{"id":11324,"date":"2026-04-01T18:02:17","date_gmt":"2026-04-01T18:02:17","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/ntb-rate\/"},"modified":"2026-04-01T18:02:17","modified_gmt":"2026-04-01T18:02:17","slug":"ntb-rate","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/ntb-rate\/","title":{"rendered":"Ntb Rate: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Shopping Ads"},"content":{"rendered":"\n

Ntb Rate is a practical way to understand how much of your growth in Paid Marketing<\/strong> is coming from new<\/em> customers rather than people who already know and buy from your brand. In the context of Shopping Ads<\/strong>, it helps answer a crucial question: are your product ads expanding your customer base, or mainly converting existing shoppers who would have purchased anyway?<\/p>\n\n\n\n

As acquisition costs rise and remarketing becomes less reliable due to privacy changes, modern Paid Marketing<\/strong> strategies increasingly prioritize customer growth quality\u2014not just volume. Tracking Ntb Rate<\/strong> gives teams a clearer view of whether Shopping Ads<\/strong> are driving real brand expansion, supporting long-term revenue, and improving the efficiency of prospecting budgets.<\/p>\n\n\n\n

What Is Ntb Rate?<\/h2>\n\n\n\n

Ntb Rate<\/strong> (often read as \u201cnew-to-brand rate\u201d) is the percentage of conversions or purchases attributed to shoppers who are classified as new<\/em> to your brand (or business) within a defined lookback window.<\/p>\n\n\n\n

At a high level:<\/p>\n\n\n\n

    \n
  • What it measures:<\/strong> the share of orders\/conversions coming from new customers<\/li>\n
  • Why it exists:<\/strong> to separate customer acquisition from repeat purchasing<\/li>\n
  • Where it fits:<\/strong> a core acquisition indicator inside Paid Marketing<\/strong><\/li>\n
  • How it applies to Shopping Ads:<\/strong> it evaluates whether Shopping Ads<\/strong> are prospecting effectively or primarily capturing existing demand<\/li>\n<\/ul>\n\n\n\n

    A simple way to express the concept is:<\/p>\n\n\n\n

      \n
    • Ntb Rate = New-to-brand conversions \u00f7 Total conversions<\/strong><\/li>\n<\/ul>\n\n\n\n

      The \u201cnew-to-brand\u201d classification depends on your measurement approach. Some teams use ad-platform-defined new customer logic; others use first-party data (CRM\/ecommerce history). Either way, Ntb Rate<\/strong> turns \u201cnew customer acquisition\u201d from a vague goal into a measurable performance outcome.<\/p>\n\n\n\n

      Why Ntb Rate Matters in Paid Marketing<\/h2>\n\n\n\n

      In Paid Marketing<\/strong>, optimizing only for ROAS or CPA can unintentionally overweight returning buyers, because they convert more easily. That can look efficient in-platform while failing to grow your market share. Ntb Rate<\/strong> adds strategic balance by revealing whether performance is coming from incremental customer acquisition or from harvesting existing customers.<\/p>\n\n\n\n

      Key reasons Ntb Rate<\/strong> matters:<\/p>\n\n\n\n

        \n
      • Protects long-term growth:<\/strong> New customers create future repeat revenue, subscriptions, and referrals.<\/li>\n
      • Improves budget allocation:<\/strong> It helps decide how much spend belongs in prospecting vs. retention.<\/li>\n
      • Clarifies channel roles:<\/strong> Shopping Ads<\/strong> may be doing brand capture, competitor conquesting, or true discovery\u2014Ntb Rate<\/strong> helps identify which.<\/li>\n
      • Strengthens competitive advantage:<\/strong> If your Ntb Rate<\/strong> is rising while maintaining margin, you\u2019re expanding your customer base more efficiently than competitors.<\/li>\n<\/ul>\n\n\n\n

        For ecommerce and retail, Shopping Ads<\/strong> are often the highest-intent format. That makes Ntb Rate<\/strong> especially important: high intent can mean you\u2019re winning new customers\u2014or simply intercepting buyers who already planned to purchase from you.<\/p>\n\n\n\n

        How Ntb Rate Works<\/h2>\n\n\n\n

        Ntb Rate<\/strong> is less about a mechanical \u201cprocess\u201d and more about a measurement workflow that turns identity and conversion data into an acquisition signal. In practice, it works like this:<\/p>\n\n\n\n

