{"id":7072,"date":"2026-03-23T23:16:41","date_gmt":"2026-03-23T23:16:41","guid":{"rendered":"https:\/\/www.wizbrand.com\/tutorials\/weighted-pipeline-influence\/"},"modified":"2026-03-23T23:16:41","modified_gmt":"2026-03-23T23:16:41","slug":"weighted-pipeline-influence","status":"publish","type":"post","link":"https:\/\/www.wizbrand.com\/tutorials\/weighted-pipeline-influence\/","title":{"rendered":"Weighted Pipeline Influence: What It Is, Key Features, Benefits, Use Cases, and How It Fits in Attribution"},"content":{"rendered":"\n

Weighted Pipeline Influence is a way to quantify how marketing and sales touchpoints contribute to pipeline creation by assigning a proportional \u201cinfluence weight\u201d to each touch. In Conversion & Measurement<\/strong>, it helps teams move beyond binary thinking (\u201cthis campaign sourced the deal\u201d vs. \u201cit didn\u2019t\u201d) and instead measure how much<\/em> a channel, campaign, or interaction shaped pipeline outcomes. It\u2019s especially valuable in Attribution<\/strong>, where the goal is to distribute credit across multiple touches rather than over-crediting only the first or last interaction.<\/p>\n\n\n\n

Modern buying journeys are fragmented: prospects might discover a brand through SEO, attend a webinar months later, engage with retargeting ads, and then talk to sales. Weighted Pipeline Influence<\/strong> matters because it turns that messy journey into measurable influence that can be analyzed, reported, and optimized\u2014making Conversion & Measurement<\/strong> more realistic, and Attribution<\/strong> more defensible for budgeting and forecasting.<\/p>\n\n\n\n

What Is Weighted Pipeline Influence?<\/h2>\n\n\n\n

Weighted Pipeline Influence<\/strong> is a measurement concept that assigns a defined share of pipeline value to marketing (and sometimes sales) touches that occurred during a buyer\u2019s journey. Instead of counting \u201cinfluenced pipeline\u201d as a simple yes\/no flag, it estimates influence proportionally<\/em> by applying weights based on an Attribution<\/strong> approach (for example, weighting early discovery touches differently than late-stage conversion touches).<\/p>\n\n\n\n

At its core, it answers: \u201cHow much pipeline should we attribute to each touchpoint, channel, or campaign\u2014given that multiple interactions contributed?\u201d<\/em><\/p>\n\n\n\n

From a business standpoint, Weighted Pipeline Influence<\/strong> helps leaders understand:\n– Which programs are consistently involved in creating pipeline, not just closing it\n– Where to invest to generate future revenue, not merely capture demand at the end\n– How marketing assists sales across the funnel in Conversion & Measurement<\/strong><\/p>\n\n\n\n

Within Conversion & Measurement<\/strong>, it sits between activity metrics (clicks, sessions, MQLs) and revenue metrics (closed-won). In Attribution<\/strong>, it\u2019s one practical way to translate multi-touch journeys into allocatable pipeline value that finance and leadership can use.<\/p>\n\n\n\n

Why Weighted Pipeline Influence Matters in Conversion & Measurement<\/h2>\n\n\n\n

In many organizations, measurement breaks down when stakeholders ask, \u201cWhat did marketing really<\/em> contribute?\u201d Weighted Pipeline Influence<\/strong> matters because it provides a structured answer that acknowledges reality: most meaningful deals involve multiple touches.<\/p>\n\n\n\n

Strategically, it supports better decisions in Conversion & Measurement<\/strong> by:\n– Reducing over-reliance on last-touch metrics that favor late-stage channels\n– Improving budget allocation by valuing upper- and mid-funnel activity appropriately\n– Helping teams understand which messages and offers move opportunities forward<\/p>\n\n\n\n

It also creates business value by connecting program performance to pipeline with nuance<\/em>. When leadership sees credible Attribution<\/strong> logic behind the numbers, marketing earns more trust, more budget stability, and clearer accountability.<\/p>\n\n\n\n

Competitive advantage comes from faster learning loops: teams using Weighted Pipeline Influence<\/strong> can spot patterns (e.g., webinars accelerate late-stage velocity; certain SEO topics drive higher deal sizes) and respond sooner than competitors who only track last click or sourced pipeline.<\/p>\n\n\n\n

