CHINA FASHION BUSINESS

▼The following discussion and summary from the Coldy Fashion Circle address industry-related issues. These insights are the product of collective wisdom and do not represent individual opinions. The aim is to benefit industry professionals.

The Algorithm Trap—Triple Dilemmas for White-Label Merchants

During a survey at the Yiwu Small Commodities Market, a bag merchant with 12 years of experience revealed his “cost death spiral”: Douyin’s click-through cost surged from ¥0.3 in 2021 to ¥2.8, while return rates skyrocketed from 28% to 65%.

“Behind every hit product, three unsold items are filling the gap. We’re like hamsters sprinting on a treadmill.”

More critically, the algorithm’s black box—natural traffic suddenly plummeted. The operations team spent three days troubleshooting only to discover that a competitor had launched a targeted “bombing” ad campaign at 3 AM.

The decline of traditional shelf-based e-commerce is inevitable.

A CTO from a top-tier e-commerce agency disclosed that 17 out of the top 20 products in Taobao search results are algorithmically optimized standardized items. When the keyword “dress” only accommodates A-line skirts, designer brands specializing in qipaos and Hanfu are being devoured by the traffic meat grinder.

Yet, white-label merchants venturing into content e-commerce are sinking deeper into a prisoner’s dilemma.

A Hangzhou-based MCN executive crunched the numbers: For every 0.1 increase in ROI (Return on Investment) for influencer livestreams, product commission rates rise by 3 percentage points. Even more absurd is the “return economics”—a influencer’s livestream once achieved ¥7 million GMV, but the merchant ended up losing ¥170,000 in shipping costs due to 55% of returns occurring on the 6th day post-delivery (just beyond the platform’s shipping insurance window).

Amid this battle for survival, the WeChat Channels ecosystem is cracking open an opportunity. In Shenzhen’s Nanyou Apparel Base, an original design brand reduced its private domain return rate to under 12% using a “WeChat Moments + WeChat Groups/Enterprise WeChat + WeChat Channels” trifecta.

The secret lies in redefining the “product-user-scenario” relationship—private domain users nurtured through deep content are willing to pay a 30% premium for emotional value. With a community pre-sale model, inventory turnover cycles are compressed to 7 days. This reaffirms a business truth: When transactions evolve from algorithmic matching to emotional connections, price wars degrade into the lowest dimension of competition.

The next frontier for white-label merchants is undoubtedly the “user symbiosis” paradigm.

As traditional shelf-based e-commerce becomes an algorithmic game and content e-commerce drowns in traffic wars, white-label merchants must leap from “shelves → content → social” e-commerce. The rise of WeChat Channels offers a strategic opportunity to rebuild the product-user-scenario dynamic.

1.1 The Return Black Hole: The Crisis of Quality Control

The core contradiction: Algorithm-driven hit product logic forces merchants to rush into unprepared supply chains, creating a death spiral—”price wars → cost-cutting → quality failures → high returns → cash flow strain → reluctance to stock inventory.”

During the 2023 Double 11 festival, a Jiangnan-style women’s apparel brand saw return rates breach the 68% survival threshold. The trigger? A platform’s “24-hour lightning delivery” traffic incentive policy.

To secure a prime livestream slot, the brand slashed quality checks from 7 stages to 2, leading to disaster—a batch of 3,000 acetate satin shirts had cutting errors causing underarm tears, triggering an avalanche of returns.

Worse, 43% of returns were “non-standard” (damage from wear), yet merchants still bore shipping costs per platform rules.

A deep dive into supply chain data revealed: When livestream GMV hit ¥8 million, fabric procurement cycles were compressed to 72 hours (industry norm: 7-15 days). “We knew the color fastness of this TR fabric was subpar, but the algorithm’s traffic window was only 48 hours,” lamented the supply chain head. This “traffic-driven production” distortion caused a 240% YoY surge in quality complaints, with after-sales costs devouring 21% of gross profit.

At an internal review meeting, the operations director presented a suffocating “death spiral” model: Using spot goods (ready stock) to meet platform delivery deadlines → SKU reduction → overconcentration on hit products → extreme production cycle compression → quality failures → return surges → cash flow strain → abandonment of pre-sales → heavier reliance on spot goods. This loop culminated in 60% of ¥17 million spring inventory being resold returns, which themselves had a 78% return rate.

