Xiaohongshu Analytics Glossary: Every Metric & Term Defined
Date Published
Table Of Contents
1. Why Analytics Terminology Matters on Xiaohongshu
3. Content Performance Metrics
4. Engagement Metrics & the CES Score
6. Paid Advertising Metrics (Aurora / Juguang)
7. Influencer & KOL Campaign Metrics
8. E-commerce & Conversion Metrics
9. Audience & Demographic Terms
10. Key Platform Tools & Infrastructure Terms
11. Quick-Reference Glossary Index A–Z
Stop Guessing What Your Xiaohongshu Numbers Mean
You open your Xiaohongshu dashboard, and the numbers are right there — impressions, 互动率, 完播率, CPE, CES score, ROAS. But knowing the number and knowing what to do with it are two completely different skills. For international brands entering China's fastest-growing social commerce platform, that gap costs real money.
Xiaohongshu (also known as RedNote or Little Red Book) now counts over 376 million monthly active users, with daily post views reaching 9.12 billion. The platform is no longer a nice-to-have discovery channel — it is China's primary product research engine, with nearly 70% of monthly active users performing searches every single session. Getting your analytics literacy right is not optional.
This glossary is built specifically for international marketers and brand teams navigating Xiaohongshu's analytics ecosystem. Every term is defined with context, benchmarks where available, and a note on why it matters for your strategy — covering organic content analytics, Aurora paid advertising metrics, Pugongying influencer campaign KPIs, and e-commerce conversion tracking in one place. Bookmark it, share it with your team, and stop second-guessing your reports.
Why Analytics Terminology Matters on Xiaohongshu {#why-analytics-matter}
Xiaohongshu does not behave like Instagram, TikTok, or any Western platform you already know. Its algorithm, commerce architecture, and user behavior create a unique set of metrics that often have no direct equivalent in standard social media reporting. A metric that signals success on Instagram (raw follower count, for example) is largely irrelevant here — the platform's algorithm weights engagement quality and search relevance far more heavily than audience size.
Furthermore, Xiaohongshu marketing operates across at least three distinct measurement environments: the native Professional Account dashboard for organic content, the Aurora (聚光) advertising platform for paid campaigns, and Pugongying (蒲公英) for influencer collaboration tracking. Each environment surfaces different terms, different formulas, and different benchmarks. Without a clear glossary anchored to each context, brands routinely misread performance, misallocate budget, and draw the wrong strategic conclusions.
The definitions below are organized by category rather than alphabet, because understanding which type of metric you are looking at — reach, engagement, search, paid, conversion — is the first step to acting on it correctly.
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Platform & Account Metrics {#platform-account-metrics}
These are the top-level indicators that give you a snapshot of your brand's overall health and momentum on the platform.
Impressions (曝光量 / 曝光) — The total number of times your content appeared in a user's feed, search results, or explore pages. Impressions count every display, including multiple views by the same user. This is a reach metric, not an engagement metric, and should never be evaluated in isolation. On the Aurora dashboard, the top-level summary view surfaces impressions alongside clicks and engagement rate as headline figures — useful for a quick health check, but the real value lies one layer deeper.
Unique Reach (触达人数) — The number of distinct individual users who saw your content, as opposed to raw impression volume. Reach removes duplicate views and gives a cleaner picture of how many actual people your content touched. When impressions are high but reach is low, your content is being served repeatedly to the same small audience — a signal to broaden your targeting or diversify content formats.
Follower Count (粉丝数) — The total number of users who follow your account. On Xiaohongshu, follower count matters far less than on Western platforms because the algorithm distributes content to non-followers based on relevance and engagement signals. A small account with a strong engagement rate will consistently outperform a large account with passive followers.
Follower Growth Rate — Net new followers divided by total followers, typically measured monthly. A healthy growth rate for established brand accounts generally falls between 3–8% monthly, though viral campaigns or trending topic participation can produce significant short-term spikes. The more important signal is consistency: steady growth over time indicates sustainable audience building, while sharp spikes followed by flatlines often reflect one-off campaign traffic that hasn't converted to genuine community.
Frequency (频次) — The average number of times a single user has seen a specific piece of content or ad within a defined time window. High frequency without corresponding engagement uplift suggests audience fatigue — a useful signal to refresh creative or expand audience targeting parameters.
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Content Performance Metrics {#content-performance-metrics}
These metrics measure how individual notes (posts) perform once they are in the platform ecosystem.