          \n
        1. \n

          Input (what triggers the metric)<\/strong>\n – A user clicks a Shopping ad (or another paid placement) and completes a purchase or conversion.\n – The conversion includes identifiers (order ID, email hash, user ID, platform user signals) depending on your setup.<\/p>\n<\/li>\n

        2. \n

          Processing (how \u201cnew\u201d is determined)<\/strong>\n – The system checks whether the buyer has purchased from your brand within a defined historical window (for example, the last 12 months).\n – Classification can be:<\/p>\n

            \n
          • Platform-defined<\/strong> (based on its own identity graph and purchase history it can observe), or<\/li>\n
          • First-party-defined<\/strong> (based on your ecommerce\/CRM records).<\/li>\n<\/ul>\n<\/li>\n
          • \n

            Application (where it\u2019s used in Paid Marketing)<\/strong>\n – You analyze Ntb Rate<\/strong> by campaign, product group, audience, device, geo, and creative\/feed attributes.\n – You pair it with profitability metrics to ensure you aren\u2019t buying new customers at an unsustainable cost.<\/p>\n<\/li>\n

          • \n

            Output (what you get)<\/strong>\n – A percentage showing how acquisition-heavy your results are.\n – A decision signal for bidding, targeting, creative strategy, and budget splits across Paid Marketing<\/strong> programs\u2014especially Shopping Ads<\/strong>.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

            Key Components of Ntb Rate<\/h2>\n\n\n\n

            To make Ntb Rate<\/strong> reliable and actionable, you need more than a single number. The most important components include:<\/p>\n\n\n\n

            Data inputs<\/h3>\n\n\n\n
              \n
            • Conversion events:<\/strong> purchases, leads, subscriptions, or qualified actions<\/li>\n
            • Customer identity signals:<\/strong> order\/customer IDs, hashed emails, login IDs, device\/user identifiers<\/li>\n
            • Historical purchase data:<\/strong> needed to determine if a customer is truly \u201cnew\u201d<\/li>\n
            • Product feed attributes (for Shopping Ads):<\/strong> category, price, brand, GTIN, variants, availability\u2014useful for diagnosing which items drive higher Ntb Rate<\/strong><\/li>\n<\/ul>\n\n\n\n

              Systems and processes<\/h3>\n\n\n\n
                \n
              • Attribution setup:<\/strong> consistent conversion windows and attribution logic<\/li>\n
              • Data governance:<\/strong> agreed definitions for \u201cnew customer\u201d and how exceptions are handled (returns, cancellations, guest checkout)<\/li>\n
              • Experimentation:<\/strong> tests to validate if higher Ntb Rate<\/strong> correlates with incremental growth<\/li>\n<\/ul>\n\n\n\n

                Team responsibilities<\/h3>\n\n\n\n
                  \n
                • Paid media managers:<\/strong> optimize campaigns and feed strategy to influence Ntb Rate<\/strong><\/li>\n
                • Analytics\/BI:<\/strong> validate measurement, deduplicate customers, and reconcile platform vs. first-party counts<\/li>\n
                • Lifecycle\/CRM teams:<\/strong> estimate downstream value (repeat rate, LTV) of acquired customers<\/li>\n<\/ul>\n\n\n\n

                  Types of Ntb Rate<\/h2>\n\n\n\n

                  There aren\u2019t universally standardized \u201ctypes,\u201d but there are important distinctions that change how Ntb Rate<\/strong> should be interpreted:<\/p>\n\n\n\n

                  Platform-defined vs. first-party-defined Ntb Rate<\/h3>\n\n\n\n
                    \n
                  • Platform-defined:<\/strong> easier to access, consistent within the platform, but may not match your true customer file.<\/li>\n
                  • First-party-defined:<\/strong> closer to your business reality, but requires identity resolution and strong data hygiene.<\/li>\n<\/ul>\n\n\n\n

                    New-to-brand vs. new-to-business (definition scope)<\/h3>\n\n\n\n
                      \n
                    • New-to-brand:<\/strong> customer is new to your brand<\/em>.<\/li>\n
                    • New-to-business:<\/strong> customer is new to your store\/business entity<\/em> (sometimes broader, depending on how brands\/shops are structured).<\/li>\n<\/ul>\n\n\n\n