A sobering industry lesson: The brand once invested ¥1.5 million in paid traffic to buy 15 days of production time. But the algorithm’s ruthlessness showed—when livestream interaction rates dropped 0.3%, traffic instantly shifted to competitors. The rescue attempt ended with a ¥3 million inventory backlog, proving content e-commerce’s harshest rule: In the algorithm empire, quality control isn’t a competitive edge—it’s a survival license.

1.2 Pricing Dilemma: Misaligned Mental Accounting

The core issue lies in failing to anchor prices to the psychological expectations of target customers.

Butterfly Effect of Price Fluctuations

On the eve of 2024’s Double 11, a down jacket studio witnessed a nerve-wracking pricing battle. A parka originally priced at ¥799 underwent four price adjustments in 30 days—slashed to ¥499 for clearance, raised back to ¥699 due to competitor price cuts, and finally sold at ¥399. The cost of this rollercoaster: 15% of loyal customers demanded price difference refunds, 38% of returns cited “price fraud,” and behind the seemingly impressive ¥8 million GMV, net profit margin stood at a mere 0.7%.

Algorithmic Strangulation of Pricing Power

E-commerce platforms’ “auto-price-matching” systems have become tyrants for white-label merchants. When an algorithm deems a dress 50% similar to a 1688.com counterpart, it forces a “suggested price cut to ¥49” and blocks traffic for merchants refusing to comply. A more absurd case: A homeware brand’s original ceramic cup was flagged as “overpriced” after a factory knockoff dropped its price by ¥2, causing natural traffic to plunge 90%. This mechanical price comparison has slashed the lifecycle of hit products in Hangzhou’s apparel cluster from 3 months in 2021 to 17 days in 2024.

Cognitive Divide in Mental Accounting

Consumer price perceptions for white-label products are polarized: Lower-tier markets anchor ¥39 T-shirts to “fast fashion” expectations, tolerating 5% quality variance, while new middle-class consumers categorize them under “lifestyle” accounts, demanding both design and value. A data firm found that the same white-label coffee beans were deemed “reasonably priced” at ¥29.9/500g on Pinduoduo but required a “¥45 + origin story” on Xiaohongshu to attract buyers. This cognitive gap caused a designer brand to lose 62% of its target audience by using uniform pricing across Douyin and Dewu.

Vicious Cycle of the Death Spiral

Pricing chaos triggers chain reactions: A Shenzhen 3C accessory merchant’s data shows that a 10% price cut boosts GMV by 23% but triggers 15% customer churn and 8% gross margin erosion.

Worse, a clothing manufacturer surrendered pricing power to an MCN to maintain traffic, paying 45% commission per livestream order, trapping itself in a “sell more, lose more” loop. This distortion fueled a 37% YoY surge in white-label store closures across the Yangtze River Delta in 2024.

A Ningbo small appliance brand’s breakthrough offers insight: By segmenting users, it repackaged an air fryer as a “basic model (¥199)” and a “smart ecosystem model (¥399)” for different channels, boosting repurchase rates to 28% and cutting complaints to one-third of industry averages. This validates behavioral economist Thaler’s axiom: Pricing isn’t a numbers game but a precise sculpting of consumers’ mental accounts.

1.3 Inventory Curse: The Reckless Gamble on Hit Products

Inventory overstocking appears to be poor product selection but is actually algorithm-driven “gambling.” When livestream traffic fluctuates wildly, merchants lacking customer insights bet on hits, only to face the paradox: “The more you sell, the more you lose.”

Roulette in the Algorithm Casino

In September 2023, alarms blared in a Hangzhou apparel brand’s ERP system—8 SKUs from its ¥17 million autumn/winter collection had sell-through rates below 12%. The disaster began when a knitwear item unexpectedly ranked third in its category during a livestream. The algorithm boosted traffic weight by 300%, forcing the merchant to ramp production from 3,000 to 50,000 units within 48 hours. But as raw materials were still dyeing, platform traffic shifted to a new fur livestream, leaving 42,000 units stranded.

Supply Chain Fractures

The procurement director revealed a fatal mismatch: Traditional apparel requires 120 days from planning to shelf, but livestream hits now last 7-15 days. To chase algorithms, fabric procurement shrank from 45 to 7 days, using untested greige fabric. A deadlier decision: outsourcing 20% of production to untested factories, resulting in 30% unsellable inventory due to quality failures.

Death Tax of Dead Stock

Financial data exposed inventory’s toll: Every ¥1 million in overstock raised monthly storage costs by ¥28,000 and capital costs by ¥43,000, plus 6%-15% seasonal depreciation. A “livestream clearance” backfired—¥39 fire-sale prices cannibalized full-price items and triggered a “low-quality” platform label, halving natural traffic. This desperation inflated losses from ¥3 million to ¥6.7 million.

