MARKETING GROWTH PORTFOLIO / AI + BRAND + DATA

Yufeng Hu, MS in Applied Analytics from Columbia University. I connect marketing growth, AI content applications, brand positioning, and data workflows into one capability portfolio: understanding audiences, translating business context, and building systems that execute.

Columbia AnalyticsMS Applied Analytics / Data analysis training
AI ContentFrom content cold starts to AI visuals, scripts, editing, and review
Brand + DataAudience insight, positioning language, and business data assets
01 / New Media Projects

10M+ Xiaohongshu Views + Brand Content Operations

01

Over 10 million views and 36K followers in three months, plus a Brezi coffee machine content project covering scripts, shooting, editing, and AI-generated visual assets.

Xiaohongshu account data overview
Xiaohongshu AI Virtual Character

Viral Xiaohongshu AI Virtual Character Account

Built an AI virtual character for Xiaohongshu image-text content, using an outsider perspective, Chinese daily-life scenes, and misunderstanding-driven contrast. Through topic testing, cover optimization, tone refinement, and post-launch review, the account completed a cold start in three months and produced a reusable viral image-text content method.

10M+Total views
36KCold-start followers
27KPeak likes per post
RMB 6,888Commercial quote
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Brezi coffee machine product visual
Brezi / Campaign Case

Brezi Coffee Machine AI Commercial Content

For a premium cold-brew coffee machine, I broke down the product selling points and delivered English short-video scripts, AI ad demos, poster visuals, and campaign materials, translating “cold drink efficiency” into brand content that can actually travel.

10+AI ad demos
RMB 1,500Per-video quote
2-4 postsMonthly content plan
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02 / Brand Positioning

From Content Traffic,
to Brand Mindshare.

02

The positioning cases show another layer of business judgment: why customers choose, what mental position a brand should occupy, and how product, channels, and communication should align.

Lao Xiang Ji brand logo
Xuji Seafood brand logo
Lao Xiang Ji / Positioning Context

National Positioning for a Regional Restaurant Brand

The key in the Lao Xiang Ji case is not only “expanding beyond Anhui,” but finding a quality-oriented route within Chinese fast food: a more premium, more reassuring brand position connected to middle-class customers, family occasions, store experience, product, and supply-chain alignment.

RMB 1B -> 8.8BBeyond AnhuiNo.1 national Chinese fast-food brand
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Xuji Seafood / Strategy Upgrade

From Affordable Seafood to Business Banquet Occasions

The Xuji Seafood case focuses on upgrading from a “seafood category” to a “business banquet need.” Seafood is the entry point; business banquets are the more mainstream, stable, and higher-paying occasion that better supports cross-city expansion.

RMB 400M -> 1.5BChangsha -> Wuhan / Shenzhen / ShanghaiNo.1 national seafood restaurant brand
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03 / Work Experience

Turn Judgment
into Systems.

03

The work section shows how content judgment and business understanding enter real organizations: processing data, building workflows, driving collaboration, and using AI and automation to reduce repetitive work.

Operating Layer

CNPCG + Everbright: Real Business Contexts.

One side is trade data systems, risk monitoring, and AI workflows; the other is customer scoring, feature engineering, and precise marketing in banking. Together they show that analysis should not stop at reports; it should enter business action.

CNPCG / Data Infra + Risk Monitoring

CNPCG: Business Data, Risk Monitoring, and AI Workflows

Built around customer, contract, order, payment, credit, overdue, and fulfillment data, this work pushed trade data infrastructure and credit risk monitoring forward, turning scattered information into traceable, reusable dashboards and workflows.

Risk monitoringData platformAI workflow
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China Everbright Bank / Analytics Case

Everbright: Customer Scoring and Precision Marketing Analytics

In a retail banking marketing analytics context, I worked on customer segmentation, feature engineering, and model scoring, translating data outputs into actionable marketing leads that connected model judgment with business execution.

Customer segmentationModel scoringPrecision marketing
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04 / Education

Education as
the Final Backing.

04

Education closes the portfolio: after projects and business experience, it explains where the data training, business context, and long-term learning foundation come from.

Columbia University
MS Applied Analytics
Trained in business analytics, data modeling, visualization, and analytical storytelling, strengthening the ability to break complex business problems into data problems and translate them back into business language.
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Zhongnan University of Economics and Law
Finance and Business Foundation
A Chinese finance-and-law university background that built a foundation in business environments, market mechanisms, and operating problems, complementing later data analysis and brand judgment.
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