Laura Yan - Product MAnager,

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Network Power<100 people

Roles

💸100%

Marketing

✔️100%

🎓100%

Student

Geos

🇺🇸100%

United States

Work Background

MeituanProduct Manager

Dec. 2020 - Jan. 2023Shanghai, China · On-site• Product manager of a flash sale channel. Performed product function iteration, product data analyzing, promotional merchandise investment and promotional marketing activities. o Wrote PRDs and worked with engineering, design, and marketing to deliver a new front page and back-end system. o Gathered user feedback via A/B testing, surveys, user testing, and interviews, integrating insights into product enhancements. o Created product dashboard metrics for continuous monitoring and analysis of user behavior and sales performance. •Led a team to execute an integrated marketing project, launched 30+ campaigns, yielding a 50% increase in revenue. o Monitor and analyze campaign performance and adjust strategies as needed to maximize ROI and achieve business objectives. o Develop and manage budgets, timelines and metrics for all marketing campaigns and initiatives.

Shenzhen Pingan Bank Co., Ltd.app Product Manager

Aug. 2019 - Jun. 2020Shanghai, China · On-site•Managed the credit card feature on the mobile app, overseeing account management and bill payment functionalities. •Launched the company’s first credit card community from inception, enhancing user retention by 10% -MAU and visit frequency. oDeveloped initial PRDs, conducted research on online forums, and supervised policies, successfully launching in 6 months. oEstablished content rules and tagging systems, including traffic operations, UGC incentives, and B-side operations. •Launched new user features such as specific pages and bill-cutting function, achieving a 20% reduction in new user activation costs and a 15% increase in activation rate.

ByteDanceUser Engagement Manager

Dec. 2018 - Jul. 2019Shanghai, China · On-site•Successfully anticipated an emerging trend, leading to a campaign that garnered millions of views within two weeks. --Employed 5W model for in-depth data analysis of trending content , identifying key characteristics such as creator demographics, video attributes, and optimal timing for content release. Conducted case study tracing the evolution of a trending topic from inception, pinpointing the critical two-week period post-creation as pivotal for momentum. •Created a filter that reached the top users and resulted in a million user-shot videos with it. oExecuted a thorough analysis of the attributes associated with top-performing filters and their creators. Leveraged insights to develop and introduce a new filter concept, selecting the designer based on previous data performance.

Alibaba GroupKey Account Manager

Jan. 2017 - Aug. 2018Shanghai City, China · On-site• Formulated Key Account team strategies and orchestrated traffic operations. • Devised a comprehensive group traffic resource strategy to empower merchants. • Managed 10+ food and beverage brands (including McDonald's, Burger King, Haagen-Dazs). • Strategically planned online and offline promotional campaigns, significantly boosting the adoption of offline Alipay payments.

Yihaodianapp Product Manager

Jul. 2014 - Jan. 2017shanghai · On-siteProduct manager of three homepage sections, wrote PRDs, BRDs to define the product. •Conducted the redesign and optimization of those product functions, budget allocation as well as event planning and execution. • Achieved significant daily order volume increase on the flash sale channel, while cutting subsidy costs by 75%. --Analyzed the relationship among price, sales, and traffic weekly to decide the discount price of flash sale commodities. --Crafted a recommendation algorithm by selecting and weighting relevant factors, including user engagement (views and clicks) and purchase behaviors, along with product attributes such as discount rates and historical sales figures. --Conducted A/B tests to evaluate recommendation algorithm performance. --Delivered weekly analyses on product performance, traffic metrics, user purchasing, and item-level sales data to guide decisions.

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