Xiaohongshu Benchmark Data: Industry Averages for Key Metrics
Date Published
Table Of Contents
• Why Platform-Specific Benchmarks Matter on Xiaohongshu
• The Core Xiaohongshu Metrics Every Brand Should Track
• Engagement Rate Benchmarks by Industry
• Save Rate (Collect Rate) Benchmarks
• Video vs. Image Post Performance Benchmarks
• KOL and KOC Engagement Benchmarks
• Conversion and Commercial Benchmarks
• How to Use These Benchmarks to Improve Your Strategy
If your Xiaohongshu content is getting views but you're not sure whether you're actually performing well, you're not alone. One of the biggest challenges international brands face on Xiaohongshu (also known as RedNote or Little Red Book) is the absence of a clear reference point — without industry benchmarks, it's nearly impossible to tell whether a 4% engagement rate is something to celebrate or a signal that your content strategy needs a rethink.
This guide cuts through the noise and gives you concrete Xiaohongshu benchmark data across the metrics that matter most: engagement rate by vertical, save rate targets, video completion standards, KOL and KOC performance norms, and conversion averages. Whether you're in beauty, fashion, food and beverage, travel, or mother and baby, you'll leave with numbers you can actually use to evaluate where you stand and where to improve.
For brands new to the platform, it also helps to understand that Xiaohongshu's algorithm operates very differently from Western social media. Follower count is a weak signal here — content quality, engagement depth, and save behavior drive distribution. That distinction shapes every benchmark in this article.
Why Platform-Specific Benchmarks Matter on Xiaohongshu {#why-platform-specific-benchmarks-matter}
Applying generic social media benchmarks to Xiaohongshu leads brands astray in predictable ways. A 2% engagement rate that would be respectable on Weibo or Instagram is actually below par for most Xiaohongshu verticals, while a save rate that barely registers on other platforms is one of the most commercially meaningful signals on this one. The platform's unique content discovery mechanics, its community of high-intent shoppers, and its algorithm's preference for genuine interaction all create a different performance baseline.
Xiaohongshu's user base is also distinctly skewed toward engaged, purchase-ready consumers. Research indicates that 70% of monthly active users engage in product search behavior, and 90% report that platform content directly influences their purchase decisions. That level of commercial intent doesn't exist on most social platforms, which is precisely why brands should hold their Xiaohongshu performance to a higher standard — and why the benchmarks here will look higher than what you'd find for Instagram or Facebook.
With those caveats in place, here is what the data actually shows.
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The Core Xiaohongshu Metrics Every Brand Should Track {#core-xiaohongshu-metrics}
Before diving into the numbers, it's worth establishing which metrics are worth benchmarking in the first place. Unlike most social platforms where likes and follower growth dominate dashboards, Xiaohongshu performance is best captured through a tighter set of signals.
Engagement Rate is calculated as (likes + comments + collects + shares) divided by impressions, multiplied by 100. Using impressions rather than follower count is important because Xiaohongshu's algorithm regularly distributes content to non-followers, meaning follower-based calculations systematically understate or overstate reach depending on your account stage.
Save Rate (Collect Rate) measures the percentage of viewers who bookmark a post. On Xiaohongshu, saving a post signals significantly stronger intent than a like — it's the behavior of a user who plans to come back before making a purchase decision.
Video Completion Rate and the 5-Second Play Rate are the two video-specific signals the algorithm weights most heavily. If users drop off in the first five seconds, distribution is throttled. If they watch to the end, the algorithm reads the content as genuinely valuable.
Follower Growth Rate and Search Ranking Position round out the picture for brands focused on organic visibility, though they are lagging indicators compared to the engagement metrics above.
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Engagement Rate Benchmarks by Industry {#engagement-rate-benchmarks-by-industry}
Overall, Xiaohongshu engagement rates for brand accounts typically run between 2% and 8%, with the precise range depending heavily on vertical, account maturity, and content format. For established brand accounts across most categories, a healthy benchmark sits in the 3–5% range. Emerging brands producing tightly targeted content can realistically target above 8%, particularly in high-affinity categories.
Below are industry-specific benchmarks based on aggregated platform data:
Beauty and Cosmetics consistently achieves the platform's highest engagement rates, typically ranging from 5% to 10%. The combination of a highly engaged female-skewing audience, the platform's deeply embedded review culture, and the visual compatibility of skincare and makeup content with Xiaohongshu's format explains this outperformance. Beauty brands also benefit from the strongest purchase-intent correlation of any vertical — users actively researching product efficacy interact at higher depth than casual browsers.
Fashion and Apparel performs strongly, with typical engagement rates of 4% to 7%. Fashion content tends to generate high save rates as users build personal style references and outfit inspiration boards, though conversion timelines are longer than in beauty. Luxury fashion brands specifically benefit from aspirational content formats that the platform's aesthetic sensibility supports well.
