{"id":1972,"date":"2026-09-11T05:12:05","date_gmt":"2026-09-11T05:12:05","guid":{"rendered":"https:\/\/listenlabs.com\/articles\/align-brand-tracking-metrics-markets\/"},"modified":"2026-09-11T05:12:44","modified_gmt":"2026-09-11T05:12:44","slug":"align-brand-tracking-metrics-markets","status":"publish","type":"post","link":"https:\/\/listenlabs.com\/articles\/align-brand-tracking-metrics-markets\/","title":{"rendered":"How To Align Brand Tracking Metrics Across Global Markets"},"content":{"rendered":"<p><em>Written by: Anish Rao, Head of Growth, Listen Labs<\/em><\/p>\n<h2 id=\"key-takeaways\">Key Takeaways<\/h2>\n<ul>\n<li>Cross-market brand tracking comparability requires a documented governance layer: a metric dictionary, equivalence testing, change control, bridging records, and three-view reporting. Identical questionnaires alone are not enough.<\/li>\n<li>Establish a global KPI hierarchy that locks only metrics every market can field identically. Move any locally adapted item to the category or local layer.<\/li>\n<li>Confirm measurement equivalence (configural, metric, scalar) before comparing countries. Partial scalar invariance with documented rationale is acceptable, and \u201cnot yet comparable\u201d is a valid result.<\/li>\n<li>Implement strict change control and bridging studies for any methodology shift so trend lines stay interpretable and auditable across waves.<\/li>\n<li>Listen Labs delivers the metric dictionary, equivalence testing, and three-view reporting in a single conversational wave. <a href=\"https:\/\/listenlabs.com\/book-my-demo\" target=\"_blank\" rel=\"noindex nofollow\">See how global teams maintain defensible cross-market numbers<\/a> at enterprise scale.<\/li>\n<\/ul>\n<h2>Prerequisites And Context For Global Brand Tracking<\/h2>\n<p>This guide assumes familiarity with unaided awareness, aided awareness, consideration, and brand funnel metrics, and with how a tracker wave works. Before the seven steps, several terms need precise definitions.<\/p>\n<p>A <strong>global core<\/strong> is the set of questions asked identically in every market. A <strong>local module<\/strong> is a market-specific or category-specific block that sits alongside the core without touching it. A <strong>metric dictionary<\/strong> is the single source of truth that defines every tracked metric, including its wording, scale, base, calculation, and allowed local variation. <strong>Measurement equivalence<\/strong> (also called measurement invariance) is the statistical property confirming that a survey item measures the same latent construct in the same way across countries. Without it, <a href=\"https:\/\/academic.oup.com\/sp\/advance-article\/doi\/10.1093\/sp\/jxag040\/8729229\" target=\"_blank\" rel=\"noindex nofollow\">cross-country comparisons are not valid<\/a>.<\/p>\n<p><strong>Conceptual equivalence<\/strong> asks whether a construct exists and carries the same meaning across cultures. <strong>Linguistic equivalence<\/strong> asks whether the translated wording conveys that meaning accurately. <strong>Acquiescence bias<\/strong> is the tendency to agree with a statement regardless of its content, driven by agree\/disagree item formats and cultural deference. <strong>Extreme-response tendency<\/strong> is the habit of choosing scale endpoints regardless of content, <a href=\"https:\/\/onlinelibrary.wiley.com\/doi\/full\/10.1002\/joe.70032\" target=\"_blank\" rel=\"noindex nofollow\">documented as more pronounced in Mediterranean than Northwestern European samples<\/a>, and more pronounced on wider scales. A <strong>bridging study<\/strong> runs old and new methodologies in parallel for at least one wave so the historical trend stays readable after a change. <strong>Trend line integrity<\/strong> means the series is interpretable wave over wave without unexplained breaks.<\/p>\n<p>The operating environment makes this governance urgent. Enterprises are shifting from one-off studies to continuous customer intelligence programs. Trackers now run across 45+ countries and 120+ languages, and internal stakeholders expect cross-market tables they can act on. <a href=\"https:\/\/timelaps.io\/resources\/blogs\/what-is-brand-tracking-a-2026-guide-to-optimize-roi-in-brand-health-tracking\" target=\"_blank\" rel=\"noindex nofollow\">Traditional wave-based, quant-only trackers report that a KPI moved but carry no diagnostic for why<\/a>. That gap makes cross-market comparison fragile.<\/p>\n<p><a href=\"https:\/\/listenlabs.com\/book-my-demo\" target=\"_blank\" rel=\"noindex nofollow\">See how Listen Pulse keeps core questions constant<\/a> wave over wave while adding the qualitative explanation behind every KPI movement.