{"id":5101,"date":"2026-10-16T10:00:00","date_gmt":"2026-10-16T10:00:00","guid":{"rendered":"https:\/\/freshfacedmarketing.co.uk\/blog\/marketing-performance-framework-a-guide-for-2026\/"},"modified":"2026-10-16T13:23:52","modified_gmt":"2026-10-16T13:23:52","slug":"marketing-performance-framework-a-guide-for-2026","status":"publish","type":"post","link":"https:\/\/freshfacedmarketing.co.uk\/blog\/marketing-performance-framework-a-guide-for-2026\/","title":{"rendered":"Marketing performance framework: a guide for 2026"},"content":{"rendered":"<p>Could your marketing report tell you what to do next, not just what happened? A <strong>marketing performance measurement framework<\/strong> should connect day-to-day activity with business outcomes, yet reports often leave teams with plenty of figures and little clarity about what they mean.<\/p>\n<p>If you\u2019re tracking a long list of metrics, struggling to show how marketing contributes to business goals, or seeing different results from attribution models and platform reports, the problem may not be a lack of data. It may be a lack of structure. Not every metric deserves equal weight, and no single attribution method can explain every part of the customer journey.<\/p>\n<p>This guide will help you build a practical framework that links objectives to meaningful measures, so your team can make more confident decisions about priorities and investment. It will also show how to choose measurement methods for the questions you need to answer, rather than treating one model as definitive.<\/p>\n<p>We\u2019ll move from business goals to metrics, then look at how to interpret evidence and turn it into action. The aim is not another dashboard. It\u2019s a clearer basis for deciding what to continue, change or investigate further.<\/p>\n<div class=\"key-takeaways\">\n<h2 id=\"key-takeaways\">Key Takeaways<\/h2>\n<ul>\n<li>Build a marketing performance measurement framework by linking a business outcome to an objective, measure, method, owner and decision.<\/li>\n<li>Choose measures that answer a specific business question, rather than tracking activity for its own sake.<\/li>\n<li>Use attribution, incrementality testing and Marketing Mix Modelling for different questions, and weigh each method\u2019s limitations.<\/li>\n<li>Make reviews useful by observing results, testing what they mean and agreeing what to do next.<\/li>\n<li>Use MARLO for competitor evidence and strategic insight; the Marketing Success Blueprint adds human-led analysis and an execution plan.<\/li>\n<\/ul>\n<\/div>\n<div class=\"table-of-contents\" role=\"navigation\" aria-label=\"Table of Contents\">\n<h2 id=\"table-of-contents\">Table of Contents<\/h2>\n<ul>\n<li><a href=\"#why-a-marketing-performance-measurement-framework-must-start-with-decisions\">Why a marketing performance measurement framework must start with decisions<\/a><\/li>\n<li><a href=\"#how-to-build-a-marketing-performance-measurement-framework-step-by-step\">How to build a marketing performance measurement framework step by step<\/a><\/li>\n<li><a href=\"#which-marketing-measurement-methods-answer-different-performance-questions\">Which marketing measurement methods answer different performance questions?<\/a><\/li>\n<li><a href=\"#how-to-turn-marketing-measurement-into-a-regular-decision-cycle\">How to turn marketing measurement into a regular decision cycle<\/a><\/li>\n<li><a href=\"#how-marlo-and-the-marketing-success-blueprint-fit-into-measurement-led-planning\">How MARLO and the Marketing Success Blueprint fit into measurement-led planning<\/a><\/li>\n<\/ul>\n<\/div>\n<h2 id=\"why-a-marketing-performance-measurement-framework-must-start-with-decisions\">Why a marketing performance measurement framework must start with decisions<\/h2>\n<p>Marketing teams can collect a steady stream of figures and still be unsure what to change. A report may show impressions, clicks and enquiries, but not whether those results support the organisation\u2019s goals or what action should follow. The gap is not necessarily more data. It is a clear route from evidence to a decision.<\/p>\n<p>A <strong>marketing performance measurement framework<\/strong> connects business objectives, marketing measures, methods for gathering and interpreting evidence, accountable owners and the decisions that evidence can inform. Each part has a role. Without an objective, a metric lacks direction. Without an owner, no one is responsible for interpreting it. Without a decision, measurement risks becoming reporting for its own sake.<\/p>\n<p>Reporting describes what happened: a campaign generated a certain number of clicks, for example. Measurement goes further. It asks how those results relate to the objective, what might explain them and what to do next. The distinction matters because a dashboard can display results without explaining their significance. Broader discussions of <a href=\"https:\/\/en.wikipedia.org\/wiki\/Marketing_effectiveness\">Marketing Effectiveness and Measurement Approaches<\/a> also cover how organisations assess marketing\u2019s contribution, including return on marketing investment.