                      Order-based vs. customer-based Ntb Rate<\/h3>\n\n\n\n
                        \n
                      • Order-based:<\/strong> % of orders that are new-to-brand.<\/li>\n
                      • Customer-based:<\/strong> % of unique purchasers who are new-to-brand.\nOrder-based metrics can be skewed if new customers place multiple orders quickly or if bundling differs by segment.<\/li>\n<\/ul>\n\n\n\n

                        Observed vs. incremental Ntb Rate<\/h3>\n\n\n\n
                          \n
                        • Observed Ntb Rate:<\/strong> what reporting shows (new customers happened).<\/li>\n
                        • Incremental Ntb Rate:<\/strong> what happened because of ads<\/em> (requires testing or incrementality methods).\nIn Paid Marketing<\/strong>, this distinction matters because some \u201cnew\u201d customers may have arrived organically anyway.<\/li>\n<\/ul>\n\n\n\n

                          Real-World Examples of Ntb Rate<\/h2>\n\n\n\n

                          Example 1: Ecommerce brand balancing ROAS and acquisition in Shopping Ads<\/h3>\n\n\n\n

                          A mid-sized apparel brand runs Shopping Ads<\/strong> and sees strong ROAS, but growth stalls. When they segment performance, they find branded queries and best-seller SKUs have a low Ntb Rate<\/strong>, suggesting many conversions are from existing customers.<\/p>\n\n\n\n

                          They restructure:\n– Separate campaigns for branded vs. non-branded intent\n– Increase bids and budget for category-level searches and new-season collections\n– Use feed titles and imagery to emphasize differentiation<\/p>\n\n\n\n

                          Outcome: Slightly lower ROAS, meaningfully higher Ntb Rate<\/strong>, and healthier net-new customer growth\u2014an intentional Paid Marketing<\/strong> tradeoff.<\/p>\n\n\n\n

                          Example 2: High-AOV product using Ntb Rate to avoid \u201ccheap\u201d conversions<\/h3>\n\n\n\n

                          A premium home goods retailer notices remarketing-heavy Shopping Ads<\/strong> deliver low CPA but low Ntb Rate<\/strong>. They introduce an acquisition-focused structure:\n– Prospecting-only audiences (excluding recent purchasers)\n– Product groups prioritized for \u201cfirst purchase\u201d suitability (starter items, giftable bundles)\n– Landing pages built for first-time buyers (clear value prop, shipping\/returns, reviews)<\/p>\n\n\n\n

                          Result: Ntb Rate<\/strong> increases while protecting margin by steering new customers toward high-converting entry products.<\/p>\n\n\n\n

                          Example 3: Marketplace seller diagnosing product-level acquisition<\/h3>\n\n\n\n

                          A brand selling multiple lines finds that one category drives high volume but low Ntb Rate<\/strong>\u2014it\u2019s mostly repeat replenishment. Another category has a smaller volume but a very high Ntb Rate<\/strong>.<\/p>\n\n\n\n

                          They adjust Paid Marketing<\/strong> mix:\n– Keep replenishment category efficient with tighter bids and inventory controls\n– Scale the higher Ntb Rate<\/strong> category with broader targeting and more coverage in Shopping Ads<\/strong><\/p>\n\n\n\n

                          This shifts spend toward products that bring new customers into the brand ecosystem.<\/p>\n\n\n\n

                          Benefits of Using Ntb Rate<\/h2>\n\n\n\n

                          Using Ntb Rate<\/strong> as a decision metric creates tangible improvements across performance and planning:<\/p>\n\n\n\n

                            \n
                          • Better acquisition efficiency:<\/strong> You can optimize campaigns to attract first-time buyers rather than over-serving repeat purchasers.<\/li>\n
                          • Smarter budget splits:<\/strong> It becomes easier to justify prospecting spend even when ROAS is lower than remarketing.<\/li>\n
                          • Clearer customer growth reporting:<\/strong> Executives care about new customers; Ntb Rate<\/strong> translates Paid Marketing<\/strong> activity into that language.<\/li>\n
                          • Improved product strategy in Shopping Ads:<\/strong> You can identify which SKUs and categories act as \u201ccustomer openers.\u201d<\/li>\n
                          • Stronger customer experience:<\/strong> Acquisition-focused ads and landing pages often provide clearer messaging for first-time shoppers.<\/li>\n<\/ul>\n\n\n\n

                            Challenges of Ntb Rate<\/h2>\n\n\n\n

                            Ntb Rate<\/strong> is powerful, but it\u2019s not a perfect metric. Common issues include:<\/p>\n\n\n\n

