Quick BI x Puracotton: Spun Data into Gold

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Client Overview:

Purcotton is a Chinese consumer brand owned by Winner Medical that pioneered 100 % cotton daily-use products. Founded in 2009, it has expanded from sanitary pads into mother-and-baby, personal-care and home-cleaning categories. The company has grown from an early operating loss to annual sales exceeding RMB 4 billion, supported by 300+ offline stores, flagship e-commerce shops and WeChat mini-programs. Today it manages a nationwide supply chain built on medical-grade spun-lace cotton technology and serves more than 42 million registered members, treating membership loyalty as a strategic growth engine and investing heavily in data-driven customer intimacy.

“E-commerce competition is now blooming; brand strategy must shift from chasing ‘traffic’ to retaining it, focusing on the value of existing users. Members are the heart of user operations—by forging emotional bonds through the membership system and nurturing those relationships with care, brands can unlock much deeper value.”

— Purcotton

Problem Statement:

Purcotton’s rapid omni-channel expansion created a 42-million-strong member base, yet its legacy marketing stack could no longer support refined operations. Without SKU-level data and AI-driven personas, the team struggled to isolate high-value cotton lovers, reactivate dormant users or orchestrate profitable cross-category journeys. Previous Double 11 store-visit conversions plateaued and household-cleaning penetration among mother-and-baby shoppers remained low, limiting incremental revenue and lifetime value. Furthermore, fragmented data silos hampered real-time decisioning, causing missed upsell windows and promotional waste.

Solution Implemented:

Purcotton deployed Lingyang Data Intelligence’s full-funnel BI suite, linking its CDP, POS and mini-program events into one analytical layer. AutoML clustering models divided mothers into “premium delicate”, “trendy new” and “value-seeking township” cohorts, scoring each on activity, spend and lifecycle. A knowledge graph mapped these personas to SKU attributes, exposing gifting gaps in items such as nappies and antibacterial wipes. Smart Card-SMS and real-time dashboards let marketers preview predicted lift before launching campaigns.

Implementation finished in six weeks through Snowflake connectors and Kubernetes micro-services, while a zero-code journey builder empowered marketers to design pre-heat, burst and re-engagement tracks. During warm-up, silent members received benefit cards stressing cotton safety; peak-hour AI-personalised messages pushed coupons plus “super-head” livestream reminders, and reinforcement-learning models timed follow-ups by open-rate prediction. Pregnancy-status labels triggered medical-grade diaper content, and churn-risk scoring automated secondary offers. All decisions rendered in milliseconds via edge-deployed recommendation services.

Outcomes Achieved:

In the first Double 11 after launch, store-visit-to-purchase conversion soared 150%+, while livestream-guided traffic supplied over 10% of total footfall and raised in-store conversion 30%. Active-member ratio climbed 20% versus the 618 festival, and cross-purchase penetration between household-cleaning and mother-and-baby lines jumped 50%. Pregnancy-stage personalisation added another 70% uplift on targeted SKUs. Qualitative NPS surveys show higher satisfaction, boosted emotional resonance and cemented Purcotton’s reputation as families’ trusted cotton authority.

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Quick BI x Puracotton: Spun Data into Gold

Join Alibaba Cloud Discord Community! Accept Your Invitation

Access Quick BI for free! Official Website

Client Overview:

Problem Statement:

Solution Implemented:

Outcomes Achieved:

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