<\/p>\n<p>Start with the business question, not the dashboard. \u201cHow many people saw the campaign?\u201d may help describe delivery. \u201cIs this activity contributing to qualified demand, and should we continue investing in it?\u201d is more likely to guide a decision. The right question depends on the organisation\u2019s objective, the evidence available and the choice the team needs to make.<\/p>\n<h3>What should a marketing measurement framework help you decide?<\/h3>\n<p>It should make practical choices easier: prioritise channels, adjust activity or investigate a weaker-than-expected result. Tie each choice to a business objective, such as increasing qualified demand, rather than an isolated task such as publishing more posts. A measure earns its place when different possible results could lead to a considered action.<\/p>\n<p>For example, if qualified demand is the objective, a team might compare the quality of enquiries associated with different activities before shifting effort. The measure, method and owner should be clear enough for the team to interpret the evidence consistently. If the result cannot affect a choice, ask whether the metric belongs in the core framework or only in supporting detail.<\/p>\n<h3>Why are activity metrics not the same as performance?<\/h3>\n<p>Activity metrics describe outputs: impressions served, emails sent or posts published. Outcomes describe what happened beyond delivery, such as qualified enquiries or progression towards a commercial goal. The two are related, but they are not interchangeable. A campaign can attract strong engagement yet make little contribution to the business objective it was intended to support.<\/p>\n<p>That does not make reach or engagement irrelevant. They can be useful when the objective is to increase awareness or understand audience response. Their meaning depends on the question being asked. Read them alongside measures closer to the intended outcome, then decide whether the evidence supports continuing, changing or investigating the activity.<\/p>\n<h2 id=\"how-to-build-a-marketing-performance-measurement-framework-step-by-step\">How to build a marketing performance measurement framework step by step<\/h2>\n<p>Build the framework from the result the organisation needs, then work towards the evidence and decisions that can support it. This keeps measures purposeful and makes responsibilities clear. A useful rule is: <strong>Every marketing measure should show how activity relates to a business outcome and help someone decide what to do next.<\/strong><\/p>\n<ol>\n<li><strong>Define the business outcome.<\/strong> Start with the result the organisation wants to influence, such as increasing qualified demand or improving customer retention. Make the outcome specific enough to guide marketing choices.<\/li>\n<li><strong>Set the marketing objective.<\/strong> Identify how marketing could plausibly contribute. For example, the objective might be to generate more qualified enquiries from a defined audience, rather than simply to publish more content.<\/li>\n<li><strong>Choose a small set of measures.<\/strong> Select indicators that show progress at different stages. A leading indicator can signal early response, whilst a lagging indicator shows whether the intended outcome followed. Keep supporting activity measures where they help explain the result.<\/li>\n<li><strong>Select the method.<\/strong> Decide how each measure will be gathered and interpreted. This could involve campaign data, website analytics or records of qualified enquiries. Use a method suited to the question, and document what it can and cannot show.<\/li>\n<li><strong>Assign an owner.<\/strong> Name the role responsible for the source data, measure definition and review. Clear ownership helps teams spot missing data and apply consistent interpretations.<\/li>\n<li><strong>Agree the decision.<\/strong> Set out what the team might do if results support the objective, fall short or remain unclear. A decision rule needn\u2019t force an immediate change; it can call for further investigation when the evidence is inconclusive.<\/li>\n<\/ol>\n<h3>How do you translate business goals into marketing measures?<\/h3>\n<p>Keep a visible line from outcome to objective to evidence. Choose measures that reflect both progress and results, but avoid adding metrics simply because a platform makes them easy to access. Before including a measure, ask what different results would mean and whether they could change a marketing choice.<\/p>\n<p><strong>Hypothetical example:<\/strong> An organisation wants to increase qualified enquiries. Its marketing objective is to attract more relevant prospects through a campaign. It could track visits to the campaign page as an early indicator, then qualified enquiries as a later outcome. The team might use tagged campaign links and its enquiry records to connect activity with responses, while recognising that this alone won\u2019t prove the campaign caused every enquiry.