<\/p>\n<h2>How To Align Brand Tracking Metrics Across Markets: A Seven-Step Process (Including Equivalence Testing And Governance)<\/h2>\n<ol>\n<li><strong>Build The Global KPI Hierarchy.<\/strong> Separate metrics into three layers: global core (tracked identically everywhere), category layer (shared within a category or region), and local diagnostics (market-specific). Include in the core only metrics that every market can field with the same question wording, the same scale, and a sufficient base. Move any metric that requires local adaptation to the category or local layer.<\/li>\n<li>To make this decision, you need stakeholder alignment on business questions and clear category definitions by region. The global insights lead, regional research leads, and marketing leadership should be involved. A smaller core is more comparable but less rich, while a bloated core that no market can execute in full is worse than no core at all.<\/li>\n<li><strong>Write The Metric Dictionary.<\/strong> The dictionary is the governance artifact that makes every other step enforceable. For each metric, document the metric name, exact question wording, response options (including scale labels verbatim), calculation method (for example, top-two-box or unaided first mention), base definition, target population, weighting approach, reporting frequency, reporting owner, and allowed local changes.<\/li>\n<li>Present the dictionary as a living document with version control. It should be updated regularly, not treated as a one-time deliverable. Inputs include the finalized KPI hierarchy and existing questionnaires from each market. The global insights lead and, where relevant, legal or compliance teams should own this work. Locking wording globally improves comparability but may reduce local relevance for markets with distinct category structures.<\/li>\n<li><strong>Establish Measurement Equivalence Before Comparing Countries.<\/strong> Confirm conceptual equivalence before testing linguistic equivalence. Use translation and back-translation with independent translators following the TRAPD model (Translation, Review, Adjudication, Pretesting, Documentation), the <a href=\"https:\/\/formpl.us\/blog\/translation-bias-in-multilingual-surveys-causes-prevention-methods\" target=\"_blank\" rel=\"noindex nofollow\">standard multi-stage approach for research where cross-cultural comparability matters<\/a>. Then run cognitive interviews with five to ten native speakers per language to confirm that respondents interpret items as intended.<\/li>\n<li>Test statistical equivalence using multi-group confirmatory factor analysis (MGCFA) in a sequential invariance hierarchy. Configural invariance confirms that the same factor structure holds across countries. Metric invariance adds equal factor loadings and <a href=\"https:\/\/academic.oup.com\/poq\/advance-article\/doi\/10.1093\/poq\/nfag025\/8671904\" target=\"_blank\" rel=\"noindex nofollow\">licenses comparison of relationships such as covariances or regression coefficients<\/a>. Scalar invariance adds equal item intercepts and licenses comparison of latent means, which appear in cross-market brand tracking tables.<\/li>\n<li><a href=\"https:\/\/isoglu.com\/insights\/journal\/measurement-invariance-before-comparing-english-and-german-scores\" target=\"_blank\" rel=\"noindex nofollow\">Partial scalar invariance, freeing equality constraints on a limited number of noninvariant items, can still justify latent mean comparisons when freed items are theoretically defensible<\/a>. Treat the release gate as binary. \u201cNot yet comparable\u201d is a valid methods result. Inputs include translated questionnaires and pilot data per market. The global insights lead and a psychometrician or methods specialist should own this work. Skipping equivalence testing produces numbers that look comparable but are not.<\/li>\n<li><strong>Set Up Change Control.<\/strong> Change control protects trend line integrity. Define a central approval process for any change to question wording, response scale, sample definition, panel source, or fieldwork mode. Name a single approver and maintain a change-control log with fields for date of request, description of proposed change, requester, business rationale, approver, decision, and effective wave.<\/li>\n<li>Trigger a review for any change to global core wording, scale, sample source, supplier, or mode. Do not trigger a review for adding a flexi-section question, rotating topical items in the local module, or adjusting fieldwork timing within the same quarter. Inputs come from the finalized metric dictionary. The global insights lead and a named approver, typically a VP of Consumer Insights or equivalent, should manage this. Strict change control slows adaptation but protects the trend line.