                              \n
                            • Definition inconsistency:<\/strong> Different teams (or platforms) may define \u201cnew\u201d differently (30 days vs. 12 months; brand vs. business).<\/li>\n
                            • Identity resolution gaps:<\/strong> Guest checkout, cookie loss, and cross-device behavior can misclassify returning customers as new.<\/li>\n
                            • Attribution bias:<\/strong> Shopping Ads<\/strong> often capture lower-funnel intent; a high Ntb Rate<\/strong> may still reflect demand created elsewhere.<\/li>\n
                            • Delayed or partial reporting:<\/strong> Some systems provide new-customer labeling with lag or only at certain aggregation levels.<\/li>\n
                            • Profitability risk:<\/strong> Chasing a higher Ntb Rate<\/strong> can raise CPA\/CAC if you don\u2019t pair it with margin and LTV analysis.<\/li>\n
                            • Incrementality uncertainty:<\/strong> Observed Ntb Rate<\/strong> does not automatically mean incremental growth without testing.<\/li>\n<\/ul>\n\n\n\n

                              Best Practices for Ntb Rate<\/h2>\n\n\n\n

                              To use Ntb Rate<\/strong> effectively in Paid Marketing<\/strong> and Shopping Ads<\/strong>, focus on practices that improve both measurement and decision-making:<\/p>\n\n\n\n

                                \n
                              1. \n

                                Standardize your definition<\/strong>\n – Choose a lookback window that fits your purchase cycle (e.g., 180\/365 days).\n – Document how you handle returns, exchanges, and order cancellations.<\/p>\n<\/li>\n

                              2. \n

                                Segment Ntb Rate, don\u2019t average it<\/strong>\n – Break down by campaign type (brand vs. non-brand), product category, price point, device, and geo.\n – In Shopping Ads<\/strong>, also segment by feed attributes (brand, product type, custom labels).<\/p>\n<\/li>\n

                              3. \n

                                Pair Ntb Rate with unit economics<\/strong>\n – Monitor CAC, contribution margin, and payback period alongside Ntb Rate<\/strong>.\n – A rising Ntb Rate<\/strong> is only \u201cgood\u201d if the customers are economically viable.<\/p>\n<\/li>\n

                              4. \n

                                Use exclusions thoughtfully<\/strong>\n – Exclude recent purchasers in acquisition campaigns where appropriate.\n – Keep a separate retention structure so returning customers still have a path to convert efficiently.<\/p>\n<\/li>\n

                              5. \n

                                Optimize for first purchase success<\/strong>\n – Promote \u201cstarter\u201d products, bundles, and clear value propositions.\n – Improve landing pages for first-time buyers (trust signals, shipping clarity, reviews).<\/p>\n<\/li>\n

                              6. \n

                                Validate with experiments<\/strong>\n – Use geo tests, holdouts, or budget split tests to estimate incrementality.\n – Treat Ntb Rate<\/strong> as a directional KPI unless validated against experiments.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                                Tools Used for Ntb Rate<\/h2>\n\n\n\n

                                You don\u2019t need a single \u201cNtb Rate tool,\u201d but you do need a connected measurement stack. Common tool categories include:<\/p>\n\n\n\n

                                  \n
                                • Ad platforms and retail media consoles:<\/strong> Provide conversion and (sometimes) new-customer classification for Shopping Ads<\/strong> and other Paid Marketing<\/strong> channels.<\/li>\n
                                • Web analytics tools:<\/strong> Help connect session behavior and assisted conversions to acquisition outcomes.<\/li>\n
                                • Tag management and server-side tracking:<\/strong> Improve conversion signal quality and reduce loss from browser restrictions.<\/li>\n
                                • CRM and ecommerce platforms:<\/strong> Source of truth for purchase history and customer status.<\/li>\n
                                • CDPs \/ identity resolution systems:<\/strong> Help deduplicate users across devices and channels.<\/li>\n
                                • Data warehouse + BI dashboards:<\/strong> Combine ad spend, conversions, and customer history into a consistent Ntb Rate<\/strong> reporting layer.<\/li>\n
                                • Feed management systems (for Shopping Ads):<\/strong> Enable product labeling (e.g., \u201cnew customer friendly,\u201d \u201chigh margin\u201d) to operationalize Ntb Rate<\/strong> optimization.<\/li>\n<\/ul>\n\n\n\n