<\/p>\n<h3>How should you document ownership and decision rules?<\/h3>\n<p>Record each measure\u2019s definition, data source, review period, owner and limitations in one shared reference. For the example above, the marketing manager could own campaign tagging and page-visit reporting, whilst the sales or admissions role responsible for qualifying enquiries maintains the outcome records. Agree how the teams will reconcile differences before reviewing results.<\/p>\n<p>Then write down the response to each plausible finding: continue, adjust or investigate. If the data is incomplete or the pattern is uncertain, note what further evidence is needed before changing course. Teams developing their wider priorities can use <a href=\"https:\/\/freshfacedmarketing.co.uk\/\">Fresh Faced\u2019s Marketing Success Blueprint<\/a> to connect evidence with practical planning.<\/p>\n<h2 id=\"which-marketing-measurement-methods-answer-different-performance-questions\">Which marketing measurement methods answer different performance questions?<\/h2>\n<p>Measurement methods are tools for different questions, not competing routes to one definitive answer. Platform attribution can help explain which recorded interactions received credit for conversions. Incrementality tests estimate whether activity produced additional outcomes compared with a suitable comparison condition. Marketing Mix Modelling (MMM) examines how marketing channels relate to results over time. A marketing performance measurement framework can use one or more methods, depending on the decision, available evidence and organisational context.<\/p>\n<h3>When is attribution useful, and where can it mislead?<\/h3>\n<p>Attribution assigns credit across observed customer interactions, using rules such as last click or a platform\u2019s own model. It can help teams understand activity along tracked paths and manage campaigns using consistent operational signals. Useful inputs include conversion records, tagged links and tracking events. The picture is limited to interactions that can be observed and linked under those rules.<\/p>\n<p>Results can differ between platforms and an organisation\u2019s own records. Each platform may apply different attribution windows, event definitions or tracking rules. Its report may credit a conversion to an interaction that another system doesn\u2019t record, or may count the same customer journey differently. Platform incentives and measurement choices also shape the result, so reported credit needs interpretation rather than automatic acceptance.<\/p>\n<p><strong>Attribution credit shows how a model assigns a conversion, not whether marketing caused an additional conversion.<\/strong> A conversion may have happened without the credited interaction. Use attribution to investigate observed journeys and optimise within its limits; don\u2019t treat it alone as proof of incremental impact.<\/p>\n<h3>When should you consider incrementality tests or Marketing Mix Modelling?<\/h3>\n<p>An incrementality test compares an exposed group or period with a suitable control or comparison condition to estimate the change associated with marketing activity. It can help answer a focused question, such as whether a campaign generated additional enquiries. The design needs a credible comparison, reliable outcome data and consideration of factors that could affect the result. If those conditions aren\u2019t met, the estimate may be difficult to interpret.<\/p>\n<p>MMM takes a broader view. It analyses historical business outcomes alongside channel activity or investment over time, often taking other relevant influences into account. It can inform choices about the overall channel mix, especially when the decision concerns patterns across multiple channels rather than a single campaign. Its conclusions depend on the quality and consistency of historical data, the model\u2019s assumptions and how well the available data represents the business.<\/p>\n<ul>\n<li><strong>Use attribution<\/strong> to inspect tracked interactions and support campaign-level decisions, while recognising that it allocates credit.<\/li>\n<li><strong>Consider an incrementality test<\/strong> when you need to estimate the additional effect of a defined activity and can establish a meaningful comparison.<\/li>\n<li><strong>Consider MMM<\/strong> when you need a broader view of channel contribution over time and have suitable historical data.<\/li>\n<\/ul>\n<p>No method answers every question. Choose by working backwards from the decision: define what you need to learn, assess whether the necessary evidence is available, then state the limitations alongside the result. Where practical, compare perspectives without assuming they should produce identical numbers. Differences can reveal distinct measurement rules, timeframes or questions, not necessarily an error.<\/p>\n<p><!