                        Sometimes. Segment-based Pricing Test can be valid when costs, willingness to pay, or competitive context differ. In Conversion & Measurement<\/strong>, plan segmentation upfront and watch for fairness, compliance, and interpretability issues.<\/p>\n\n\n\n

                                        7) What metric should I prioritize in a Pricing Test?<\/h3>\n\n\n\n

                                        Choose a metric aligned to the business model: revenue per visitor, contribution margin, or LTV. Then add guardrails like churn, refunds, and support contacts so the Pricing Test improves the business, not just the funnel.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                        Pricing is one of the most powerful levers in growth because it affects revenue per customer, perceived value, and who decides to buy at all. A **Pricing Test** is the disciplined practice of experimenting with prices, packaging, discounts, or billing terms to learn what improves business outcomes\u2014without relying on opinions or gut feel.<\/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":[1889],"tags":[],"class_list":["post-7177","post","type-post","status-publish","format-standard","hentry","category-cro"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7177","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=7177"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7177\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=7177"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=7177"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=7177"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}