Notes (笔记) — Xiaohongshu's term for a user post. A note can contain images, short-form video, text, location tags, product tags, and hashtags. It is the fundamental unit of content performance measurement on the platform.
Views / Read Count (阅读量) — The number of times a note has been opened and read, as distinct from impressions (which count feed appearances). Views indicate active intent — a user tapped your content to see more. Monitoring the ratio of views to impressions gives you a useful click-through proxy for organic content.
Click-Through Rate (CTR / 点击率) — The percentage of users who tap on your content after seeing it in their feed or search results. On Xiaohongshu, your cover image and title are the two primary CTR drivers. The platform's algorithm uses CTR as a strong early signal of content relevance — a high CTR feeds more impressions, while a low CTR suppresses distribution. A healthy organic CTR benchmark sits between 3–8%; below 2% typically signals a creative or headline problem that needs addressing before further amplification.
Complete Rate (完播率) — For video content, the percentage of viewers who watch from start to finish. Complete rate is one of Xiaohongshu's most important algorithmic signals for video notes — high completion tells the algorithm the content is engaging and triggers wider distribution. A low complete rate with a high impression count means your thumbnail is working but your content is not delivering on the promise it made.
Save Rate (收藏率) — The percentage of viewers who save (bookmark) your content relative to total impressions or views. Save rate is arguably the single most important organic content metric on Xiaohongshu. When a user saves a note, it signals high perceived value and future purchase consideration — the algorithm weights saves heavily in distribution decisions. Benchmarks vary by vertical, but save rates consistently above 2–3% are considered strong indicators of content quality.
Traffic Source Breakdown (流量来源) — A breakdown of where your note's views originated: discovery feed, search results, following feed, or creator profile. This split is critical strategic intelligence. A high proportion of search-sourced traffic means your content is indexing well for relevant keywords and will continue generating views long after publication. Feed-sourced traffic tends to spike on publication day and decay quickly, whereas search traffic can compound over weeks and months.
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Engagement Metrics & the CES Score {#engagement-metrics}
Engagement is the currency of organic distribution on Xiaohongshu. The platform uses a weighted scoring system that treats different types of engagement very differently.
Engagement Rate (互动率) — The aggregate measure of how actively users interact with your content. The standard formula is: (Likes + Comments + Saves + Shares) ÷ Impressions. Xiaohongshu's algorithm heavily weights engagement rate over follower count in distribution decisions, which is why accounts with smaller but more engaged audiences frequently achieve wider reach than large accounts with passive followers.
CES Score (Content Engagement Score) — Xiaohongshu's internal weighted engagement scoring system that assigns different point values to each interaction type. The weighting currently applied is: Likes (1 point), Collections/Saves (1 point), Comments (4 points), Shares (4 points), and Follows (8 points). This scoring model directly reflects the platform's content distribution logic — a post with 50 comments and 20 shares will receive meaningfully more algorithmic distribution than one with 500 likes and nothing else. Understanding CES scoring is essential for shaping content that earns algorithmic reach, not just passive consumption.
Likes (点赞) — A surface-level positive signal. While likes matter for CES scoring, they are considered a lighter form of engagement compared to saves and comments. A high like count with low saves often indicates content that is visually appealing but not purchase-intent-driving.
Comments (评论) — Active audience participation that carries 4x the CES weight of a like. Comment quality and sentiment offer direct insight into audience reception. On Xiaohongshu, the community values authentic, detailed discussions — comment sections frequently function as extended product reviews and Q&A sessions that influence other users' purchase decisions.
Saves / Collections (收藏) — The bookmarking action that signals a user wants to return to your content later. Saves indicate purchase consideration and content utility, and they carry significant algorithmic weight. A high save rate is one of the clearest indicators that your content is doing its job as a discovery-to-purchase bridge.
Shares (分享) — Users distributing your content to their own followers or via direct message. Shares carry the same CES weight as comments and reflect genuine advocacy — a user is willing to put their personal credibility behind recommending your content. Share rate is particularly valuable as a virality signal.
ERPF (Engagement Rate per Post per Follower) — A normalized engagement metric used by analysts and agencies to compare content performance across accounts of different sizes. An ERPF of 0.01% means that on average, one in every 10,000 followers engages with each post in that category. ERPF provides a more honest comparison of content quality than raw engagement volume because it controls for audience size.
