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emma_sheng55

DataInsightPro

@emma_sheng55

Customer Acquisition and Retention and AI Accelerated

China
Inglês, Chinês
Algumas informações são exibidas no idioma inglês.
Sobre mim
Is your acquisition cost rising while retention drops? I'm a senior data analyst with 12 years across insurance, FMCG, internet, and fintech. I help you: • Find when and why customers leave (cohort & retention) • Identify VIPs and churn risks (RFM segmentation) • Stop wasting ad budget (ROI & attribution) • Recover silent high-value customers (win-back) • Automate weekly/monthly reports Traditional analysis takes 2 weeks. I deliver in 3 days using AI — without cutting corners. No 50-page reports nobody reads. Just specific answers with clear next steps. 📩Message me. I respond within 24 hours.... Saiba mais

Habilidades

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emma_sheng55
DataInsightPro
offline • 

Conheça meus serviços

Consultoria em data analytics
I will do customer retention analysis and rfm segmentation
A partir deUS$ 150 /projetoMais detalhes

Portfólio

Experiência profissional

Freelancer.com

Freelancer.com

Período integral • 12 yrs 1 mo

Analytics Manager

Sep 2019 - Present • 6 yrs 11 mos

• FMCG (2019-2021): Managed end-to-end customer acquisition projects with C-level reporting; designed loyalty program KPIs and operational metrics to identify growth opportunities • Internet (2021-2022): Built automated BI pipelines tracking GMV and sales performance; developed 2-month forward sales forecasting models incorporating campaign seasonality • Fintech (2022-Present): Develop propensity models and pricing strategies for the products; optimize marketing spend allocation and channel performance across digital and offline touchpoints • Integrate online/offline customer data to build 360° profiles, enabling precision marketing and channel diversion strategies • Design retention frameworks combining RFM, cohort analysis, and predictive modeling to recover at-risk revenue and improve customer lifetime value

Lead Data Analyst

Jun 2014 - Aug 2019 • 5 yrs 2 mos

Consultant Company • Developed propensity models (logistic regression, decision tree, random forest) for tier-1 US auto and health insurers, improving campaign response rates by 25-40% • Built customer segmentation frameworks integrating demographic, transactional, and market research data across 100M+ records for personalized targeting • Managed billion-level data integration, cleaning, and exploration; designed executive KPI dashboards and automated reporting systems • Reduced policyholder churn through cross-selling optimization and predictive churn modeling, improving retention 15% while maintaining cost efficiency • Led data quality assessment and list testing programs for internal and external vendor data