                                  Metrics Related to Ntb Rate<\/h2>\n\n\n\n

                                  Ntb Rate<\/strong> becomes far more actionable when monitored with adjacent metrics that explain cost, value, and quality:<\/p>\n\n\n\n

                                    \n
                                  • New customer conversions \/ orders:<\/strong> the numerator behind Ntb Rate<\/strong><\/li>\n
                                  • Customer Acquisition Cost (CAC):<\/strong> cost per new customer (often more meaningful than CPA)<\/li>\n
                                  • New customer ROAS:<\/strong> revenue from new customers \u00f7 spend (use carefully; consider margins)<\/li>\n
                                  • Contribution margin per new customer:<\/strong> profitability signal, especially for Shopping Ads<\/strong><\/li>\n
                                  • Repeat purchase rate \/ retention:<\/strong> whether new customers return<\/li>\n
                                  • Estimated LTV (cohort-based):<\/strong> long-term value of customers acquired via Paid Marketing<\/strong><\/li>\n
                                  • Conversion rate and AOV by new vs. returning:<\/strong> reveals whether you\u2019re attracting the right first-time buyers<\/li>\n
                                  • Incrementality lift (test-based):<\/strong> validates whether higher Ntb Rate<\/strong> equals real growth<\/li>\n<\/ul>\n\n\n\n

                                    Future Trends of Ntb Rate<\/h2>\n\n\n\n

                                    Several shifts are making Ntb Rate<\/strong> more central to how Paid Marketing<\/strong> is planned and optimized:<\/p>\n\n\n\n

                                      \n
                                    • AI-driven bidding toward acquisition goals:<\/strong> Automated optimization is increasingly able to target \u201cnew customer\u201d outcomes, pushing teams to define and validate Ntb Rate<\/strong> properly.<\/li>\n
                                    • More first-party measurement:<\/strong> As privacy constraints reduce third-party identifiers, brands will lean on CRM and server-side signals to calculate Ntb Rate<\/strong> consistently.<\/li>\n
                                    • Cohort-based reporting:<\/strong> Expect greater emphasis on post-acquisition quality (retention and margin by cohort), not just the initial Ntb Rate<\/strong>.<\/li>\n
                                    • More structured product strategy in Shopping Ads:<\/strong> Feeds will be managed not only for ROAS, but also for acquisition propensity (entry products, bundles, high-intent categories).<\/li>\n
                                    • Incrementality as a requirement:<\/strong> Leadership teams will increasingly ask whether new customers are incremental, forcing Ntb Rate<\/strong> to be paired with experimentation.<\/li>\n<\/ul>\n\n\n\n

                                      Ntb Rate vs Related Terms<\/h2>\n\n\n\n

                                      Understanding nearby metrics prevents misinterpretation:<\/p>\n\n\n\n

                                      Ntb Rate vs New Customer Rate<\/h3>\n\n\n\n

                                      They\u2019re often used interchangeably, but \u201cnew customer\u201d can mean new to a store\/account, while Ntb Rate<\/strong> usually implies new to the brand<\/em> within a defined window. The key is the definition and the data source behind the label.<\/p>\n\n\n\n

                                      Ntb Rate vs CAC (Customer Acquisition Cost)<\/h3>\n\n\n\n
                                        \n
                                      • Ntb Rate<\/strong> tells you mix<\/em> (what portion of conversions are new).<\/li>\n
                                      • CAC<\/strong> tells you cost<\/em> (what you paid per new customer).\nA campaign can have a high Ntb Rate<\/strong> but unacceptable CAC\u2014so you need both.<\/li>\n<\/ul>\n\n\n\n

                                        Ntb Rate vs Conversion Rate<\/h3>\n\n\n\n

                                        Conversion rate measures how efficiently clicks become purchases. Ntb Rate<\/strong> measures who those purchasers are (new vs. returning). In Shopping Ads<\/strong>, you can raise conversion rate by leaning into returning buyers, while Ntb Rate<\/strong> may decline.<\/p>\n\n\n\n

                                        Who Should Learn Ntb Rate<\/h2>\n\n\n\n

                                        Ntb Rate<\/strong> is useful across roles because it bridges campaign performance and business growth:<\/p>\n\n\n\n

