{"id":7169,"date":"2026-03-24T02:47:52","date_gmt":"2026-03-24T02:47:52","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/offer-test\/"},"modified":"2026-03-24T02:47:52","modified_gmt":"2026-03-24T02:47:52","slug":"offer-test","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/offer-test\/","title":{"rendered":"Offer Test: What It Is, Key Features, Benefits, Use Cases, and How It Fits in CRO"},"content":{"rendered":"\n

An Offer Test<\/strong> is the disciplined process of testing different versions of what you\u2019re asking customers to say \u201cyes\u201d to\u2014pricing, bundles, guarantees, trials, bonuses, shipping thresholds, payment plans, and positioning\u2014to identify which offer drives the best business outcomes. In Conversion & Measurement<\/strong>, it\u2019s one of the most direct ways to influence revenue because it changes the value exchange, not just the page layout.<\/p>\n\n\n\n

In CRO<\/strong> (conversion rate optimization), an Offer Test sits above many tactical experiments (like button color or headline tweaks) because the offer often determines whether the user converts at all. Modern Conversion & Measurement<\/strong> strategies increasingly prioritize Offer Test programs because acquisition costs rise, attention is scarce, and small improvements to conversion efficiency can compound across paid, organic, email, and product-led funnels.<\/p>\n\n\n\n

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

An Offer Test<\/strong> is a structured experiment that compares two or more offers presented to similar audiences under comparable conditions, with the goal of measuring which offer produces better outcomes (such as conversion rate, revenue per visitor, or qualified leads). The core concept is simple: if you change the terms of the deal, you may change the customer\u2019s decision.<\/p>\n\n\n\n

Business-wise, an Offer Test helps answer questions like:<\/p>\n\n\n\n

    \n
  • Should we lead with a free trial or a discount?<\/li>\n
  • Is \u201cmonthly plan + onboarding\u201d more compelling than \u201cannual plan – 20%\u201d?<\/li>\n
  • Does a stronger guarantee increase completed purchases\u2014or increase refunds?<\/li>\n<\/ul>\n\n\n\n

    Within Conversion & Measurement<\/strong>, an Offer Test connects marketing intent to measurable results by tying the offer variation to a defined KPI and tracking it across the funnel. Inside CRO<\/strong>, it\u2019s often considered a high-leverage test category because it can improve both conversion rate and average order value\u2014if designed and measured correctly.<\/p>\n\n\n\n

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

    An Offer Test matters because it addresses the most fundamental conversion question: \u201cIs this worth it to me?\u201d In Conversion & Measurement<\/strong>, you\u2019re not just counting conversions\u2014you\u2019re diagnosing why they happen and what they\u2019re worth.<\/p>\n\n\n\n

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

      \n
    • Direct revenue leverage:<\/strong> Changing price, bundles, or payment terms can materially shift revenue per visitor more than cosmetic page changes.<\/li>\n
    • Efficiency gains across channels:<\/strong> A better offer improves performance in paid search, social ads, email, SEO landing pages, and partner traffic\u2014boosting ROI without necessarily increasing spend.<\/li>\n
    • Clearer product-market signals:<\/strong> Offer performance can reveal which value proposition resonates and which segments are most responsive.<\/li>\n
    • Competitive advantage:<\/strong> Competitors can copy ad creative; they can\u2019t easily copy your exact packaging, guarantee structure, onboarding, or pricing model.<\/li>\n<\/ul>\n\n\n\n

      In mature CRO<\/strong> programs, Offer Test initiatives are often prioritized because they improve the economics of growth: higher conversion, higher order value, better lead quality, and improved retention when aligned with customer needs.<\/p>\n\n\n\n

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

      Although an Offer Test is a concept, it becomes practical through a repeatable workflow that fits into Conversion & Measurement<\/strong> and CRO<\/strong> operations.<\/p>\n\n\n\n

        \n
      1. \n

        Input \/ Trigger (what prompts a test)<\/strong>\n – A conversion bottleneck (high traffic, low purchases)\n – High drop-off at checkout or pricing pages\n – Sales feedback that prospects \u201cdon\u2019t get the value\u201d\n – Rising CAC that requires better conversion efficiency\n – Competitive pressure on price or perceived value<\/p>\n<\/li>\n