-- autoseo-infographic --><\/p>\n<div class=\"autoseo-infographic-container\"><img fetchpriority=\"high\" decoding=\"async\" width=\"830\" height=\"2560\" src=\"https:\/\/freshfacedmarketing.co.uk\/blog\/wp-content\/uploads\/2026\/10\/infographic_1792152515_1g5aDKa6-scaled.jpg\" class=\"autoseo-infographic-image skip-lazy no-lazy\" alt=\"Marketing performance framework: a guide for 2026\" loading=\"eager\" data-no-lazy=\"1\" data-skip-lazy=\"1\" srcset=\"https:\/\/freshfacedmarketing.co.uk\/blog\/wp-content\/uploads\/2026\/10\/infographic_1792152515_1g5aDKa6-scaled.jpg 830w, https:\/\/freshfacedmarketing.co.uk\/blog\/wp-content\/uploads\/2026\/10\/infographic_1792152515_1g5aDKa6-97x300.jpg 97w, https:\/\/freshfacedmarketing.co.uk\/blog\/wp-content\/uploads\/2026\/10\/infographic_1792152515_1g5aDKa6-332x1024.jpg 332w, https:\/\/freshfacedmarketing.co.uk\/blog\/wp-content\/uploads\/2026\/10\/infographic_1792152515_1g5aDKa6-768x2369.jpg 768w, https:\/\/freshfacedmarketing.co.uk\/blog\/wp-content\/uploads\/2026\/10\/infographic_1792152515_1g5aDKa6-498x1536.jpg 498w, https:\/\/freshfacedmarketing.co.uk\/blog\/wp-content\/uploads\/2026\/10\/infographic_1792152515_1g5aDKa6-664x2048.jpg 664w\" sizes=\"(max-width: 830px) 100vw, 830px\" \/><\/div>\n<p><!-- \/autoseo-infographic --><\/p>\n<h2 id=\"how-to-turn-marketing-measurement-into-a-regular-decision-cycle\">How to turn marketing measurement into a regular decision cycle<\/h2>\n<p>A measurement process only creates value when findings lead to considered action. Set a review rhythm around the decision and the time it takes for relevant data to become meaningful. A team monitoring campaign delivery may need to review it differently from one assessing qualified demand, which can take longer to emerge. There is no universal cadence. Match the timing to the objective, evidence and action at stake.<\/p>\n<p>Use the same sequence each time: observe the result, test its interpretation, then agree an action. This keeps discussion grounded in evidence without treating every change as proof of cause. A useful review should capture what changed, what the team thinks it means, what remains uncertain and who will follow up.<\/p>\n<h3>What belongs in a useful performance review?<\/h3>\n<p>Keep the review focused on progress against the objective and the measures that help explain it. Note meaningful changes since the previous review, then separate observed evidence from interpretation and assumptions. For example, record a fall in qualified enquiries as the result; a change in audience response as one possible explanation. End with a named owner, a next action and a measure that will help assess its effect.<\/p>\n<p>For a practical discussion, move through three questions:<\/p>\n<ol>\n<li><strong>What changed?<\/strong> Compare relevant measures with the agreed objective and previous review period. Record data gaps or changes in how the figures were collected.<\/li>\n<li><strong>What could explain it?<\/strong> Check the interpretation against context, such as changes to activity, tracking or the audience. Note other plausible explanations rather than selecting the first one.<\/li>\n<li><strong>What happens next?<\/strong> Agree whether to continue, adjust or investigate. Give the action an owner and define what evidence would help assess its effect.<\/li>\n<\/ol>\n<p>This creates a clear route from measurement to prioritised work. If several actions emerge, place them in an <em>actionable marketing roadmap<\/em> so the team can see what comes first, what depends on other work and how each priority supports the objective.<\/p>\n<h3>How do you avoid vanity metrics and false certainty?<\/h3>\n<p>Before adding a metric to recurring reporting, ask whether its result could change a decision. If not, it may be useful background rather than a core measure. Keep reach and engagement where they help answer the question, but don\u2019t treat movement in either as proof of commercial impact. Flag attribution limits, small samples and external factors when they affect interpretation.<\/p>\n<p>Unexpected results are a reason to investigate, not an automatic explanation. Check whether the measure is defined consistently, whether relevant data is missing and whether another change could account for the pattern. Where the evidence remains inconclusive, record that uncertainty and agree what to learn next instead of making a confident claim the data can\u2019t support.<\/p>\n<p>A well-run <strong>marketing performance measurement framework<\/strong> makes follow-through part of the review, not an afterthought. If you\u2019re shaping priorities and need support turning evidence into a practical plan, Fresh Faced\u2019s <a href=\"https:\/\/freshfacedmarketing.co.uk\/\">Marketing Success Blueprint<\/a> brings human-led strategic analysis together with an execution blueprint.