Food and Beverage lands in the 3% to 6% engagement range. Restaurant discovery and packaged food content both perform well, with a particularly strong local discovery function that makes F&B one of the most effective verticals for driving offline foot traffic. Premium imported goods and health-focused nutrition content sit at the higher end of this range.
Travel and Lifestyle typically achieves 3% to 5% engagement, with the highest share rates of any category. Travel content is aspirational and inherently shareable, which generates strong top-of-funnel reach, though conversion paths are longer and less direct than in beauty or fashion.
Mother and Baby is a high-commercial-intent vertical that sits in the 4% to 6% range. Community discussion is intense, with users frequently asking detailed product questions in comments — a signal that engagement depth in this category is particularly high even when raw engagement rate looks moderate.
Home and Living ranges from 3% to 5%, with a growing user base that skews slightly older (28–35). Interior design inspiration, product recommendations, and home organization content all perform consistently, though this vertical is less saturated than beauty or fashion, creating real organic opportunity for brands entering now.
One consistent pattern across all verticals: beauty brands typically see engagement rates 30–40% higher than electronics or B2B categories, reflecting how well Xiaohongshu's content culture aligns with consumer goods and lifestyle products versus technical or considered-purchase categories.
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Save Rate (Collect Rate) Benchmarks {#save-rate-benchmarks}
If there is a single metric that separates Xiaohongshu from every other social platform in its commercial significance, it is the save rate. On Xiaohongshu, a save is functionally a purchase consideration bookmark — users save content they intend to revisit before buying. The algorithm recognizes this intent signal and rewards high-save content with extended distribution, meaning posts with strong save rates continue to appear in search results weeks or months after publication.
The general benchmark for a healthy impression-to-save ratio is above 1.5%. Content that consistently clears this threshold is being treated by users as reference material rather than passive entertainment, which is the ideal positioning for a brand on a platform where discovery and purchase intent overlap so heavily.
For context on what strong save performance looks like in practice: a micro-influencer with 15,000 followers whose lifestyle guides consistently earn 3–5% save rates will typically deliver more commercial value for a brand than a macro-influencer with 200,000 followers whose content earns primarily likes and minimal saves. The algorithm treats that save-heavy content as high-quality and distributes it broadly — repeatedly and over time.
Content formats that consistently generate above-benchmark save rates include detailed product comparison guides, step-by-step tutorials with clear visuals, curated product collections with specific themes, and practical advice posts with specific, actionable takeaways. Brands should design content with the explicit goal of being saved, not just viewed.
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Video vs. Image Post Performance Benchmarks {#video-vs-image-performance}
Both formats have distinct performance profiles on Xiaohongshu, and understanding the difference is important for setting realistic expectations.
Video content drives higher raw engagement and is increasingly prioritized by the algorithm, but it demands more from the viewer — and from the creator. The platform's recommendation engine heavily weights the 5-second play rate (the proportion of viewers who watch past the first five seconds) and overall completion rate. Video posts with average dwell times exceeding 30 seconds perform measurably better in distribution. The ideal video length varies by content type: product reviews typically perform best at 2–4 minutes, tutorials at 3–5 minutes, lifestyle and vlog content at 1–3 minutes, and quick tips or hacks at 30–60 seconds.
Image and carousel posts, by contrast, are the native format for high-save, reference-style content. Carousel posts with 7–9 images typically generate approximately 25% higher save rates compared to single-image posts, making them the format of choice for tutorial content, travel guides, comparison posts, and curated lists. Image posts also have a longer shelf life in Xiaohongshu's search index because the text-rich captions they support help with keyword-based discovery.
The practical implication for brands: video performs better as a discovery and engagement vehicle; image carousels perform better as a save-and-convert vehicle. A balanced content strategy deploys both intentionally.
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KOL and KOC Engagement Benchmarks {#kol-koc-engagement-benchmarks}
Xiaohongshu's influencer ecosystem is structured around two distinct tiers, and understanding the performance differences between them is essential for benchmarking partnership results accurately.
KOLs (Key Opinion Leaders) are established creators typically with 100,000 to several million followers. Large KOL accounts (500K+ followers) generate average engagement rates in the 2–4% range. Mid-tier KOLs (100K–300K followers) often carry the highest fees relative to engagement delivered, making them frequently the least efficient tier for cost-per-engagement calculations.
KOCs (Key Opinion Consumers) are everyday users with smaller but highly engaged communities, typically 1,000 to 50,000 followers. KOC accounts regularly achieve engagement rates of 8–15% or higher, reflecting the trust premium that comes from peer-to-peer recommendations. Research suggests KOCs convert at 3 to 8 times the rate of KOLs per impression, precisely because their recommendations are perceived as authentic consumer voices rather than paid placements.