Mathematical Trap of Gambling on Hits

An industry survey shows livestream merchants’ hit prediction rate crashed from 35% in 2021 to 7.2% in 2023. When a dress hits 5,000 daily sales, algorithms expand category traffic pools by 300%, inviting competitors. This shortens hit lifecycles from 3 weeks to 5 days, yet minimum fabric orders remain 10,000 yards. A Shenzhen apparel merchant’s brutal formula: Every hit requires 3 duds to offset losses, slashing net margins by 8%.

WeChat Channels Breakthrough—Golden Path from Public to Private Domains

2.1 Merchant Empowerment Revolution: Breaking Free from Influencer Dependence

Top influencers often hijack profits. The solution: “Standardized livestream rooms” that replicate top industry livestreams’ tactics, product mixes, and traffic strategies to create replicable templates. This “fixed process, rotating hosts” model stabilizes per-session GMV by multiples.

The Industrial Revolution of Standardized Livestream Rooms

A Shenzhen women’s apparel studio’s ERP system records two contrasting datasets:

During the 2023 phase of reliance on top influencers, single-session GMV volatility reached 472%. By 2024, after adopting standardized livestream templates, GMV standard deviation dropped to 18%. This transformation stems from its “Livestream Industrialization Operating System,” which breaks down livestreams into 37 standardized modules, from host scripts to lighting angles, all parameterized.

Core of the System: Three-Axis Positioning Method

1. Script Flow Axis:For example, AI analysis of 5,000 hours of top industry livestreams distilled a four-stage script template: “pain point awakening → scenario embedding → trust-building → urgency-driven conversion,” reducing new host training from 28 days to 3 days.

2. Product Portfolio Axis:A golden ratio model: “traffic driver (¥9.9 accessories) + main product (¥199 dress) + profit product (¥599 coat) + strategic product (¥999 collab set),” boosting average order value by 65%.

3. Traffic Strategy Axis:Developed a “private domain priming → public domain explosion → cross-domain synergy” traffic funnel. Community pre-order data predicts hit potential, enabling precise Dou+ ad allocation with an average ROI of 1:4.3.

Standardization isn’t mechanical replication but precise calibration of trust transmission—Five-Dimensional Trust Formula:

• Visual Trust: Strict adherence to the E-Commerce Livestream HD Broadcast Guide, using Canon EOS C80 cinema cameras to ensure millimeter-level fabric texture clarity.
• Process Trust: Embedding real-time factory monitoring in livestreams to showcase 72-step quality checks, slashing return rates from 35% to 8%.
• Data Trust: Displaying raw material traceability QR codes during livestreams; scanning reveals Xinjiang cotton sun exposure hours and cashmere fiber microscopy images.
• Emotional Trust: “VIP-only service channels” with 28-second response times for loyal customers, lifting repurchase rates to 47%.
• Institutional Trust: Adopting Zhejiang Province’s Green Livestroom Certification, reducing compliance complaints by 92%.

This industrial system is rewriting industry rules: Future competitiveness lies not in superstar individuals but in replicable, scalable standardization capabilities.

2.2 Cold Start Playbook: Leveraging Private Domains to Fuel Public Domains

A mid-to-high-price white-label brand’s private domain strategy: Test short videos on WeChat Moments, then push content with >15% engagement to public domains for a 1:3 ROI cold start. The key tactic: Design livestream traffic products as “private domain passes,” achieving 90% WeChat-add rates via customized services.

Precision Testing in Private Domain Content Libraries

The brand conducted A/B testing on Enterprise WeChat Moments at zero cost. For a ¥1,599 wool coat, three video variants were tested:

• Craftsmanship-focused: Microscope comparisons of premium vs. standard fabrics (9% engagement).
• Scenario-driven: Founder’s daily work stories (17% engagement).
• Emotional storytelling: “Mom’s First Luxury” narrative (23% engagement).

Data shows private domain pre-screening reduced CPM by 62% and boosted first-purchase conversion to an industry-leading 7.8%.