<\/li>\n<li><strong>Bridge The Trend Line.<\/strong> When a methodology change is unavoidable, such as a supplier change, scale revision, or mode shift, run old and new in parallel for at least one wave. <a href=\"https:\/\/ongraph.com\/owned-research-panel-vs-sample-providers\" target=\"_blank\" rel=\"noindex nofollow\">For tracking studies requiring greater confidence, the parallel-run overlap period may extend from three months to a year<\/a>. Document the bridging adjustment in the metric dictionary and in the change-control log.<\/li>\n<li>The bridging record must state what changed, the wave in which the parallel run occurred, the observed difference between old and new, and the adjustment applied to connect the series. Inputs include parallel-run data and the change-control log entry. The global insights lead and data science or analytics team should own this work. Bridging requires additional fieldwork cost but is the only defensible way to preserve a historical trend.<\/li>\n<li><strong>Decide How To Average Markets.<\/strong> The roll-up method defines what a global number means. Document this choice in the metric dictionary before reporting begins. Unweighted averaging treats every market as equal regardless of size. This is defensible when markets are strategically equivalent and population data is unreliable.<\/li>\n<li>Population-weighted averaging weights each market by its population share. This approach is useful when the goal is a true consumer-population estimate. Revenue-weighted averaging weights by each market\u2019s revenue contribution and suits a commercially relevant global figure. Strategic-weighted averaging assigns weights based on investment priority or growth targets. This approach is defensible when leadership has explicitly defined which markets matter most, and it requires a documented rationale and periodic review.<\/li>\n<li><a href=\"https:\/\/datalion.com\/en\/blog\/brand-tracker-survey-template\" target=\"_blank\" rel=\"noindex nofollow\">Apply weighting consistently everywhere in the dashboard, including inside filters<\/a>. A weighted total with unweighted subgroups is a common and incorrect combination. Inputs include market revenue data and the strategic priority framework. The global insights lead, finance, and marketing leadership should agree on the method. Each weighting method answers a different question, and the wrong choice produces a number that misleads.<\/li>\n<li><strong>Report In Three Views.<\/strong> As introduced in Step 7, the three reporting views serve different audiences and purposes. The executive view shows global roll-up KPIs with trend lines and confidence bands, annotated with campaign dates and methodology events.<\/li>\n<li>The market view shows each country\u2019s metrics in context, against its own trend, against regional peers, and against the competitive set in that market. The methodology view documents the equivalence status of each metric by market, the weighting method applied, any active bridging adjustments, and any open change-control items. This view makes cross-market comparison honest and provides the artifact that survives audit.<\/li>\n<\/ol>\n<p><a href=\"https:\/\/listenlabs.com\/book-my-demo\" target=\"_blank\" rel=\"noindex nofollow\">See how Listen Labs compresses the research cycle from weeks to hours<\/a> while preserving the governance discipline this playbook requires. The metric dictionary is the cornerstone of that discipline, and the next section explains how to build one.<\/p>\n<h2>How To Build A Metric Dictionary For Global Brand Tracking<\/h2>\n<p>The metric dictionary is the single source of truth for the global brand tracking governance framework. It resolves the global core vs. local module question by specifying which fields are locked globally and which permit documented local variation.