<\/p>\n<h2 id=\"how-marlo-and-the-marketing-success-blueprint-fit-into-measurement-led-planning\">How MARLO and the Marketing Success Blueprint fit into measurement-led planning<\/h2>\n<p>A <strong>marketing performance measurement framework<\/strong> belongs to your organisation. It sets out the objectives, evidence, responsibilities and decisions that guide how you assess your own marketing. Software can help inform that work, but it can\u2019t replace the choices behind the framework or prove the performance of your campaigns simply by presenting data.<\/p>\n<p>MARLO and the Marketing Success Blueprint (MSB) have distinct roles in planning. MARLO is competitor-research software, delivered through an interactive web dashboard and strategic roadmap. The MSB is a separate, human-led service that adds strategic interrogation of evidence and a detailed execution blueprint. Neither changes the need to measure your organisation\u2019s own results against its objectives.<\/p>\n<h3>What can MARLO contribute to evidence-led planning?<\/h3>\n<p>MARLO analyses competitors\u2019 search, content, social and paid-media activity. Its interactive dashboard helps you examine which keywords competitors rank for, the content that attracts traffic and engagement, how competitors use social platforms and where paid activity appears. It also provides a strategic roadmap that prioritises options against your goals, budget and resources.<\/p>\n<p>This evidence can sharpen planning questions. If competitors are gaining visibility around relevant topics, for instance, that may prompt your team to investigate whether there is an opportunity worth pursuing. It doesn\u2019t show how your own campaign performed, establish that a competitor\u2019s activity caused its results or replace your organisation\u2019s performance measures. Treat it as market context to weigh alongside your own evidence.<\/p>\n<p>That distinction is useful when the team needs to decide what to examine or prioritise next. Competitor signals can suggest areas for further analysis, but your framework should still define how you\u2019ll assess your own activity and what business outcomes matter.<\/p>\n<h3>When is the human-led Marketing Success Blueprint relevant?<\/h3>\n<p>The MSB suits organisations that want strategists to interrogate competitive evidence and turn it into a practical plan. It includes forensic competitive analysis across channels, human-led strategic interrogation, a detailed execution blueprint, two one-to-one strategy calls and a two-to-three-hour workshop. This goes beyond MARLO\u2019s dashboard and roadmap: the strategists work through what the evidence could mean for your priorities and execution.<\/p>\n<p>In practice, MARLO helps surface competitor evidence and structure potential options; the MSB adds human-led interpretation and an execution blueprint. Both can inform evidence-led marketing strategy, but neither should be confused with the organisation\u2019s measurement framework. Your team still owns the objectives, performance measures and decisions used to evaluate its marketing.<\/p>\n<p>Use MARLO when you want an interactive view of competitor search, content, social and paid activity. Choose the MSB when you want Fresh Faced strategists to interrogate that evidence and develop an execution blueprint with your team.<\/p>\n<h2 id=\"make-your-next-measurement-decision-clearer\">Make your next measurement decision clearer<\/h2>\n<p>Your next step doesn\u2019t need to be a full reporting rebuild. Choose one business question that matters, then identify the evidence that could help you answer it. Agree who will review the findings and what decisions they can inform. Start with a manageable process, learn where it gives useful direction and refine it as your organisation\u2019s priorities change.<\/p>\n<p>Measurement is most useful when it helps your team focus. Competitor context can prompt questions about where to investigate, while your own objectives and evidence should guide decisions about your marketing. Keep those roles clear, and you can make space for insight without mistaking it for proof of performance.<\/p>\n<p><a href=\"https:\/\/freshfacedmarketing.co.uk\">Explore MARLO\u2019s competitor research dashboard<\/a> to see how competitor insight could inform your planning. Start with a clear question and use the findings to help guide your next decision.<\/p>\n<h2 id=\"frequently-asked-questions\">Frequently Asked Questions<\/h2>\n<h3>Is a marketing performance measurement framework the same as marketing analytics?<\/h3>\n<p>No. A marketing performance measurement framework defines the decisions, responsibilities and evidence an organisation needs; marketing analytics supplies techniques and tools for examining data. For example, the framework might ask whether a campaign is reaching its intended audience and specify who acts on the answer. Analytics could then segment visits by audience or source. Sophisticated analytics alone won\u2019t provide direction if nobody knows which decision the analysis should inform.<\/p>\n<h3>Can a small business build a marketing performance measurement framework?