      2. \n

        Analysis \/ Processing (deciding what to test)<\/strong>\n – Identify the decision barrier (price anxiety, risk, complexity, lack of urgency, unclear value)\n – Choose a lever: pricing, bundle, guarantee, bonus, trial, shipping, payment plan, or positioning\n – Define success metrics and guardrails (e.g., profit, refund rate, churn)<\/p>\n<\/li>\n

      3. \n

        Execution \/ Application (running the experiment)<\/strong>\n – Deploy variants via landing pages, checkout, pricing pages, email sequences, or sales scripts\n – Ensure randomization and consistent audience splits when possible\n – Maintain a stable environment (avoid overlapping big promos or site changes)<\/p>\n<\/li>\n

      4. \n

        Output \/ Outcome (what you learn)<\/strong>\n – Determine which offer wins on primary metrics (and why)\n – Validate that gains are real (not a tracking artifact or short-term spike)\n – Decide whether to roll out, iterate, or segment the winning offer<\/p>\n<\/li>\n<\/ol>\n\n\n\n

        A strong Offer Test does not only \u201cpick a winner.\u201d It produces learning about customer motivation that can improve messaging, product packaging, and future CRO<\/strong> roadmaps.<\/p>\n\n\n\n

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

        To run Offer Test programs reliably, you need more than ideas\u2014you need measurement discipline and operational clarity.<\/p>\n\n\n\n

        Offer design elements<\/h3>\n\n\n\n
          \n
        • Value proposition framing:<\/strong> outcome, time-to-value, proof, differentiation<\/li>\n
        • Price architecture:<\/strong> list price, discounting, tiering, anchoring<\/li>\n
        • Risk reducers:<\/strong> guarantees, refunds, cancellation terms<\/li>\n
        • Incentives:<\/strong> bonuses, add-ons, onboarding, credits<\/li>\n
        • Friction reducers:<\/strong> payment plans, one-click checkout, shorter forms (when aligned)<\/li>\n<\/ul>\n\n\n\n

          Data inputs and research<\/h3>\n\n\n\n
            \n
          • Qualitative: surveys, user interviews, customer support tickets, sales call notes<\/li>\n
          • Behavioral: heatmaps, click paths, funnel drop-offs, session recordings<\/li>\n
          • Commercial: margin constraints, LTV distribution, refund\/churn patterns<\/li>\n<\/ul>\n\n\n\n

            Systems and governance<\/h3>\n\n\n\n
              \n
            • A testing backlog with hypotheses and prioritization<\/li>\n
            • Clear ownership across marketing, product, analytics, and finance<\/li>\n
            • QA procedures to prevent tracking or pricing errors<\/li>\n
            • Documentation of results for future reuse<\/li>\n<\/ul>\n\n\n\n

              Metrics and measurement foundation<\/h3>\n\n\n\n
                \n
              • Correct event tracking (views, clicks, add-to-cart, purchases, qualified leads)<\/li>\n
              • Clean attribution assumptions for channel-specific tests<\/li>\n
              • A consistent approach to statistical confidence and sample size (or sequential testing rules)<\/li>\n<\/ul>\n\n\n\n

                All of these are part of Conversion & Measurement<\/strong> hygiene and are critical to trustworthy CRO<\/strong> decisions.<\/p>\n\n\n\n

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

                Offer Test doesn\u2019t have one universal taxonomy, but in practice you can categorize tests by the lever you pull and the context where the offer appears.<\/p>\n\n\n\n

                By offer lever<\/h3>\n\n\n\n
                  \n
                • Pricing tests:<\/strong> different price points, tier thresholds, annual vs monthly emphasis<\/li>\n
                • Bundling tests:<\/strong> base product vs bundle, bundle composition, \u201cgood\/better\/best\u201d<\/li>\n
                • Promotion tests:<\/strong> discount vs bonus, limited-time vs evergreen<\/li>\n
                • Risk-reversal tests:<\/strong> stronger guarantee, free returns, cancellation flexibility<\/li>\n
                • Trial \/ freemium tests:<\/strong> trial length, trial gating, credit card required vs not<\/li>\n
                • Shipping \/ threshold tests (ecommerce):<\/strong> free shipping threshold, flat rate vs variable<\/li>\n<\/ul>\n\n\n\n