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Search & Discovery Metrics {#search-discovery-metrics}
Xiaohongshu functions increasingly like a search engine. Nearly 70% of monthly active users perform searches every session, and one in three users opens the app and goes directly to search as their first action. This search behavior gives rise to a distinct set of metrics that most Western marketers overlook entirely.
Keyword Ranking (关键词排名) — The position at which your content appears in Xiaohongshu's search results for a specific keyword or phrase. Unlike traditional SEO, Xiaohongshu ranks individual notes (posts) as well as brand accounts, so both content and account authority contribute to ranking. Higher keyword rankings drive sustained organic traffic from users with active purchase intent.
Search Impression Share — The proportion of searches for a given keyword that result in an impression of your content. High search impression share for relevant category keywords indicates strong content-search alignment and signals that your notes are being indexed effectively by the platform's search algorithm.
Branded Search Volume (品牌搜索量) — The volume of users actively searching for your brand name on Xiaohongshu. Branded search volume is a lagging but highly reliable indicator of campaign effectiveness — when seeding campaigns and KOL activity succeed in planting genuine product interest, users subsequently search for your brand to find more information. Tracking branded search volume before, during, and after campaigns helps isolate platform-driven demand creation.
Share of Voice (SOV / 声量占比) — Your brand's share of total relevant content views, mentions, or search impressions within your product category, relative to all competitors. On Xiaohongshu, SOV is typically calculated as your brand's content interactions divided by the total interactions across your category. It is a competitive visibility metric — not an absolute performance figure — and is particularly important for beauty, fashion, and lifestyle brands operating in crowded verticals.
Hashtag Performance (话题标签表现) — The reach and engagement driven by specific hashtags attached to your notes. Tracking which hashtags generate visibility has a direct relationship to search ranking, as heavily-used topic tags function as content categorization signals that influence both algorithmic distribution and search indexing. Effective strategy combines branded hashtags, trending platform topics, and evergreen category terms.
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Paid Advertising Metrics (Aurora / Juguang) {#paid-advertising-metrics}
Aurora (聚光), also known as Juguang, is Xiaohongshu's official advertising platform. It bridges paid media and organic content intelligence in a single dashboard, allowing brands to monitor boosted notes, track organic content indexing, and analyze audience behavior simultaneously. The following metrics are native to the Aurora environment.
CPM (Cost Per Mille / 千次曝光成本) — The cost per 1,000 impressions. CPM is the standard reach-stage efficiency metric for awareness campaigns on Aurora. It answers the question: how much are you paying to put your content in front of 1,000 users? CPM is most meaningful when evaluated alongside CTR — a low CPM with a low CTR means you are reaching people cheaply but failing to earn their attention.
CPC (Cost Per Click / 单次点击成本) — The cost incurred each time a user clicks on your ad. On Aurora, brands can bid on a CPC basis for objectives including profile visits, website traffic, and lead generation. CPC on Xiaohongshu ranges from approximately RMB 3–15 across most verticals, with beauty and skincare as the most competitive category (RMB 8–20). Importantly, a higher CPC on Xiaohongshu often delivers stronger downstream conversion than lower CPCs on passive social platforms, because the platform's search-driven, peer-recommendation environment produces users with genuine purchase intent.
CPE (Cost Per Engagement / 单次互动成本) — The total spend divided by the number of interactions (likes, saves, comments, shares) generated. CPE is the primary efficiency metric for content consideration campaigns. A CPE below RMB 10 is generally considered good on Xiaohongshu; below RMB 5 is excellent. CPE is also the most reliable metric for comparing KOL or KOC post performance because it normalizes for audience size and filters out inflated follower counts.
CPA (Cost Per Acquisition / 单次转化成本) — The cost of driving one defined conversion action — a purchase, sign-up, app install, or lead. CPA requires conversion tracking to be properly configured before a campaign launches. It is the ultimate performance metric for commerce-stage campaigns and the final arbiter of campaign efficiency when revenue attribution is in place.
ROAS (Return on Ad Spend / 广告投入产出比) — Revenue generated divided by advertising spend, expressed as a multiplier (e.g., 3x ROAS means every RMB 1 spent generated RMB 3 in revenue). ROAS is the top-level financial efficiency metric for Aurora campaigns with commerce objectives. Benchmarks vary significantly by vertical and campaign type, but ROAS is most meaningful when tracked alongside CPA to ensure you are acquiring customers profitably, not just generating revenue.
CPV (Cost Per View / 单次播放成本) — The cost of each individual video view. CPV is the relevant efficiency metric for video-format Aurora campaigns, particularly short-form content seeding amplification.