Golden Funnel Design: Livestream-to-Private Domain Linkage

• Traffic Product Anchoring: Offer a ¥9.9 “private domain pass” (custom leather keychain + lifetime free dry cleaning) via livestream pop-ups, achieving 90% WeChat-add rates per session.
• Segmented Activation: Use enterprise WeChat tags to differentiate “price-sensitive” (targeted with ¥399 basics) and “quality-driven” (targeted with ¥1,599 premium) users, with 100% manual follow-up within 48 hours.
• Data Feedback Loop: Sync user preference data (color choices, size distribution) to livestream product selection systems, raising hit rates from 12% to 38%.

Flywheel Effect of Public-Private Domain Synergy

At 500k private domain users, the brand launched a “Customer Testimonial Program”: Inviting KOCs to co-stream styling tips, generating UV values 3.2x higher than new customers. Integrating SCRM systems further enabled:

1. Prioritized ad targeting for engaged private domain users, cutting click costs by 44%.
2. Pre-livestream exclusive rewards in private communities, extending average watch time from 72 to 156 seconds.
3. “One-hour delivery” for high-value users, compressing repurchase cycles to one-third of industry averages.

Cold Start Insights

This case validates the “private domain foundation → data feedback → public domain explosion” model:

1. Precision Testing: Low-cost private domain experimentation avoids public domain waste.
2. Segmented Operations: Enterprise WeChat tags enable hyper-personalized outreach.
3. Value Loop Design: Convert private domain services into quantifiable traffic leverage, bridging the “public domain burn vs. private domain stagnation” divide.

Data shows brands adopting this model achieved:

• Private domain users’ annual value (¥2,187) 4.3x public domain users’.
• Livestream ROI surged from 1:1.2 to 1:3.6 in Q4 2024, proving the strategic value of “using private domains as a lever for omnichannel growth.”

Private Domain Alchemy—From Traffic to Retention

3.1 User Segmentation: Multi-Layered Tags and Tailored Services

For white-label brands, only 8%-10% of S-tier users in private domains require intensive nurturing.

Granular Three-Dimensional Scoring System

A dynamically calibrated model based on “purchase frequency × order value × social influence”:

1. Purchase Frequency:

• Active (standard deviation <7 days), weight 1.2.
• Sporadic (7-15 days), weight 1.0.
• Dormant (>15 days), weight 0.8.

2. Order Value:

• Exponential weight triggered at 3x category average (e.g., dresses >¥900, weight 2.5).

3. Social Influence:

• KOC Index built via WeChat keywords (e.g., “recommend to friends”) and engagement data. Livestream sharing adds 20% weight.

Four-Dimensional Segmentation with Contextual Variables

Layered tags across “inquiry/ purchase/ repurchase/ high-value” actions:

1. Time Sensitivity: S-tier users require <3-minute responses and <48-hour delivery.
2. Scenario Penetration: A-tier users must purchase across 3+ lifestyle contexts (e.g., commute, parties, sports).
3. Social Amplification: B-tier users drive ≥2 UVs per share.
4. Price Insensitivity: C-tier users show <10% purchase intent fluctuation despite 30% discount changes.

Atomic Service Strategies for S-Tier Users

For the 8% contributing 42% of premium sales:

1. Data Penetration: RFID tracks wardrobe SKUs, triggering replenishment alerts (e.g., cashmere coat maintenance after 28 wears).
2. Scenario Pre-Embedding: Push outfits 48 hours ahead based on schedules (e.g., flights, meetings), achieving 93% scenario accuracy.
3. Exclusive Access: Grant fabric lab tours and customization rights (yarn count, dye techniques), tripling order values.

Dynamic Validation Mechanism for Tiered Services

Validating tier effectiveness through A/B testing:

1. Control Group: A white-label down jacket brand uniformly pushed a ¥399 basic model to all users, achieving a mere 7.2% conversion rate.
2. Experimental Group: Targeting S-tier users with a ¥999 premium model (with down quality detector) and A-tier users with a ¥699 mid-tier model (lifetime warranty card), conversion rates reached 41% and 23% respectively.
3. Data Feedback: High-converting content from the experimental group was deconstructed into labeled packages like “Winter Luxury” and “Light Warmth,” enhancing awareness among B/C-tier users.

Long-Term Value of Tiered Infrastructure

1. User Lifetime Value (LTV): S-tier users spend ¥24,000 annually—17x C-tier users.
2. Social Asset Conversion: S-tier users drive 29% of total GMV through referrals, with their recommended customers spending 38% more than organic traffic.
3. Risk Resilience: Amid industry-wide 35% return rates, S-tier users maintained sub-5% returns due to deep engagement.