<\/p>\n<p>Each entry in the dictionary contains the following fields:<\/p>\n<ul>\n<li><strong>Metric name<\/strong> \u2014 the canonical label used in all reporting<\/li>\n<li><strong>Exact question wording<\/strong> \u2014 verbatim, including any category or brand placeholders<\/li>\n<li><strong>Response options<\/strong> \u2014 all scale points labeled verbatim, in order<\/li>\n<li><strong>Calculation method<\/strong> \u2014 for example, top-two-box, unaided first mention, or net score<\/li>\n<li><strong>Base definition<\/strong> \u2014 for example, total sample, category aware, or brand aware<\/li>\n<li><strong>Target population<\/strong> \u2014 screener criteria that define who qualifies<\/li>\n<li><strong>Weighting approach<\/strong> \u2014 the documented roll-up decision (see Step 6)<\/li>\n<li><strong>Reporting frequency<\/strong> \u2014 wave cadence and any continuous-tracking parameters<\/li>\n<li><strong>Reporting owner<\/strong> \u2014 the named individual responsible for this metric<\/li>\n<li><strong>Allowed local changes<\/strong> \u2014 explicitly listed; anything not listed is locked<\/li>\n<li><strong>Equivalence status<\/strong> \u2014 configural, metric, or scalar invariance confirmed, or \u201cnot yet comparable\u201d<\/li>\n<li><strong>Version and last-reviewed date<\/strong> \u2014 tied to the change-control log<\/li>\n<\/ul>\n<p>The dictionary makes the boundary between global core and local module explicit. Fields marked as globally locked cannot change without a change-control entry and a named approval. Fields marked as locally variable must still be documented. The dictionary records what the local variation is, not just that variation is permitted. <a href=\"https:\/\/datalion.com\/en\/blog\/brand-tracker-survey-template\" target=\"_blank\" rel=\"noindex nofollow\">Documenting analysis definitions next to the questionnaire is essential because staff turnover means that six waves in, no one may know how the metric was originally defined.<\/a><\/p>\n<h2>How To Report Cross-Market Brand Metrics Without Misleading Leadership<\/h2>\n<p>As introduced in Step 7, the three reporting views serve different audiences and purposes. This section explains how to implement each view in practice.<\/p>\n<p>The <strong>executive view<\/strong> presents global roll-up KPIs with trend lines, confidence bands, and annotations for campaign dates and methodology events. It is designed for speed and decision-making, not for methodological detail. Include a footnote referencing the methodology view for any metric where equivalence is partial or where a bridging adjustment is active.<\/p>\n<p>The <strong>market view<\/strong> presents each country\u2019s metrics in context: against its own historical trend, against regional peers, and against the competitive set in that market. <a href=\"https:\/\/ballparkhq.com\/research-glossary\/brand-tracking\" target=\"_blank\" rel=\"noindex nofollow\">The relative view, your brand against named competitors in the same wave with the same questions, is the only honest way to know whether growth is yours or the category\u2019s<\/a>. Market-level numbers should always include confidence bands. <a href=\"https:\/\/brandsand.co\/insights\/brand-tracking-survey\" target=\"_blank\" rel=\"noindex nofollow\">A movement that falls within the margin of error is not statistically meaningful regardless of how it looks on a chart<\/a>.<\/p>\n<p>The <strong>methodology view<\/strong> documents the equivalence status of each metric by market, the weighting method applied and its rationale, any active bridging adjustments, and any open change-control items. This view makes cross-market comparison honest. A cross-market table without a methodology view invites leadership to rank markets without knowing whether the numbers are comparable. The methodology view is the artifact that survives audit and protects the insights function when leadership asks why Germany and France look different.<\/p>\n<p><a href=\"https:\/\/listenlabs.com\/book-my-demo\" target=\"_blank\" rel=\"noindex nofollow\">Explore how Listen Labs delivers all three reporting views<\/a>, including the qualitative narrative behind every KPI movement, in a single wave. A key input to those reports is the decision about what belongs in the global core versus local modules, which the next section explores.<\/p>\n<h2>Global Core Vs. Local Module: How Much Should Be Standardized?<\/h2>\n<p>The decision rule for core size is simple. Include in the global core only what every market can field with identical wording, an identical scale, and a sufficient base. When in doubt, move the metric to the category or local layer and document it in the dictionary.<\/p>\n<p>A worked example illustrates the boundary. A single global core funnel, covering unaided awareness, aided awareness, consideration, preference, and purchase intent, is asked identically in every market with locked wording, a locked scale, and a locked base of category-aware adults 18\u201354. Three local modules sit alongside the core without touching it.