                  By funnel placement<\/h3>\n\n\n\n
                    \n
                  • Top-of-funnel offer tests:<\/strong> lead magnet types, webinar vs demo vs trial<\/li>\n
                  • Mid-funnel offer tests:<\/strong> email sequence offers, retargeting incentives<\/li>\n
                  • Bottom-of-funnel offer tests:<\/strong> checkout incentives, warranty language, payment plans<\/li>\n<\/ul>\n\n\n\n

                    By audience strategy<\/h3>\n\n\n\n
                      \n
                    • Broad tests:<\/strong> one offer for all visitors (good for learning and simplicity)<\/li>\n
                    • Segmented tests:<\/strong> different offers by device, geo, new vs returning, or intent level (higher complexity, higher potential lift)<\/li>\n<\/ul>\n\n\n\n

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

                      Example 1: SaaS pricing page (trial vs demo-first)<\/h3>\n\n\n\n

                      A B2B SaaS company runs an Offer Test where Variant A leads with \u201cStart a 14-day free trial,\u201d while Variant B leads with \u201cBook a 20-minute demo + get a custom setup plan.\u201d In Conversion & Measurement<\/strong>, they track not just sign-ups, but activation rate and qualified pipeline. In CRO<\/strong>, the winning offer may be the one that produces fewer sign-ups but more sales-qualified opportunities and higher close rate.<\/p>\n\n\n\n

                      Example 2: Ecommerce bundle vs discount<\/h3>\n\n\n\n

                      An ecommerce brand tests \u201cBuy 2, get 15% off\u201d against \u201cBuy 2, get a free accessory.\u201d The Offer Test measures conversion rate, average order value, and gross margin. In Conversion & Measurement<\/strong>, the key is aligning incentives with profitability; in CRO<\/strong>, the best variant is often the one that increases contribution margin per visitor, not just conversion.<\/p>\n\n\n\n

                      Example 3: Lead generation for a service business<\/h3>\n\n\n\n

                      A local service provider tests two offers on the same landing page template: (A) \u201cFree inspection + quote\u201d vs (B) \u201c$99 diagnostic credited toward service.\u201d The Offer Test tracks lead submission rate, show-up rate, close rate, and average job value. In Conversion & Measurement<\/strong>, offline conversion integration matters; in CRO<\/strong>, this prevents \u201cwinning\u201d an offer that generates many low-intent leads.<\/p>\n\n\n\n

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

                      A well-run Offer Test program can deliver compounding benefits across marketing and product.<\/p>\n\n\n\n

                        \n
                      • Higher conversion efficiency:<\/strong> Better offers reduce hesitation and increase action rates at key funnel steps.<\/li>\n
                      • Improved revenue per visitor:<\/strong> Offer changes can lift average order value or upgrade rates.<\/li>\n
                      • Lower acquisition costs (effective CAC):<\/strong> When conversion improves, you can spend less per outcome or scale profitably.<\/li>\n
                      • Better lead quality:<\/strong> Offer structure can filter out low-intent leads and attract the right customers.<\/li>\n
                      • Clearer positioning:<\/strong> Learn which value angles resonate, improving copy, ads, and sales enablement.<\/li>\n
                      • Customer experience improvements:<\/strong> Offers that reduce complexity (simple tiers, clear guarantees) make decisions easier.<\/li>\n<\/ul>\n\n\n\n

                        In Conversion & Measurement<\/strong>, these benefits show up as improved unit economics; in CRO<\/strong>, they translate into sustainable optimization rather than short-lived gimmicks.<\/p>\n\n\n\n

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

                        Offer Test is powerful, but it\u2019s also easy to misread if measurement and operations are weak.<\/p>\n\n\n\n