This system creates an “data insight → scenario prediction → resource exclusivity” loop, evolving from traditional “user-finds-product” logic to a white-label “product-trains-user” ecosystem.

As noted in an industry report: When segmentation reaches 213 tag dimensions, user decision costs drop 64%, while brand溢价 expands 3-5x.

3.2 Emotional Value: The Invisible GMV Engine

Livestreams with <20 viewers during non-peak periods still generated miracles like ¥100k annual spend per customer.

Building Emotional Maps via Private Domain Data

White-label brands use Enterprise WeChat to construct a “user emotion coordinate system”:

1. Moments Emotion Radar: AI analyzes posts about parenting, pets, or work stress, identifying “parenting anxiety” (38%), “career burnout” (27%), and “marital crisis” (15%).
2. Community Keyword Bank: High-frequency terms like “slimming,” “age-defying,” and “anti-copycat” in WeChat groups inspired XS-size collections and designer collaborations.
3. Conversation Granularity: The CRM detects deep needs like “I need a power suit to command respect” or “post-divorce style renewal,” triggering 1v1 service.

Precision Emotional Supply Chain Matching

For 20% core private domain users, implement a “three-tier emotional value delivery model”:

1. Foundation (Empathy): Mother’s Day livestreams feature “working mom armor” narratives and wrinkle-free shirts, achieving 42% conversion.
2. Premium (Scenario Empowerment): Target divorced women with “New Wardrobe Plans” showcasing “reunion comebacks” and “travel encounters,” lifting order values to ¥8,000.
3. Custom (Personality Mirroring): Build “style DNA banks” for VIPs (213 parameters like shoulder width and color preferences) enabling preemptive recommendations.

Asymmetric Competition via Emotional Infrastructure

Core elements of this “emotional value supply chain”:

1. Content Industrialization: A 500+ phrase empathy library, e.g., “This trench’s waistline is like a ruler for life’s discipline.”
2. Agile Response: Deploy “emotional first-aid kits”—custom coupons and styling tips within 30 minutes of detecting negative posts.
3. ROI Tracking: SCRM data shows handwritten birthday cards yield 3.2x higher repurchase rates than bulk greetings.

This engine rewrites e-commerce logic: While rivals chase traffic, this brand earns 85% gross margin from 20% core users’ “emotional needs.” As its CEO stated: “Real GMV isn’t on livestream counters—it’s in being the ‘most understood’ brand in users’ hearts.”

IP Essence: Personified Trust Currency

White-label brands need private domain IP recognition, not public domain fame.

Growth Trap: Trust Erosion from Category Expansion

A linen apparel brand faced 27% churn in 2023 after adding seasonal items like sunscreen jackets. Only 12% of new buyers repurchased, with complaints spiking 58%. A VIP’s critique—”How are you different from fast fashion?”—sparked a trust crisis, eroding its “skin-friendly” equity.

Mindset Mining: From Fabric Traits to Emotional Bonds

The brand launched a “Cognitive Archaeology Project,” analyzing 32k chat logs:

• “Skin-friendly” appeared 46 times per 1k chats vs. “breathable” (22) and “eco-friendly” (15).
• Moms linked linen to “baby skin safety,” sensitive-skin users to “second skin,” designers to “natural aesthetics.”

This redefined its IP as a “skin-intimacy architect,” not just a fabric supplier.

Rational Category Expansion via Trust Radius

A three-tier expansion model around “skin-friendly” equity:

1. Core: Linen apparel with medical-grade allergen certification, slashing returns from 18% to 5%.
2. Derivative: Baby linen bedding with traceable cotton sourcing, hitting ¥2 million in debut month.
3. Extension: Hospital-collab therapeutic wear with medical-grade silicone edging, tripling order values.

Value Verification: The Miracle of Off-Season Turnaround

After three months of implementation, key data underwent structural changes:

1. Off-season (June-August) revenue surged by 317% year-on-year, with new products contributing 68% of the revenue.
2. The proportion of high-net-worth users (annual consumption > 50,000 yuan) increased from 3% to 11%.
3. Users spontaneously created over 24,000 UGC “Skin-Care Diaries,” boosting natural search traffic by 230%.

This case confirms the golden rule of IP construction: When a brand becomes the “sovereign spokesperson” of a specific, what it expands is not the product category, but the payment scenarios of user trust.

As summarized by its founder, “A true IP is not the recognizability of the logo, but the conditioned neural circuit in the user’s brain when facing choices.” The commercial value brought by this cognitive occupation is far more penetrating than short-term GMV.