<\/p>\n<ul>\n<li>A <strong>retail-perception module<\/strong>, used in markets where the brand distributes primarily through physical retail, asks about shelf presence, in-store experience, and retailer association. It appears in the dictionary as a category-layer module, active in eight markets, with its own equivalence status recorded separately from the global core.<\/li>\n<li>A <strong>distribution\/access module<\/strong>, used in markets where availability is a known barrier, asks about ease of finding the brand and perceived availability. It is documented as a local diagnostic, active in four markets, and explicitly excluded from the global roll-up.<\/li>\n<li>A <strong>usage-occasion module<\/strong>, used in markets where category usage patterns differ materially, asks about the contexts in which the brand is used. It is documented as a local diagnostic and used for market-level strategy only.<\/li>\n<\/ul>\n<p>The weighting decision for the global roll-up in this example is documented clearly. The global consideration score is reported as a revenue-weighted average of the eight markets in the global core, weighted by each market\u2019s prior-year net revenue contribution, reviewed annually by the global insights lead and the CFO\u2019s office. An unweighted reference view is retained in the methodology view for audit purposes.<\/p>\n<p>This choice is defensible because leadership\u2019s primary question is commercially relevant global consideration, not a population-representative estimate. The dictionary entry for the global consideration metric states the weighting method, its rationale, the review cadence, and the fact that the unweighted view is available on request.<\/p>\n<h2>Advanced Considerations: From Wave-Based Tracking To Always-On Intelligence<\/h2>\n<p>Once the governance layer is in place, three advanced strategies extend its value.<\/p>\n<p>Moving from wave-based tracking to always-on continuous research reduces latency. <a href=\"https:\/\/timelaps.io\/resources\/blogs\/what-is-brand-tracking-a-2026-guide-to-optimize-roi-in-brand-health-tracking\" target=\"_blank\" rel=\"noindex nofollow\">By the time weakening brand equity shows up in a P&amp;L, a company has already lost 6\u201312 months of ground it did not know it was losing<\/a>. Always-on tracking surfaces the signal earlier. It still requires the same governance discipline, including the metric dictionary, change-control process, and three-view reporting, applied continuously rather than wave by wave.<\/p>\n<p>Running qualitative depth alongside the tracker means every KPI movement arrives with its explanation. The governance layer tells you whether Germany\u2019s 62% consideration is comparable to France\u2019s 48%. It does not explain why the gap exists or whether it is narrowing for the right reasons. Qualitative conversation alongside the tracker answers the why.<\/p>\n<p>For teams ready to operationalize both, Listen Labs recommends <strong>Listen Pulse<\/strong>, the conversational tracker. Pulse runs the same study with the same screeners wave after wave across markets, understands the open-ended answers, sorts them into themes, quantifies them, and charts each theme next to the KPIs already reported. The metric change and the reason behind it arrive in the same wave. Core questions stay constant to keep the trend line clean while timely questions cover new campaigns and competitors.<\/p>\n<p>Pulse deploys alongside an existing tracker or as the primary tracking system and integrates with Qualtrics and Decipher. Teams keep the KPIs they already report while adding the qualitative layer.<\/p>\n<p>The value of this approach is concrete. One well-known clothing brand, famous for its big logos, was quietly losing customers. Its traditional tracker caught the drop but could not explain it. Pulse found that the issue was style, not price. A growing group of customers felt the big logos were too loud for their changing lifestyles. That finding arrived in the same wave as the KPI decline, not weeks later from a separate qualitative study.<\/p>\n<p>Listen Labs is the end-to-end AI research platform with a 50M+ verified respondent network. It compresses a 4\u20136 week research cycle to less than 24 hours and is trusted by enterprises including Microsoft, Google, Anthropic, Sony, Sweetgreen, Procter &amp; Gamble, Skims, Levi\u2019s, Boston Consulting Group, and Nestl\u00e9.<\/p>\n<p>Readiness criteria for adopting always-on intelligence include mature research operations with a functioning metric dictionary and change-control process, data governance infrastructure capable of handling continuous data streams, and cross-functional alignment on which KPI movements trigger which decisions. The recommended pilot approach is to run Pulse alongside the existing tracker for one or two waves, compare the qualitative narrative against the KPI movement, and then phase in Pulse as the primary tracking system once the governance integration is confirmed.