How Weighted Pipeline Influence Works<\/h2>\n\n\n\n

Weighted Pipeline Influence<\/strong> is often implemented as a practical workflow rather than a single formula. A typical approach looks like this:<\/p>\n\n\n\n

    \n
  1. \n

    Inputs (touchpoints and pipeline events)<\/strong>\n You start with trackable touches (ad clicks, email engagement, content views, event attendance, SDR meetings) and pipeline milestones (opportunity created, stage changes, amount changes). These inputs must be reliably tied to accounts\/contacts and opportunities for Conversion & Measurement<\/strong> to work.<\/p>\n<\/li>\n

  2. \n

    Processing (identity, timelines, and weighting logic)<\/strong>\n Touchpoints are stitched together into a journey (at contact or account level). Then a weighting model is applied\u2014an Attribution<\/strong> rule set that determines how influence is distributed. For example, you might assign more weight to the first meaningful touch and to the touch closest to opportunity creation, with the remainder spread across middle touches.<\/p>\n<\/li>\n

  3. \n

    Application (aggregation and reporting)<\/strong>\n The weighted influence is rolled up by channel, campaign, content theme, audience segment, or region. This creates reports like \u201cweighted influenced pipeline by channel\u201d or \u201cpipeline influence by campaign cohort,\u201d which are central to Conversion & Measurement<\/strong> reviews.<\/p>\n<\/li>\n

  4. \n

    Outputs (budget and optimization decisions)<\/strong>\n The outcome is not just a dashboard\u2014it\u2019s action: reallocating spend, adjusting messaging, improving nurture sequences, prioritizing sales enablement, and setting more realistic targets based on how influence behaves over time.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

    Importantly, Weighted Pipeline Influence<\/strong> doesn\u2019t claim perfect causality. It\u2019s a disciplined estimation method used in Attribution<\/strong> to approximate contribution in complex, multi-touch buying cycles.<\/p>\n\n\n\n

    Key Components of Weighted Pipeline Influence<\/h2>\n\n\n\n

    Strong Weighted Pipeline Influence<\/strong> measurement depends on a few foundational elements:<\/p>\n\n\n\n

    Data inputs<\/h3>\n\n\n\n
      \n
    • Touchpoint data:<\/strong> web sessions, form fills, email interactions, paid media engagements, event participation, meetings<\/li>\n
    • CRM opportunity data:<\/strong> opportunity creation date, stages, amount, close date, owner, account<\/li>\n
    • Identity data:<\/strong> contact IDs, account IDs, deduped email domains, mapping rules<\/li>\n
    • Cost data:<\/strong> campaign spend, event costs, content production cost (optional but powerful)<\/li>\n<\/ul>\n\n\n\n

      Systems and processes<\/h3>\n\n\n\n
        \n
      • CRM governance:<\/strong> consistent opportunity creation rules, stage definitions, and required fields<\/li>\n
      • Marketing operations:<\/strong> clean campaign taxonomy, UTMs, and lifecycle tracking<\/li>\n
      • Data pipelines:<\/strong> reliable sync between marketing platforms and CRM<\/li>\n
      • Measurement cadence:<\/strong> monthly\/quarterly Conversion & Measurement<\/strong> reviews to validate assumptions<\/li>\n<\/ul>\n\n\n\n

        Ownership and responsibilities<\/h3>\n\n\n\n
          \n
        • Marketing ops ensures tracking integrity and taxonomy<\/li>\n
        • Sales ops enforces pipeline hygiene and stage consistency<\/li>\n
        • Analytics defines the Attribution<\/strong> model, validates outputs, and documents methodology<\/li>\n
        • Leaders align on what \u201cinfluence\u201d means and how it will be used (and not misused)<\/li>\n<\/ul>\n\n\n\n

          Types of Weighted Pipeline Influence<\/h2>\n\n\n\n

          There aren\u2019t universally standardized \u201ctypes,\u201d but there are common approaches and contexts that function like variants:<\/p>\n\n\n\n

          1) Model-based weighting (rule-driven)<\/h3>\n\n\n\n

          Weights are assigned using a chosen Attribution<\/strong> model such as:\n– Position-based (e.g., heavier weight on early and late touches)\n– Time-decay (more credit to recent touches)\n– Linear (equal weight across touches)<\/p>\n\n\n\n