Customer Assets: Co-Building Local Ecosystem from Going It Alone to Value Co-Creation

Traffic is limited, but traffic based on trust can extend upstream and downstream, expanding one’s own small ecosystem.

Licensed Products: Value Co-Creation Across Domains

With “skin-friendliness” at the core, construct a cross-industry cultural symbol ecosystem. For instance, White Label can collaborate with a tea dyeing intangible cultural heritage workshop to launch the “Symbiosis of Grass and Trees” series, combining tea dyeing craftsmanship with natural fibers to develop antibacterial fabrics containing tea polyphenols. This series achieves three levels of value enhancement through “product + cultural storytelling”:

1. Functional upgrade: Tea polyphenol penetration technology improves the antibacterial rate of fabrics, enabling the unit price to surpass conventional products.
2. Cultural premium: Each product comes with a handwritten note from an intangible cultural heritage craftsman, and scanning the code allows users to watch a documentary on the dyeing process, thereby increasing user retention.
3. Ecological payback: 5% of sales revenue is used to support tea farmers’ ecological planting, forming a closed loop of “consumption – protection – reproduction.”

Cultural Tour Exhibitions: Immersive Infiltration of Local Symbols

For example, activate local cultural assets through a “mobile museum”:

1. Space design: Create detachable touring exhibition devices with cotton and linen looms and miniature tea mountain landscapes to increase the number of interactive participants.
2. Data-driven: AR fitting mirrors capture users’ body data, generate personalized “Natural Aesthetics Reports,” and recommend matching solutions.
3. Ecological linkage: Tour exhibition sites are connected with local hotels and coffee shops. Users can collect stamps for redemption of licensed experience packs, thereby increasing customer traffic for surrounding merchants.

White Label’s themed exhibitions in local cultural plazas attract and local high-net-worth users, leveraging events and social media propagation to achieve a surge in local search indices.

Private Domain Membership Co-Creation: From Consumers to Ecosystem Co-Builders

Establish a “User Sovereignty Laboratory” to achieve three-level co-creation:

1. Product co-creation: Open the fabric library for members to mix and match designs, turning users’ voices into creative actions.
2. Content co-creation: KOC-shot “Tea Mountain Parent-Child Study Tours” short videos, when distributed through private domains, achieve playback volumes and redirect traffic to tea garden experience projects.
3. Rule co-creation: Members vote to decide the direction of the annual environmental protection fund, enhancing community activity levels.

Participating members’ annual average spending is often several times that of non-participants, and the recommended customer groups they bring in contribute to new GMV growth.

Ecological Infrastructure: Data-Driven Resource Integration

Construct a “four-in-one” ecosystem operation system:

1. Demand heat map: Real-time capture of all-domain “skin-friendly” related search terms to guide the development rhythm of new products (e.g., upon monitoring a surge in demand for “air-conditioned room moisturizing,” launch ramie moisturizing shawls within 72 hours).
2. Credit pass: Suppliers must pass 48 ecological indicator certifications (e.g., water consumption per unit of output value, dye degradability) to enter the whitelist.
3. Value distribution chain: A blockchain-based smart payment system automatically settles the revenues of ecological roles such as designers, raw material suppliers, and KOCs.
4. Carbon footprint ledger: Each product is labeled with the entire chain of carbon emissions from planting to finished clothing. Users can accumulate “ecological points” to redeem carbon-neutral benefits.

With this system, supply chain response speed and inventory turnover rates are improved.

Industry Enlightenment: A Qualitative Change from Transactions to Relationships

1. Symbolic assetization: Elevate “skin-friendliness” from a product attribute to a cultural matrix and achieve value breakthroughs through licensing (e.g., penetrate the Generation Z demographic by leveraging suitable IPs in the二次元realm).
2. Relationship monetization: Members are no longer just consumption units but “value amplifiers” of ecosystem nodes (e.g., open up a second growth curve through user co-created parent-child study tour projects).
3. Regional mindset monopoly: In corresponding regions, “skin-friendliness” related search terms become synonymous with the product category in people’s minds.

This ecosystem co-construction model is rewriting the rules of commerce—while peers are still competing for traffic, pioneers have already built an anti-cyclical growth moat through the triple leverage of “cultural symbols × local resources × user co-creation.”

As pointed out in the industrial digitalization report: Over the next decade, the competitive advantage of leading brands will depend on the depth of co-creation and the density of data among participants in their ecosystem.

PS: The translation is done by AI.