Quality Score / Creative Score — Aurora's internal assessment of your ad creative's relevance and user experience quality. Higher-scoring native-style, authentic-looking content earns better ad placement efficiency over time, effectively lowering your CPC through improved positioning. This is why branded content that mimics organic UGC aesthetics consistently outperforms polished brand-produced assets on both cost and conversion.
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Influencer & KOL Campaign Metrics {#influencer-kol-metrics}
KOL and KOC campaigns on Xiaohongshu are tracked through a combination of Pugongying platform data and custom reporting. The following terms appear regularly in influencer briefs, post-campaign reports, and agency proposals.
KOL (Key Opinion Leader / 关键意见领袖) — An influencer with typically 100,000+ followers whose content influences audience purchasing decisions at scale. KOL campaigns are measured primarily on reach, engagement volume, and branded search uplift.
KOC (Key Opinion Consumer / 关键意见消费者) — A micro-influencer with typically 5,000–50,000 followers whose value lies in authentic consumer credibility and high engagement rates rather than raw audience size. KOC campaigns are typically evaluated on CPE, save rate, and comment quality — signals of genuine purchase consideration rather than passive reach.
KOS (Key Opinion Seller / 关键意见销售者) — A commerce-focused creator who specializes in driving direct sales conversion through live streaming and product integrations. KOS performance is measured primarily on GMV contribution and conversion rate rather than engagement metrics.
Influencer Campaign Index — A composite metric combining multiple performance signals (reach, engagement, CPE, and brand mention quality) against investment, used to rank KOL and KOC partnerships by overall efficiency. Agencies and brands use this index to identify top-performing creators for repeat collaboration.
Viral Post Rate — The percentage of KOL or KOC posts within a campaign that exceed a predefined performance threshold (usually a CPE or engagement rate benchmark). A high viral post rate across a seeding campaign indicates strong content-audience alignment and is one of the clearest signals that a messaging angle is resonating with Chinese consumers.
Content Seeding (种草) — Xiaohongshu's native concept describing the act of planting purchase desire through content. When a user encounters appealing content featuring a product, they have been "seeded" with interest. Content seeding is measured through engagement quality, save rate, and the subsequent uplift in branded search volume — the chain from exposure to active research intent.
Conversion (拔草) — The completion of a purchase after being seeded with product interest. If seeding plants desire, conversion "pulls the grass" — turning intent into transaction. The gap between seeding metrics (high saves, comments) and conversion metrics (purchases, product page visits) reveals where your customer journey needs optimization.
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E-commerce & Conversion Metrics {#ecommerce-conversion-metrics}
GMV (Gross Merchandise Value / 商品交易总额) — The total sales value transacted through Xiaohongshu's e-commerce and live commerce features within a defined period. GMV is the primary success metric for social commerce and live streaming campaigns, providing a top-line view of commercial output.
Product Click-Through Rate (商品点击率) — The percentage of users who tap a product tag within a note to view product details. Product CTR benchmarks vary by category: beauty and fashion typically achieve 3–7%, while consumer electronics average 1–3%. Low product CTR despite high content engagement suggests a mismatch between content audience and product positioning, or a pricing or presentation friction point.
Content-Attributed Conversions — Purchases or qualified actions that can be directly traced back to specific pieces of content through UTM parameters, promotional codes, or platform-native attribution tools. This is the ultimate metric connecting your content investment to revenue, and it requires deliberate tracking setup before campaigns begin.
Conversion Rate (转化率) — The percentage of users who complete a desired action (purchase, sign-up, lead form submission) after engaging with your content or ads. Xiaohongshu delivers notably strong conversion rates for global brands — research indicates an average of 21.4% for brands with well-executed social commerce strategies. Category benchmarks for note-driven conversions typically range from 4–6%.
Traffic Attribution — The method by which inbound traffic to external properties (Tmall stores, brand websites, mini-programs) is attributed back to Xiaohongshu activity. Common attribution methods include Xiaohongshu-specific UTM parameters, unique promotional discount codes, QR code tracking in notes, and platform-native product tag click data.
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Audience & Demographic Terms {#audience-demographic-terms}
Audience Demographics (受众人口特征) — The breakdown of your followers and content viewers by age, gender, city tier, and interests. Xiaohongshu's Professional Account dashboard provides this data, which is essential for confirming that your content is reaching your intended customer profile. A mismatch between your target demographic and your actual audience is one of the most common and costly misalignments in early-stage brand strategies.