          This is the most common implementation of Weighted Pipeline Influence<\/strong> in Conversion & Measurement<\/strong> because it\u2019s explainable and operationally feasible.<\/p>\n\n\n\n

          2) Stage-based weighting (funnel-aligned)<\/h3>\n\n\n\n

          Weights are tied to funnel stages or milestones:\n– Higher influence when touches occur near opportunity creation\n– Additional influence when touches correlate with stage progression (e.g., from discovery to evaluation)<\/p>\n\n\n\n

          This is useful when you want Weighted Pipeline Influence<\/strong> to reflect pipeline movement, not just pipeline creation.<\/p>\n\n\n\n

          3) Account-based weighting (B2B buying groups)<\/h3>\n\n\n\n

          Influence is measured at the account level, recognizing that multiple contacts contribute. This is especially relevant in enterprise sales where Attribution<\/strong> must reflect buying committees and long cycles.<\/p>\n\n\n\n

          Real-World Examples of Weighted Pipeline Influence<\/h2>\n\n\n\n

          Example 1: B2B SaaS balancing demand gen and brand<\/h3>\n\n\n\n

          A SaaS company finds that paid search looks \u201cbest\u201d in last-touch reporting. After implementing Weighted Pipeline Influence<\/strong>, they discover organic content and webinars appear earlier in journeys and collectively account for a large share of weighted influenced pipeline. In Conversion & Measurement<\/strong> reviews, they protect top-of-funnel content investment instead of cutting it. Their Attribution<\/strong> story becomes more accurate: paid search captures demand, but content and events create it.<\/p>\n\n\n\n

          Example 2: Agency proving impact across a mixed channel plan<\/h3>\n\n\n\n

          An agency runs SEO, LinkedIn ads, and email nurture for a client. Only some opportunities are \u201csourced\u201d by marketing, causing budget pressure. Using Weighted Pipeline Influence<\/strong>, they show that even when sales creates the opportunity, marketing touches contributed meaningful weight to pipeline creation and acceleration. In Conversion & Measurement<\/strong>, the client can see influence by campaign and cohort, improving retention and decision-making grounded in transparent Attribution<\/strong> logic.<\/p>\n\n\n\n

          Example 3: Product-led company measuring pipeline from self-serve to sales-led<\/h3>\n\n\n\n

          A product-led business tracks in-product events and content consumption before users request demos. With Weighted Pipeline Influence<\/strong>, they assign weights to product activation milestones, key content touches, and the demo request. The model clarifies which activation experiences correlate with higher pipeline amounts. This improves Conversion & Measurement<\/strong> for both product and marketing, and strengthens Attribution<\/strong> beyond ad-only thinking.<\/p>\n\n\n\n

          Benefits of Using Weighted Pipeline Influence<\/h2>\n\n\n\n

          Weighted Pipeline Influence<\/strong> improves performance and clarity in several ways:<\/p>\n\n\n\n

            \n
          • Better budget allocation:<\/strong> It reduces the bias toward only last-stage channels, improving spend efficiency across the funnel in Conversion & Measurement<\/strong>.<\/li>\n
          • More credible pipeline reporting:<\/strong> Leaders see proportional contribution rather than inflated \u201cinfluenced\u201d counts, making Attribution<\/strong> more trustworthy.<\/li>\n
          • Improved funnel optimization:<\/strong> Teams can optimize for journey impact (assist value), not just immediate conversions.<\/li>\n
          • Cross-team alignment:<\/strong> Marketing and sales can agree on how touches contribute to pipeline creation, which lowers friction in planning.<\/li>\n
          • Improved customer experience:<\/strong> When you value helpful early touches (education, onboarding, webinars), you\u2019re incentivized to create better experiences instead of only pushing bottom-funnel pressure.<\/li>\n<\/ul>\n\n\n\n

            Challenges of Weighted Pipeline Influence<\/h2>\n\n\n\n

            Despite its value, Weighted Pipeline Influence<\/strong> can fail if the foundation is weak:<\/p>\n\n\n\n