Xiaohongshu's algorithm reinforces this dynamic structurally. A KOC with a 12% comment rate can outperform a KOL with ten times the audience and a 1% rate in terms of actual reach and conversion delivered. The platform's decentralized distribution model means follower count does not guarantee reach — content quality and engagement ratio do.
For brands evaluating influencer partnerships, the most useful benchmark is cost per engagement (CPE) rather than cost per post. The KOC tier of 1,000–10,000 followers consistently delivers the best CPE across most verticals, which is why many brands have shifted meaningful budget away from large KOL posts toward KOC-led campaigns. That shift reflects both efficiency gains and an increasing consumer sophistication — Chinese shoppers are well aware that large influencers get paid for reviews, and trust KOC voices accordingly.
For more on structuring influencer strategies by vertical, AllXHS's industry-specific Xiaohongshu marketing resources cover KOL and KOC frameworks across beauty, fashion, F&B, and more.
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Conversion and Commercial Benchmarks {#conversion-and-commercial-benchmarks}
Xiaohongshu sits primarily in the discovery and consideration phase of the purchase journey, which means conversion benchmarks need to be interpreted in that context. Direct in-app conversions are one data point, but the platform's influence on off-platform purchases — via Tmall, JD.com, brand websites, and offline retail — is equally significant and often larger.
Beauty and skincare content typically leads on conversion intent, with beauty KOL campaigns generating conversion rates of 3–5% compared to the platform average of approximately 1.5%. Brands utilizing KOL collaborations on RedNote see conversion rates 2.3x higher than traditional advertising channels on average, with micro-influencer campaigns delivering particularly strong ROI.
Average order values driven by Xiaohongshu traffic are notably higher than most social channels, reflecting the high-intent nature of the audience. Platform data suggests average order values exceed ¥300 RMB (approximately $42 USD) across categories, with beauty and fashion averaging ¥450–600 RMB ($63–84 USD). Users on this platform demonstrate lower price sensitivity and higher willingness to pay a premium when purchase confidence is built through detailed, authentic content.
For repeat purchase behavior, the top-performing merchant accounts on the platform show average repeat purchase rates around 32%, indicating that Xiaohongshu-driven customers are not one-time converters — they return. This is a commercially significant benchmark for brands thinking about lifetime value, not just initial conversion rates.
To build out a full measurement framework and access industry-specific data for your vertical, AllXHS offers 378+ data-driven industry reports and ready-to-use tools designed specifically for international brands on Xiaohongshu.
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How to Use These Benchmarks to Improve Your Strategy {#how-to-use-benchmarks}
Benchmark data is only useful when it connects to decisions. Here is how to put these numbers to work.
Start with your vertical's engagement rate target and compare it against your last 30 days of content. If you're consistently below benchmark, the issue is typically one of three things: content format mismatch (posting single images in a vertical where carousels dominate), keyword targeting (your notes aren't appearing in the right searches), or authenticity signals (over-polished content that reads as advertising rather than peer recommendation).
Audit your save rate separately from your engagement rate. A post can have strong like volume but poor save rates, which tells you it's entertaining but not useful enough to bookmark. For brands in consideration-heavy verticals like fashion, home, or mother and baby, low save rates are a direct signal to create more reference-worthy, practical content.
Evaluate KOL and KOC partnerships on CPE, not follower count. Pull the engagement rate data for every creator you work with and calculate actual cost per engagement against the benchmarks in this article. Most brands find their large KOL spend is underperforming relative to mid-tier and KOC partnerships when evaluated on this basis.
Track video completion rates as a leading indicator. If your 5-second play rate is low, the algorithm is throttling distribution before most viewers even see your content. This is a thumbnail and hook problem, not a content-length problem — fix the first five seconds before adjusting anything else.
For brands that want structured guidance on applying benchmarks across their specific vertical, the AllXHS 21-module training academy covers platform analytics, content strategy, and KOL frameworks in depth — built specifically for international teams navigating Xiaohongshu for the first time or looking to scale.
Final Thoughts {#final-thoughts}
Xiaohongshu benchmark data is most valuable when treated as a directional tool rather than a fixed scorecard. Engagement rates, save ratios, and conversion averages vary by vertical, account maturity, content format, and seasonal factors — the numbers in this guide give you a reference range, not a ceiling. What matters is consistent progress against your own baseline, with these industry averages as context for where you stand.
The clearest takeaway from the data is this: on Xiaohongshu, depth beats breadth. A smaller, highly engaged audience that saves your content and returns to it before purchasing is more commercially valuable than a large, passive following. Build your content strategy around that principle, and the benchmarks will follow.
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