INTL
Freelancer
어려움
외주
원격 가능
Customer Retention Data Analysis
예산
$250~$750 USD
예상 기간
2~4주
난이도
어려움
기술 스택
Python
SQL
Tableau
Power BI
Data Analysis
Data Visualization
Predictive Analytics
Machine Learning
Database Administration
Pandas
Scikit-learn
Jupyter Notebook
AI 분석 요약
이 프로젝트는 고객 데이터를 분석하여 고객 유지율(Retention Rate)을 높이는 데 필요한 실행 가능한 통찰력을 도출하는 것을 목표로 합니다. 원본 데이터 클리닝 및 통합, 탐색적 분석, 이탈 예측 모델링을 수행하고, 대시보드와 보고서를 통해 핵심 이탈 위험 순간과 즉시 실행 가능한 개선 방안을 제시해야 합니다. 데이터 분석, 예측 모델링, 데이터 시각화 역량이 필수적입니다.
프로젝트 원문 설명
I’m sitting on a sizeable pool of customer data and need clear, actionable insight into why clients stay—or slip away—so I can sharpen our overall experience. The single metric I care about right now is retention rate; every query, chart, and model should trace back to that outcome.
Here’s how I picture the engagement:
• Clean and consolidate the raw customer datasets I’ll supply (CSV and database exports).
• Run the exploratory analysis and segmentation needed to surface churn-related patterns.
• Build predictive or descriptive models—whichever proves most reliable—to highlight the moments of greatest attrition risk.
• Present findings in a concise slide deck plus an interactive dashboard (Python, SQL, Tableau or Power BI are all acceptable) that lets me slice retention by cohort, tenure, and key behaviours.
• Conclude with two or three priority recommendations I can act on immediately to raise retention.
I’ll provide sample data before kickoff so you can scope effort precisely, and I’m happy to clarify field definitions or business rules along the way. Let’s turn the raw numbers into a roadmap for keeping more of our customers delighted and loyal.
Here’s how I picture the engagement:
• Clean and consolidate the raw customer datasets I’ll supply (CSV and database exports).
• Run the exploratory analysis and segmentation needed to surface churn-related patterns.
• Build predictive or descriptive models—whichever proves most reliable—to highlight the moments of greatest attrition risk.
• Present findings in a concise slide deck plus an interactive dashboard (Python, SQL, Tableau or Power BI are all acceptable) that lets me slice retention by cohort, tenure, and key behaviours.
• Conclude with two or three priority recommendations I can act on immediately to raise retention.
I’ll provide sample data before kickoff so you can scope effort precisely, and I’m happy to clarify field definitions or business rules along the way. Let’s turn the raw numbers into a roadmap for keeping more of our customers delighted and loyal.
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