Tier 1 Cities (一线城市) — Beijing, Shanghai, Guangzhou, and Shenzhen. Xiaohongshu users from Tier 1 cities have the highest purchasing power and are early adopters of new brands, trends, and product categories.
Tier 2 Cities (二线城市) — Major cities including Hangzhou, Chengdu, Nanjing, and Chongqing. Tier 2 consumers are increasingly affluent, aspirational, and represent some of the fastest-growing opportunity segments on the platform.
Active Hours (活跃时间) — The periods during which your specific audience is most active on the platform. Active hour data, available in the Professional Account dashboard, should directly inform your posting schedule. Peak activity windows vary significantly by demographic — Gen Z audiences (Post-95) behave differently from millennial (Post-85) or working professional segments.
Gen Z (Post-95 / 95后) — Users born after 1995, representing one of Xiaohongshu's core demographics. They are skeptical of overt advertising but highly influenced by peer recommendations and authentic creator content. Over 50% of Xiaohongshu's user base was born after 1995.
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Key Platform Tools & Infrastructure Terms {#platform-tools-terms}
Understanding the analytics stack requires knowing which tool each metric lives in.
Professional Account (专业号) — A verified brand or creator account with access to the native analytics dashboard, covering content performance, follower growth, engagement metrics, audience demographics, and traffic source breakdowns. This is the starting point for all organic analytics.
Aurora (聚光 / Juguang) — Xiaohongshu's official paid advertising platform. Aurora bridges paid and organic data in a single interface, allowing brands to monitor boosted note performance, track organic content search indexing, and cross-reference audience behavior to refine targeting. For brands investing in paid media, Aurora is the single most important analytics environment on the platform.
Pugongying (蒲公英 / Dandelion) — Xiaohongshu's official influencer collaboration marketplace, connecting brands with verified KOLs and KOCs. The platform provides performance metrics including CPE, engagement rate, audience overlap analysis, and historical creator performance data. With over 100,000 creators available, Pugongying's filtering capabilities allow brands to select partners based on content category, follower size, and tracked cost-per-engagement history.
MCN (Multi-Channel Network) — An agency that manages a network of creators and facilitates brand-influencer partnerships on Xiaohongshu. Official MCN partners have verified access to Pugongying and typically provide consolidated campaign performance reporting across multiple creator activations.
UGC (User-Generated Content / 用户生成内容) — Authentic content created by everyday users rather than brand accounts or professional creators. UGC is highly trusted by Chinese consumers and drives significant organic discovery. From an analytics perspective, brands track UGC volume (how many users are posting about your product independently) as a measure of organic advocacy and content seeding effectiveness.
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Quick-Reference Glossary Index A–Z {#quick-reference-index}
For quick lookup, here is an alphabetical index of every term defined above:
• Active Hours — Peak audience activity windows; informs posting schedule
• Aurora (聚光 / Juguang) — XHS's official paid advertising and analytics platform
• Branded Search Volume — Volume of users actively searching your brand name on XHS
• CES Score — Weighted engagement scoring: Likes (1pt), Saves (1pt), Comments (4pt), Shares (4pt), Follows (8pt)
• Click-Through Rate (CTR) — % of feed impressions that result in a content tap; healthy benchmark 3–8%
• Collections / Saves (收藏) — Bookmarking action; high-value algorithmic and purchase-intent signal
• Comments (评论) — Active engagement; 4x CES weight vs. likes
• Complete Rate (完播率) — % of video viewers who watch to the end; key distribution signal
• Content-Attributed Conversions — Purchases traced directly to specific content via tracking setup
• Content Seeding (种草) — Planting purchase desire through content; measured via engagement and branded search uplift
• Conversion (拔草) — Completing a purchase after being seeded with product interest
• Conversion Rate (转化率) — % of users completing a desired action; platform average 4–6% for notes
• CPA (Cost Per Acquisition) — Campaign cost divided by conversions; ultimate performance metric
• CPC (Cost Per Click) — Cost per ad click; XHS range RMB 3–20 depending on vertical
• CPE (Cost Per Engagement) — Campaign cost divided by total interactions; good below RMB 10, excellent below RMB 5
• CPM (Cost Per Mille) — Cost per 1,000 impressions; primary awareness-stage efficiency metric