                          \n
                        • Confounding variables:<\/strong> Seasonality, promotions, inventory issues, or simultaneous site changes can distort results.<\/li>\n
                        • Measurement gaps:<\/strong> Poor event tracking, inconsistent attribution, or missing offline outcomes create false winners.<\/li>\n
                        • Profitability blind spots:<\/strong> Discounts may lift conversion while reducing margin or increasing churn.<\/li>\n
                        • Audience contamination:<\/strong> Users seeing multiple variants across devices or sessions can reduce test validity.<\/li>\n
                        • Brand risk:<\/strong> Aggressive discounting can train customers to wait for promos or damage perceived quality.<\/li>\n
                        • Operational constraints:<\/strong> Legal, finance, and pricing approvals can slow iteration; some offers are hard to implement quickly.<\/li>\n<\/ul>\n\n\n\n

                          Strong Conversion & Measurement<\/strong> governance and CRO<\/strong> prioritization are what make these challenges manageable.<\/p>\n\n\n\n

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

                          Start with a clear hypothesis tied to a barrier<\/h3>\n\n\n\n

                          Instead of \u201clet\u2019s test a discount,\u201d define the reason: \u201cVisitors hesitate due to perceived risk; a stronger guarantee will increase completed purchases without increasing refunds.\u201d<\/p>\n\n\n\n

                          Choose metrics that reflect business truth<\/h3>\n\n\n\n

                          Primary metric examples:\n– Ecommerce: contribution margin per visitor, revenue per visitor\n– SaaS: activated trials, paid conversion, churn-adjusted LTV\n– Lead gen: qualified leads, booked appointments, close rate<\/p>\n\n\n\n

                          Guardrails:\n– Refund rate, churn, support tickets, average discount depth<\/p>\n\n\n\n

                          Limit simultaneous changes<\/h3>\n\n\n\n

                          An Offer Test should isolate the offer. If you redesign the page at the same time, you won\u2019t know what caused the lift.<\/p>\n\n\n\n

                          Ensure clean audience assignment<\/h3>\n\n\n\n

                          Use consistent bucketing across sessions where possible, and avoid running overlapping experiments on the same pages that change pricing or checkout logic.<\/p>\n\n\n\n

                          Segment only after you prove a baseline winner<\/h3>\n\n\n\n

                          First validate a winner broadly, then consider segmentation (e.g., new vs returning). This keeps CRO<\/strong> learning clean and reduces overfitting.<\/p>\n\n\n\n

                          Document and operationalize<\/h3>\n\n\n\n

                          Record the offer details, audiences, dates, traffic sources, and outcomes. In Conversion & Measurement<\/strong>, institutional memory prevents repeated mistakes and speeds future testing.<\/p>\n\n\n\n

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

                          Offer Test isn\u2019t dependent on any single platform, but it does require a tool stack that supports experimentation and trustworthy measurement.<\/p>\n\n\n\n

                            \n
                          • Analytics tools:<\/strong> to track funnel events, cohorts, retention, and revenue outcomes within Conversion & Measurement<\/strong><\/li>\n
                          • Experimentation platforms:<\/strong> to run A\/B tests, manage variants, and control traffic allocation for CRO<\/strong><\/li>\n
                          • Tag management and event tracking systems:<\/strong> to ensure consistent, auditable instrumentation<\/li>\n
                          • CRM systems:<\/strong> to connect marketing offers to lead quality, pipeline, and customer value<\/li>\n
                          • Email and marketing automation:<\/strong> to test offer framing in sequences and lifecycle campaigns<\/li>\n
                          • Ad platforms:<\/strong> to test offer angles in creative and landing-page alignment (while controlling for targeting)<\/li>\n
                          • Reporting dashboards \/ BI:<\/strong> to unify test results with margin, refunds, churn, and segment performance<\/li>\n
                          • SEO tools (supporting role):<\/strong> to understand intent and landing page opportunities where an Offer Test can improve organic conversion outcomes<\/li>\n<\/ul>\n\n\n\n

                            The most important \u201ctool\u201d is a reliable measurement plan\u2014without it, Conversion & Measurement<\/strong> results won\u2019t be credible.<\/p>\n\n\n\n