              \n
            • Identity resolution gaps:<\/strong> If touches can\u2019t be reliably tied to contacts\/accounts\/opportunities, the model will misattribute influence.<\/li>\n
            • CRM hygiene issues:<\/strong> Inconsistent opportunity creation timing, missing fields, or sloppy stage management distort Conversion & Measurement<\/strong> outcomes.<\/li>\n
            • Model disagreement:<\/strong> Stakeholders may argue over weights. That\u2019s a governance issue\u2014your Attribution<\/strong> logic must be documented and consistently applied.<\/li>\n
            • Overconfidence in precision:<\/strong> Weighted influence is still an estimation. Treat it as directional truth for decisions, not courtroom proof of causality.<\/li>\n
            • Channel measurement limitations:<\/strong> Some touches (dark social, word of mouth, offline events) are hard to track, so the model may undervalue them.<\/li>\n<\/ul>\n\n\n\n

              Best Practices for Weighted Pipeline Influence<\/h2>\n\n\n\n

              To make Weighted Pipeline Influence<\/strong> reliable and actionable:<\/p>\n\n\n\n

                \n
              1. \n

                Define your measurement scope clearly<\/strong>\n Decide whether you\u2019re weighting influence toward opportunity creation, stage progression, or both. Keep the model aligned to Conversion & Measurement<\/strong> goals.<\/p>\n<\/li>\n

              2. \n

                Standardize touchpoint taxonomy<\/strong>\n Use consistent campaign naming, channel definitions, and UTMs. Without taxonomy discipline, Attribution<\/strong> reporting becomes noisy and political.<\/p>\n<\/li>\n

              3. \n

                Document the weighting model and rationale<\/strong>\n Publish what gets counted, how weights are assigned, and known blind spots. Transparency reduces skepticism and prevents \u201cmoving the goalposts.\u201d<\/p>\n<\/li>\n

              4. \n

                Validate against reality checks<\/strong>\n Compare weighted influence outputs to:\n – pipeline sourced measures\n – win rates and deal sizes by segment\n – qualitative sales feedback\n If Weighted Pipeline Influence<\/strong> says a channel drives huge pipeline but sales disagrees, investigate tracking and definitions.<\/p>\n<\/li>\n

              5. \n

                Use cohort and time-window analysis<\/strong>\n Pipeline is slow-moving. Measure influence by cohort (e.g., quarter of first touch) and apply reasonable lookback windows. This makes Conversion & Measurement<\/strong> less reactive.<\/p>\n<\/li>\n

              6. \n

                Operationalize decisions, not just dashboards<\/strong>\n Tie weighted influence insights to weekly experiments and quarterly planning so Attribution<\/strong> becomes a management tool, not a reporting artifact.<\/p>\n<\/li>\n<\/ol>\n\n\n\n

                Tools Used for Weighted Pipeline Influence<\/h2>\n\n\n\n

                Weighted Pipeline Influence<\/strong> isn\u2019t a single tool; it\u2019s a measurement capability built from a stack:<\/p>\n\n\n\n

                  \n
                • Analytics tools:<\/strong> capture onsite behavior, content engagement, and conversion events that feed Conversion & Measurement<\/strong>.<\/li>\n
                • Marketing automation platforms:<\/strong> track email, nurture, scoring, and campaign engagement history.<\/li>\n
                • Ad platforms:<\/strong> provide impression\/click data and campaign metadata, useful for channel-level Attribution<\/strong>.<\/li>\n
                • CRM systems:<\/strong> the system of record for pipeline\u2014opportunity creation, stages, amounts, and outcomes.<\/li>\n
                • Customer data platforms \/ data warehouses:<\/strong> unify identities and event streams, enabling reliable touchpoint stitching and weighted modeling.<\/li>\n
                • Reporting dashboards \/ BI tools:<\/strong> visualize weighted influenced pipeline by channel, campaign, segment, and time period.<\/li>\n<\/ul>\n\n\n\n

                  The key is integration and governance\u2014tools only help if the data is consistent and the Attribution<\/strong> logic is stable.<\/p>\n\n\n\n

                  Metrics Related to Weighted Pipeline Influence<\/h2>\n\n\n\n

                  To use Weighted Pipeline Influence<\/strong> effectively, track it alongside complementary metrics:<\/p>\n\n\n\n