<\/h3>\n<p>Yes. Begin with one business priority, such as increasing repeat purchases, then choose a small number of measures that show whether marketing is contributing. A retailer, for example, could compare campaign responses with repeat purchases recorded in its sales system instead of building a complex dashboard across every channel. Add measures only when they help explain progress or guide a decision. The framework can grow as the business\u2019s questions and evidence develop.<\/p>\n<h3>How often should a marketing performance measurement framework be reviewed?<\/h3>\n<p>Review frequency should follow the decision and the time needed for relevant data to emerge. Campaign delivery may warrant a closer operational check, whilst repeat purchases or longer sales journeys need a longer observation period. Set a review point that allows the behaviour you\u2019re measuring to happen, and avoid changing direction because of a temporary fluctuation. Reconsider the timing if data arrives late or the decision becomes more urgent.<\/p>\n<h3>What data do you need before building a marketing measurement framework?<\/h3>\n<p>Start with the objective, a baseline, the available data source, a consistent measure definition and known limitations. The baseline gives you a reference point for assessing change; the definition prevents teams counting the same outcome differently. For example, agree what qualifies as an enquiry before comparing records from a website form and a sales system. Note gaps such as missing campaign tags, so the team can judge how confidently it can interpret results.<\/p>\n<h3>Is return on ad spend enough to measure marketing performance?<\/h3>\n<p>No. Return on ad spend (ROAS) compares revenue attributed to advertising with the advertising spend, so it can inform decisions about paid activity. It doesn\u2019t show every cost involved in serving customers, establish that the advertising caused the revenue or capture outcomes from other marketing. A business focused on qualified demand, retention or longer-term brand effects will need additional measures aligned with those objectives. Treat ROAS as one indicator, not a complete verdict.<\/p>\n<h3>How can you measure marketing when customers interact with several channels?<\/h3>\n<p>Combine evidence that captures different parts of the journey, such as campaign records, website activity and sales or customer records. Use consistent time periods and definitions where possible, then note which interactions each source can identify. A person might see a social post, visit through search and later enquire directly; no single record may capture that whole path. Compare the available views, but don\u2019t assume that assigning credit proves which channel caused the outcome.<\/p>\n<h3>What should you do when marketing metrics disagree?<\/h3>\n<p>First check whether the figures measure the same event, use the same attribution window and cover matching dates. Then compare the underlying sources and check for missing records, tracking changes or delays. For example, an advertising platform may report a conversion that hasn\u2019t yet appeared in a sales system because the systems record different stages. Document the mismatch, consider plausible explanations and decide whether the difference affects the action you\u2019re considering before drawing a conclusion.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Could your marketing report tell you what to do next, not just what happened? A marketing performance measurement framework should connect day-to-day&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[177,117,176,178,5,3,160],"class_list":["post-5101","post","type-post","status-publish","format-standard","hentry","category-blog","tag-attribution-modelling","tag-marketing-analytics","tag-marketing-framework","tag-marketing-reporting","tag-marketing-roi","tag-marketing-strategy","tag-performance-measurement","autoseo"],"_links":{"self":[{"href":"https:\/\/freshfacedmarketing.co.uk\/blog\/wp-json\/wp\/v2\/posts\/5101","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/freshfacedmarketing.co.uk\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/freshfacedmarketing.co.uk\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/freshfacedmarketing.co.uk\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/freshfacedmarketing.co.uk\/blog\/wp-json\/wp\/v2\/comments?post=5101"}],"version-history":[{"count":3,"href":"https:\/\/freshfacedmarketing.co.uk\/blog\/wp-json\/wp\/v2\/posts\/5101\/revisions"}],"predecessor-version":[{"id":5105,"href":"https:\/\/freshfacedmarketing.co.uk\/blog\/wp-json\/wp\/v2\/posts\/5101\/revisions\/5105"}],"wp:attachment":[{"href":"https:\/\/freshfacedmarketing.co.uk\/blog\/wp-json\/wp\/v2\/media?parent=5101"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/freshfacedmarketing.co.uk\/blog\/wp-json\/wp\/v2\/categories?post=5101"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/freshfacedmarketing.co.uk\/blog\/wp-json\/wp\/v2\/tags?post=5101"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}