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

                            Offer Test metrics should align to your business model and the stage of the funnel.<\/p>\n\n\n\n

                            Core performance metrics<\/h3>\n\n\n\n
                              \n
                            • Conversion rate (purchase, sign-up, lead)<\/li>\n
                            • Revenue per visitor (RPV) or average order value (AOV)<\/li>\n
                            • Lead-to-customer rate (for lead gen)<\/li>\n
                            • Trial-to-paid conversion (for SaaS)<\/li>\n<\/ul>\n\n\n\n

                              Profit and efficiency metrics<\/h3>\n\n\n\n
                                \n
                              • Contribution margin per visitor<\/li>\n
                              • Discount rate and effective price<\/li>\n
                              • CAC and payback period (when paired with channel spend)<\/li>\n
                              • Return on ad spend (ROAS) with caution (ensure incrementality assumptions)<\/li>\n<\/ul>\n\n\n\n

                                Quality and experience metrics<\/h3>\n\n\n\n
                                  \n
                                • Refund\/return rate<\/li>\n
                                • Churn and retention (logo and revenue churn)<\/li>\n
                                • Support ticket volume and satisfaction signals<\/li>\n
                                • Time to first value \/ activation rate<\/li>\n<\/ul>\n\n\n\n

                                  In CRO<\/strong>, the \u201cwinning\u201d offer is the one that improves the right metric without breaking guardrails. In Conversion & Measurement<\/strong>, success means the lift holds up across cohorts and time.<\/p>\n\n\n\n

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

                                  Offer Test is evolving as measurement and personalization change.<\/p>\n\n\n\n

                                    \n
                                  • AI-assisted offer ideation:<\/strong> AI can synthesize customer feedback and generate offer hypotheses, but human judgment is needed to protect margin, brand, and compliance.<\/li>\n
                                  • Automation and faster iteration:<\/strong> More teams will operationalize Offer Test pipelines\u2014rapid deployment, automated QA checks, and standardized reporting inside Conversion & Measurement<\/strong>.<\/li>\n
                                  • Personalized offers with constraints:<\/strong> Personalization will expand (by intent, lifecycle stage, or usage), but privacy limitations will push more on-site, first-party segmentation rather than third-party tracking.<\/li>\n
                                  • Incrementality focus:<\/strong> Organizations will demand stronger evidence that an offer change creates net-new value, not just shifts timing (e.g., pulling forward purchases with discounts).<\/li>\n
                                  • Pricing governance maturity:<\/strong> As Offer Test becomes central to CRO<\/strong>, finance and product teams will collaborate more closely to define boundaries, floors, and long-term effects.<\/li>\n<\/ul>\n\n\n\n

                                    The long-term direction is clear: Offer Test will be treated less as a one-off experiment and more as a continuous Conversion & Measurement<\/strong> capability.<\/p>\n\n\n\n

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

                                    Offer Test vs A\/B Test<\/h3>\n\n\n\n

                                    An A\/B test is a method. An Offer Test<\/strong> is the subject matter being tested (the deal). Offer tests often use A\/B methods, but not every A\/B test is an Offer Test\u2014many A\/B tests focus on UI, copy, or layout.<\/p>\n\n\n\n

                                    Offer Test vs Pricing Test<\/h3>\n\n\n\n

                                    Pricing tests focus specifically on price points and price architecture. An Offer Test is broader: it may include pricing, but also bundles, guarantees, bonuses, trials, and payment terms. In CRO<\/strong>, pricing tests are one subset of Offer Test.<\/p>\n\n\n\n

                                    Offer Test vs Message Test<\/h3>\n\n\n\n

                                    Message tests evaluate how you describe value (headlines, proof, positioning). Offer tests change the value exchange itself. In practice, Conversion & Measurement<\/strong> teams often pair message tests with Offer Test programs\u2014but separating them helps you learn what\u2019s driving impact.<\/p>\n\n\n\n