                    \n
                  • Weighted influenced pipeline ($):<\/strong> total pipeline amount distributed by your weighting model<\/li>\n
                  • Weighted influence share (%):<\/strong> the portion of total weighted pipeline credited to a channel\/campaign<\/li>\n
                  • Pipeline creation rate:<\/strong> opportunities created per period, segmented by audience and channel mix<\/li>\n
                  • Pipeline velocity indicators:<\/strong> time from first touch to opportunity creation, stage-to-stage conversion time<\/li>\n
                  • Win rate and deal size by influenced mix:<\/strong> whether certain journeys correlate with better outcomes<\/li>\n
                  • Cost per weighted influenced pipeline dollar:<\/strong> spend divided by weighted influenced pipeline (directional ROI measure)<\/li>\n
                  • Touchpoint coverage:<\/strong> percentage of opportunities with sufficient touch data for Attribution<\/strong> analysis (a quality metric for Conversion & Measurement<\/strong>)<\/li>\n<\/ul>\n\n\n\n

                    Future Trends of Weighted Pipeline Influence<\/h2>\n\n\n\n

                    Several trends are shaping how Weighted Pipeline Influence<\/strong> evolves within Conversion & Measurement<\/strong>:<\/p>\n\n\n\n

                      \n
                    • AI-assisted modeling:<\/strong> More teams will use machine learning to suggest weights or detect patterns in journeys. The best use will be \u201cdecision support,\u201d not black-box Attribution<\/strong> that can\u2019t be explained.<\/li>\n
                    • Privacy and signal loss:<\/strong> Cookie restrictions and consent requirements will push measurement toward first-party data, CRM-based touch history, and modeled approaches. Weighted influence will increasingly rely on strong identity and clean event capture.<\/li>\n
                    • More account-centric measurement:<\/strong> B2B organizations will emphasize buying-group engagement, making account-based Weighted Pipeline Influence<\/strong> more common.<\/li>\n
                    • Unified GTM measurement:<\/strong> Marketing, sales development, sales, and product signals will blend into shared dashboards, improving Conversion & Measurement<\/strong> alignment and reducing siloed Attribution<\/strong> fights.<\/li>\n
                    • Incrementality awareness:<\/strong> Teams will pair weighted influence with experiments (holdouts, geo tests) where feasible to avoid mistaking correlation for impact.<\/li>\n<\/ul>\n\n\n\n

                      Weighted Pipeline Influence vs Related Terms<\/h2>\n\n\n\n

                      Weighted Pipeline Influence vs Influenced Pipeline<\/h3>\n\n\n\n

                      Influenced pipeline<\/strong> is often binary: if any marketing touch happened, the opportunity is \u201cinfluenced.\u201d Weighted Pipeline Influence<\/strong> is proportional: it assigns a share of pipeline value based on a weighting model. In Conversion & Measurement<\/strong>, the weighted approach is usually more actionable because it reduces inflated totals and clarifies relative contribution.<\/p>\n\n\n\n

                      Weighted Pipeline Influence vs Multi-Touch Attribution<\/h3>\n\n\n\n

                      Multi-touch Attribution<\/strong> is the broader discipline and set of models used to assign credit across touches. Weighted Pipeline Influence<\/strong> is a specific application of Attribution<\/strong> that focuses on distributing pipeline value<\/em> (not just conversions) across touches.<\/p>\n\n\n\n

                      Weighted Pipeline Influence vs Marketing Sourced Pipeline<\/h3>\n\n\n\n

                      Marketing sourced pipeline<\/strong> typically means marketing is credited with creating the opportunity (often tied to a specific sourcing rule). Weighted Pipeline Influence<\/strong> can include sourced pipeline but also captures \u201cassist\u201d value where marketing contributed meaningfully even if sales technically sourced the opportunity. Together, they give a more complete Conversion & Measurement<\/strong> picture.<\/p>\n\n\n\n

                      Who Should Learn Weighted Pipeline Influence<\/h2>\n\n\n\n
                        \n
                      • Marketers:<\/strong> To defend budgets, prioritize channels across the funnel, and communicate performance through credible Attribution<\/strong> instead of vanity metrics.<\/li>\n
                      • Analysts:<\/strong> To design measurement frameworks, validate data quality, and build models that leadership can trust in Conversion & Measurement<\/strong>.<\/li>\n
                      • Agencies:<\/strong> To prove impact beyond last-click reporting and show how campaigns contribute to pipeline creation in complex journeys.<\/li>\n
                      • Business owners and founders:<\/strong> To understand which investments generate pipeline now vs. later, and to avoid cutting programs that quietly drive demand.<\/li>\n
                      • Developers and data teams:<\/strong> To support identity resolution, event tracking, and data modeling that makes Weighted Pipeline Influence<\/strong> technically sound.<\/li>\n<\/ul>\n\n\n\n

