My Portfolio
DATA ANALYST
Hello, my name is Agatha Puspita Astri
As a data-driven analyst, I combine technical skills and strategic insights to solve complex problems and deliver impactful results. Through hands-on projects, I focus on turning data into actionable insights to drive meaningful change and improve outcomes.
Skills
Projects
World Happiness Report In Southeast Asia and East Asia
Project background
The World Happiness Report is used to enhance the quality of life. Happiness scores measures the well-being of countries. This analysis aims to identify the main factors affecting happiness by examining economic and health metrics. We hope to provide insights that can help boost happiness score and overall well-being globally.
Methodology
Analyzed sales data and customer behavior to identify patterns related to cart abandonment and repeat sales. Focused on key metrics such as successful sales, customer demographics, and payment preferences to understand trends.
Result
A strong correlation between GDP per capita, healthy life expectancy, and happiness scores.
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Sales Performance Analysis of WishfulBazaar Company
Project background
A leading e-commerce platform, faces challenges with consistent sales growth and high cart abandonment, impacting revenue. The company aims to drive business expansion by encouraging repeat purchases and using data-driven insights to better understand customer behavior, enhance the shopping experience, and improve sales performance.
Methodology
Analyzed sales data and customer behavior to identify patterns related to cart abandonment and repeat sales. Focused on key metrics such as successful sales, customer demographics, and payment preferences to understand trends.
Result
Improving service quality at WishfulBazaar can reduce cart abandonment rates and increase repeat sales, enhancing customer retention and overall profitability.
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Customer Segmentation Analysis of RevoU Bank
Project background
A leading financial institution, offers a range of services, including credit cards, to a large customer base. Despite strong customer acquisition, the bank faces challenges in increasing credit card usage among existing clients. To drive revenue growth and enhance loyalty, RevoBank aims to better understand customer behavior and implement personalized promotional strategies.
Methodology
Analyzed three years of transaction data to segment customers by spending habits and engagement, and developed targeted customer personas.
Result
The analysis identified three customer segments: Cluster 1 (high-value clients) should be prioritized with premium services, Cluster 0 (frequent, low-spending clients) can benefit from targeted promotions, and Cluster 2 (moderate spenders) may need personalized offers to increase engagement. By focusing on these segments, RevoBank can drive higher credit card usage and boost revenue.
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TokoBli Campaign Performance Analysis
Project background
A major e-commerce platform in Indonesia, needed to identify the most effective promotional campaign for future use. The company regularly runs twin date promotions, and determining which campaign drives the highest sales is crucial for optimizing future strategies. A high budget has been allocated for these promotions, so it is essential to maximize returns while minimizing costs.
Methodology
Data from three twin date promotional campaigns (10/10, 11/11, and 12/12) was collected and analyzed. Key metrics such as total revenue, transactions, and average revenue per transaction were evaluated to assess performance. Data cleaning and statistical analysis techniques were applied to compare the effectiveness of the campaigns.
Result
The 11/11 campaign was identified as the top performer after analyzing the three campaigns, providing actionable insights for future promotional strategies.
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Customer Satisfaction Insights for OverU Hotel
Project background
A major multinational corporation is facing two key challenges: improving the process of identifying high-potential employees for promotion and ensuring they receive appropriate development promptly. The company seeks to enhance overall guest satisfaction, aiming to raise the average Net Promoter Score (NPS) from 3.2 to 4.0 within the next year.
Methodology
Collected NPS survey data from 482 guests and analyzed feedback to identify improvement areas. Trends were visualized, leading to recommendations aimed at raising the NPS score from 3.2 to 4.0 within a year.
Result
Recommendations were proposed to optimize employee performance, enhancing their readiness for promotion opportunities.
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Funnel Analysis and Marketing Channel Performance of PeopleU
Project background
PeopleU, a B2B SaaS company, offers an HR management platform to streamline HR tasks through a subscription model. This analysis focuses on improving PeopleU’s marketing strategy to increase conversion rates and attract high-quality leads by 5%. By examining lead traits and conversion trends, the goal is to provide actionable insights to boost lead quality, optimize resources, and drive steady customer growth.
Methodology
Analyzed session sources, subscription types, and funnel stages to identify high-performing marketing channels and key drop-off points. Utilized SQL and exploratory data analysis to assess conversion rates, revenue contributions, and lead quality. Investigated patterns to optimize resource allocation and improve marketing efficiency.
Result
Referral channels showed the highest conversion rate (47.6%), highlighting their effectiveness in attracting high-quality leads. Funnel analysis revealed significant drop-offs during the qualification and deal closure stages, suggesting areas for process improvement. Optimizing marketing spend and refining targeting strategies can enhance lead quality and overall conversion efficiency.
View ProjectLanguages
Bahasa Indonesia (Native)
English (Fluent)
Japanese (Intermediate)