                                    Who Should Learn Offer Test<\/h2>\n\n\n\n
                                      \n
                                    • Marketers:<\/strong> to improve campaign profitability and align channel strategy with outcomes in Conversion & Measurement<\/strong><\/li>\n
                                    • Analysts:<\/strong> to design measurement plans, interpret results, and prevent false wins that mislead CRO<\/strong><\/li>\n
                                    • Agencies:<\/strong> to drive measurable client growth beyond creative changes by improving offer-market fit<\/li>\n
                                    • Business owners and founders:<\/strong> to refine pricing, packaging, and guarantees while protecting margin and brand<\/li>\n
                                    • Developers and product teams:<\/strong> to implement experiment infrastructure, pricing logic, and clean event tracking that make Offer Test results trustworthy<\/li>\n<\/ul>\n\n\n\n

                                      If you touch revenue, funnels, or analytics, Offer Test literacy is a practical advantage.<\/p>\n\n\n\n

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

                                      An Offer Test<\/strong> is the practice of experimentally comparing different offers\u2014pricing, bundles, incentives, and risk reducers\u2014to determine which version drives better outcomes. It matters because it influences the core purchase decision and can improve revenue, efficiency, and customer experience more than many surface-level changes. In Conversion & Measurement<\/strong>, Offer Test strengthens the link between marketing activity and business value. In CRO<\/strong>, it\u2019s a high-leverage testing category that can lift conversion rate while improving the unit economics that sustain growth.<\/p>\n\n\n\n

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

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

                                      An Offer Test<\/strong> compares different deal structures (price, bundle, trial, guarantee, bonus) to see which produces better business results. Run one when you have stable traffic, a clear conversion bottleneck, or evidence that perceived value or risk is blocking decisions.<\/p>\n\n\n\n

                                      2) How is Offer Test different from changing page design?<\/h3>\n\n\n\n

                                      Design changes affect presentation; Offer Test changes the terms of the value exchange. In CRO<\/strong>, offer changes often have larger impact, but they require stronger guardrails (margin, churn, refunds).<\/p>\n\n\n\n

                                      3) What\u2019s the best primary metric for Offer Test?<\/h3>\n\n\n\n

                                      Use a metric that reflects business value: revenue per visitor, contribution margin per visitor, qualified leads, or activated trials. In Conversion & Measurement<\/strong>, pair it with guardrails like refund rate or churn to avoid \u201cwinning\u201d the wrong way.<\/p>\n\n\n\n

                                      4) How long should an Offer Test run?<\/h3>\n\n\n\n

                                      Long enough to reach adequate sample size and cover typical variability (day-of-week effects, traffic mix). Many teams run tests for at least 1\u20132 full business cycles, but the right duration depends on conversion volume and volatility.<\/p>\n\n\n\n

                                      5) Can Offer Test hurt my brand or customer expectations?<\/h3>\n\n\n\n

                                      Yes. Frequent discounting can reduce perceived value and train customers to wait. A responsible Offer Test program sets boundaries (price floors, promo limits) and evaluates long-term effects in Conversion & Measurement<\/strong>.<\/p>\n\n\n\n

                                      6) What role does CRO play in Offer Test?<\/h3>\n\n\n\n

                                      CRO<\/strong> provides the experimentation discipline: hypothesis creation, test design, segmentation strategy, and outcome interpretation. Offer Test is one of the most valuable CRO levers when aligned with profitability and retention.<\/p>\n\n\n\n

                                      7) Should I segment Offer Test results by audience?<\/h3>\n\n\n\n

                                      Yes\u2014after you validate overall impact. Segmenting too early can produce misleading results. In Conversion & Measurement<\/strong>, segmenting is most useful for explaining why<\/em> an offer works (new vs returning, device, geo, intent), then deciding whether to personalize or standardize.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                      An **Offer Test** is the disciplined process of testing different versions of what you\u2019re asking customers to say \u201cyes\u201d to\u2014pricing, bundles, guarantees, trials, bonuses, shipping thresholds, payment plans, and positioning\u2014to identify which offer drives the best business outcomes. In **Conversion & Measurement**, it\u2019s one of the most direct ways to influence revenue because it changes the value exchange, not just the page layout.<\/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-7169","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\/7169","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=7169"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7169\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=7169"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=7169"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=7169"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}