                        Summary of Weighted Pipeline Influence<\/h2>\n\n\n\n

                        Weighted Pipeline Influence<\/strong> assigns proportional credit for pipeline creation across marketing and sales touchpoints, making it a practical method inside Conversion & Measurement<\/strong>. It brings nuance to pipeline reporting by replacing binary \u201cinfluenced\u201d labels with weighted contributions that reflect real buyer journeys. As an Attribution<\/strong> approach, it helps teams allocate budgets more intelligently, align cross-functional stakeholders, and optimize for the touches that genuinely move prospects toward opportunities.<\/p>\n\n\n\n

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

                        1) What is Weighted Pipeline Influence in simple terms?<\/h3>\n\n\n\n

                        Weighted Pipeline Influence<\/strong> is a way to split pipeline value across multiple touchpoints so each channel or campaign gets partial credit based on an Attribution<\/strong> weighting model.<\/p>\n\n\n\n

                        2) How is Weighted Pipeline Influence different from last-touch Attribution?<\/h3>\n\n\n\n

                        Last-touch Attribution<\/strong> assigns 100% credit to the final touch before a key event. Weighted Pipeline Influence<\/strong> spreads credit across touches, which is usually more realistic for Conversion & Measurement<\/strong> in longer buying cycles.<\/p>\n\n\n\n

                        3) Do you need a data warehouse to calculate Weighted Pipeline Influence?<\/h3>\n\n\n\n

                        Not always. Some teams can implement basic Weighted Pipeline Influence<\/strong> with clean CRM and marketing automation data plus consistent campaign tracking. A warehouse becomes important as touch volume, channels, and identity complexity increase.<\/p>\n\n\n\n

                        4) What pipeline event should Weighted Pipeline Influence be tied to?<\/h3>\n\n\n\n

                        Most commonly, it\u2019s tied to opportunity created<\/strong> (pipeline creation). Some organizations also weight influence toward stage progression<\/strong> for deeper Conversion & Measurement<\/strong> insights, but that requires tighter CRM governance.<\/p>\n\n\n\n

                        5) What\u2019s a reasonable weighting model to start with?<\/h3>\n\n\n\n

                        A position-based or linear model is often a good starting point because it\u2019s explainable. The best Attribution<\/strong> model is one your teams understand, trust, and can apply consistently over time.<\/p>\n\n\n\n

                        6) Can Weighted Pipeline Influence be used for account-based marketing (ABM)?<\/h3>\n\n\n\n

                        Yes. In ABM, Weighted Pipeline Influence<\/strong> is often more meaningful at the account level, where multiple stakeholders engage across channels. This aligns well with enterprise Conversion & Measurement<\/strong> needs.<\/p>\n\n\n\n

                        7) What are the biggest causes of misleading Weighted Pipeline Influence reports?<\/h3>\n\n\n\n

                        The most common causes are poor identity matching, inconsistent opportunity creation rules, missing campaign tracking, and changing Attribution<\/strong> definitions midstream. Tight governance and documentation are essential.<\/p>\n","protected":false},"excerpt":{"rendered":"

                        Weighted Pipeline Influence is a way to quantify how marketing and sales touchpoints contribute to pipeline creation by assigning a proportional \u201cinfluence weight\u201d to each touch. In **Conversion & Measurement**, it helps teams move beyond binary thinking (\u201cthis campaign sourced the deal\u201d vs. \u201cit didn\u2019t\u201d) and instead measure *how much* a channel, campaign, or interaction shaped pipeline outcomes. It\u2019s especially valuable in **Attribution**, where the goal is to distribute credit across multiple touches rather than over-crediting only the first or last interaction.<\/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":[1888],"tags":[],"class_list":["post-7072","post","type-post","status-publish","format-standard","hentry","category-attribution"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7072","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=7072"}],"version-history":[{"count":0,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/posts\/7072\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/media?parent=7072"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/categories?post=7072"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wizbrand.com\/tutorials\/wp-json\/wp\/v2\/tags?post=7072"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}