• CPV (Cost Per View) — Cost per video view for video-format Aurora campaigns
• ERPF (Engagement Rate per Post per Follower) — Normalized engagement metric controlling for audience size
• Follower Count (粉丝数) — Total followers; less algorithmically important than engagement rate
• Follower Growth Rate — Net new followers ÷ total followers; healthy brand benchmark 3–8% monthly
• Frequency (频次) — Average exposures per unique user; high frequency without engagement uplift signals fatigue
• Gen Z (Post-95 / 95后) — Core XHS demographic; born post-1995; over 50% of user base
• GMV (Gross Merchandise Value) — Total sales value through XHS commerce and live streaming
• Hashtag Performance (话题标签表现) — Reach and engagement driven by specific topic tags
• Impressions (曝光量) — Total content appearances; includes repeat views by same user
• Influencer Campaign Index — Composite metric ranking KOL/KOC partnerships by overall efficiency
• Keyword Ranking (关键词排名) — Position of your content in XHS search results for a keyword
• KOC (Key Opinion Consumer) — Micro-influencer; 5K–50K followers; high authenticity and CPE efficiency
• KOL (Key Opinion Leader) — Macro-influencer; 100K+ followers; reach and awareness focus
• KOS (Key Opinion Seller) — Commerce-focused creator; measured on GMV and conversion rate
• Likes (点赞) — Light positive signal; 1pt CES weight
• MCN (Multi-Channel Network) — Creator management agency with Pugongying marketplace access
• Notes (笔记) — XHS term for a post; fundamental unit of content performance
• Product Click-Through Rate — % tapping product tags; beauty/fashion benchmark 3–7%
• Professional Account (专业号) — Verified brand/creator account with full analytics dashboard access
• Pugongying (蒲公英) — XHS's official influencer collaboration marketplace
• Quality Score / Creative Score — Aurora's creative relevance rating; higher score lowers effective CPC
• ROAS (Return on Ad Spend) — Revenue ÷ ad spend; top-line financial efficiency for paid campaigns
• Save Rate (收藏率) — Saves ÷ impressions; strong benchmark >2–3%; most important organic quality signal
• Search Impression Share — Your content's share of impressions for a given search term
• Share of Voice (SOV / 声量占比) — Your brand's share of category content visibility vs. competitors
• Shares (分享) — Content sharing to followers or DM; 4pt CES weight; virality signal
• Tier 1 Cities (一线城市) — Beijing, Shanghai, Guangzhou, Shenzhen; highest purchasing power
• Tier 2 Cities (二线城市) — Hangzhou, Chengdu, etc.; aspirational, fast-growing audience
• Traffic Attribution — Methodology for tracing external traffic (Tmall, websites) back to XHS content
• Traffic Source Breakdown (流量来源) — Split of views by origin: feed, search, following, profile
• UGC (User-Generated Content) — Organic user posts; tracked as advocacy and seeding effectiveness signal
• Unique Reach (触达人数) — Distinct individual users reached; cleaner audience penetration metric than impressions
• Viral Post Rate — % of KOL/KOC posts exceeding a defined performance threshold
• Views / Read Count (阅读量) — Number of times a note was opened; active intent signal
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Want to go deeper on any of these metrics in the context of your specific industry? AllXHS covers 20+ verticals with dedicated, data-driven strategy resources — from beauty and fashion to F&B, mother & baby, and beyond. You can also explore our free Xiaohongshu resources library, including tools, templates, and reports built for international brands at every stage of their XHS journey. For brands ready for a hands-on approach, our expert Xiaohongshu marketing services team is available to help you build and execute a metrics-driven strategy from day one.
Master the Metrics. Win the Platform.
Xiaohongshu rewards brands that understand how the platform actually works — and that starts with knowing what you are measuring and why. The gap between a brand that tracks raw impression counts and one that monitors save rate, CES-weighted engagement, branded search volume, and traffic source attribution is not a small gap. It is the difference between guessing and knowing.
This glossary covers the full analytics vocabulary you will encounter across organic content, Aurora paid campaigns, Pugongying influencer work, and social commerce tracking. Use it as a living reference as your XHS strategy matures — the platform evolves quickly, and the metrics that matter most will deepen as your campaigns become more sophisticated.
If you are building a Xiaohongshu presence from scratch or trying to improve an underperforming strategy, AllXHS exists to give international brands the edge that comes from genuine platform expertise. Explore our industry-specific marketing strategies, dive into our free resource library, or connect with our team for a tailored consultation.
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