<\/p>\n<p><a href=\"https:\/\/listenlabs.com\/book-my-demo\" target=\"_blank\" rel=\"noindex nofollow\">See how Listen Pulse delivers the metric change and the reason behind it in the same wave<\/a>.<\/p>\n<h2>Frequently Asked Questions<\/h2>\n<h3>How Long Should A Bridging Study Run?<\/h3>\n<p>The minimum is one parallel wave, with old and new methodologies fielded simultaneously to the same target population. In some cases, a sequential design may be used, but this should be documented in the bridging record. For tracking studies where a KPI movement of even a few percentage points would trigger a business decision, a longer parallel run is often warranted. Set the duration based on the expected size of the methodology effect and the precision the decision requires.<\/p>\n<p>When the change involves a full supplier switch or a mode change, such as from telephone to online, the overlap period may need to extend to a full year to establish a stable calibration. The bridging record must document the observed difference between old and new, the adjustment applied, and the wave in which parallel collection ended. Once the bridging adjustment is documented, the historical trend can be restated and the new methodology becomes the sole source going forward.<\/p>\n<h3>How Do You Handle A Market That Cannot Field The Full Global Core?<\/h3>\n<p>Start by determining whether the gap is structural or operational. Structural gaps occur when the construct does not exist in that market or the target population cannot be reached. In that case, move the affected metric to the local module for that market and document it as \u201cnot comparable\u201d in the metric dictionary.<\/p>\n<p>Operational gaps occur when the local fieldwork partner lacks capacity. Resolve these gaps before the next wave rather than working around them by fielding a shortened version of the core without documentation. A market that consistently cannot field the full global core signals that the core is too large. Review the KPI hierarchy and move the metric to the category layer if needed.<\/p>\n<h3>How Should You Weight A Global Roll-Up?<\/h3>\n<p>The weighting decision must be made before the first wave and documented in the metric dictionary. Unweighted averaging is a method where each market is treated equally, regardless of size. It is defensible when markets are strategically equivalent and population data is unreliable.<\/p>\n<section data-read-next=\"true\">\n<h2>Read Next<\/h2>\n<ul>\n<li><a href=\"https:\/\/listenlabs.com\/articles\/brand-tracking-metrics-explained\" target=\"_blank\">Brand Tracking Metrics Explained: What They Tell You<\/a><\/li>\n<li><a href=\"https:\/\/listenlabs.com\/articles\/brand-tracking-methodology-guide\" target=\"_blank\">Brand Tracking Methodology: The Complete 2026 Guide<\/a><\/li>\n<li><a href=\"https:\/\/listenlabs.com\/articles\/best-brand-tracking-practices\" target=\"_blank\">Brand Tracking Best Practices for Smarter Decisions<\/a><\/li>\n<li><a href=\"https:\/\/listenlabs.com\/articles\/automating-brand-tracking-studies\" target=\"_blank\">How to Automate Brand Tracking Without Losing the Why<\/a><\/li>\n<li><a href=\"https:\/\/listenlabs.com\/articles\/how-to-track-brand-health\" target=\"_blank\">How to Track Brand Health: A 2026 Step-by-Step Playbook<\/a><\/li>\n<\/ul>\n<\/section>\n","protected":false},"excerpt":{"rendered":"<p>Learn how Listen Labs helps you standardize brand tracking metrics across markets with equivalence testing, governance, and always-on intelligence.<\/p>\n","protected":false},"author":52,"featured_media":1971,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1972","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/posts\/1972","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/comments?post=1972"}],"version-history":[{"count":1,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/posts\/1972\/revisions"}],"predecessor-version":[{"id":1976,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/posts\/1972\/revisions\/1976"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/media\/1971"}],"wp:attachment":[{"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/media?parent=1972"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/categories?post=1972"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/listenlabs.com\/articles\/wp-json\/wp\/v2\/tags?post=1972"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}