                                          \n
                                        • Marketers:<\/strong> to balance ROAS with acquisition and build a sustainable Paid Marketing<\/strong> engine<\/li>\n
                                        • Analysts:<\/strong> to standardize definitions, reconcile data sources, and build trustworthy dashboards<\/li>\n
                                        • Agencies:<\/strong> to prove they\u2019re delivering customer growth\u2014not just reallocating demand<\/li>\n
                                        • Business owners\/founders:<\/strong> to connect Shopping Ads<\/strong> spend to long-term customer base expansion<\/li>\n
                                        • Developers\/data engineers:<\/strong> to implement identity stitching, event pipelines, and reliable new-customer classification<\/li>\n<\/ul>\n\n\n\n

                                          Summary of Ntb Rate<\/h2>\n\n\n\n

                                          Ntb Rate<\/strong> measures the percentage of conversions coming from new-to-brand customers. In Paid Marketing<\/strong>, it\u2019s a critical acquisition KPI that prevents over-optimizing toward easy conversions from existing buyers. Within Shopping Ads<\/strong>, Ntb Rate<\/strong> helps you understand whether product ads are expanding your audience, which products drive first purchases, and how to allocate budget between growth and retention.<\/p>\n\n\n\n

                                          Used with CAC, margin, and retention metrics, Ntb Rate<\/strong> becomes a practical guide for scaling customer growth responsibly.<\/p>\n\n\n\n

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

                                          1) What is Ntb Rate and how is it calculated?<\/h3>\n\n\n\n

                                          Ntb Rate<\/strong> is the share of conversions or orders from customers classified as new to your brand within a defined lookback window. A common calculation is new-to-brand conversions divided by total conversions.<\/p>\n\n\n\n

                                          2) What\u2019s a \u201cgood\u201d Ntb Rate for Shopping Ads?<\/h3>\n\n\n\n

                                          There\u2019s no universal benchmark. A \u201cgood\u201d Ntb Rate<\/strong> depends on category competition, brand maturity, price point, and how much branded vs. non-branded demand your Shopping Ads<\/strong> capture. Track trends over time and compare across campaign segments rather than chasing a single target.<\/p>\n\n\n\n

                                          3) Why did my ROAS go down when I tried to increase Ntb Rate?<\/h3>\n\n\n\n

                                          New customers usually require more persuasion and higher acquisition costs, so ROAS can drop as Ntb Rate<\/strong> rises. In Paid Marketing<\/strong>, that tradeoff can be healthy if CAC, margin, and repeat purchase behavior stay within your targets.<\/p>\n\n\n\n

                                          4) Can Ntb Rate be measured with first-party data?<\/h3>\n\n\n\n

                                          Yes. Many teams compute Ntb Rate<\/strong> by matching conversion events to CRM or ecommerce purchase history and labeling customers as new or returning based on a defined timeframe. This often improves consistency across channels.<\/p>\n\n\n\n

                                          5) How do I improve Ntb Rate in Shopping Ads without overspending?<\/h3>\n\n\n\n

                                          Start by segmenting branded vs. non-branded, excluding recent purchasers in acquisition campaigns, and prioritizing entry-level products or bundles that convert first-time buyers. Then monitor CAC and contribution margin alongside Ntb Rate<\/strong> to keep growth efficient.<\/p>\n\n\n\n

                                          6) Does a higher Ntb Rate always mean incremental growth?<\/h3>\n\n\n\n

                                          Not necessarily. Ntb Rate<\/strong> indicates that the customer is new, but it doesn\u2019t prove the ad caused the acquisition. Use experiments (holdouts or geo tests) to estimate incrementality in your Paid Marketing<\/strong> program.<\/p>\n\n\n\n

                                          7) What reporting breakdowns make Ntb Rate most actionable?<\/h3>\n\n\n\n

                                          The most useful views are Ntb Rate<\/strong> by campaign objective, product category\/SKU group, device, geography, and audience type. For Shopping Ads<\/strong>, adding feed-attribute breakdowns (product type, price bands, custom labels) often reveals the fastest optimization opportunities.<\/p>\n","protected":false},"excerpt":{"rendered":"

                                          Ntb Rate is a practical way to understand how much of your growth in **Paid Marketing** is coming from *new* customers rather than people who already know and buy from your brand. In the context of **Shopping Ads**, it helps answer a crucial question: are your product ads expanding your customer base, or mainly converting existing shoppers who would have purchased anyway?<\/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":[1914],"tags":[],"class_list":["post-11324","post","type-post","status-publish","format-standard","hentry","category-shopping-ads"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/11324","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=11324"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/11324\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=11324"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=11324"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=11324"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}