β Evereve β βEnd to End Full Stack Analyst Project | Data ingestion (CRM + ERP + WEB) |AWS-ETL-Pipeline-Automation | Driving Sustainable Sales Growth and Marketing Efficiency in Womenβs Health through - Product & Marketing Analysis
π΄ Product & Marketing Research Analyst initiative | β FMCG β Womenβs Health & Personal Care β Feminine Hygiene β B2C
1. Understand Company Strategic Vision & Needs β 2. Project Overview β 3. Problem Statements β 4. Objectives β 5. Counter Questions to Stakeholders (Clarify Business Needs & Targets) β 6. EDA (Data Cleaning + Data Validation) + ETL Flowchart β 7. Data Modelling chart β 8. Live Power BI Dashboard β 9. Insights + Recommendations (Storytelling) β 10. Business Impact (Pre & Post Analysis) β 11. Challenges β 12. Enhancements β 13. Boardroom PPT with Storytelling
Evereve is a womenβs hygiene & personal care brand focused on safe, high-quality feminine products that promote dignity, awareness, and well-being across all socio-economic segments.
- Industry: FMCG (Personal Care)
- Role Focus: Product Strategy + Marketing Performance
π¦ Products (Pack-size / SKU) β πΈ Pricing & Promotions β π Retention & Repeat Purchase β π Campaign Uplift β πΊοΈ Regional Scaling
- β Sales driver identification & SKU contribution analysis
- β Repeat purchase & loyalty insights (retention / churn patterns)
- β Promotion & pricing impact measurement (uplift vs margin)
- β Campaign effectiveness & marketing ROI optimization
- β Region/channel expansion recommendations for scalable growth
The sanitary napkin market in India is highly competitive and fast-changing, driven by:
- Strong competition from established and emerging brands π·οΈ
- Price-sensitive customers and heavy discounting wars πΈ
- The need to improve awareness, trust, and repeat purchases
- Changing consumer expectations for comfort, safety, and quality πΏ
This project addresses the need for data-driven growth and smarter decision-making. By analyzing product, sales, and marketing performance, we aim to:
| Objective Area | Goal | Output |
|---|---|---|
| π¦ Product Performance | Analyze pack-size & SKU-level performance | Best sellers + profit drivers + improvement zones |
| π Customer Retention | Study repeat purchase behavior & churn patterns | Loyalty strategy + long-term growth levers |
| πΈ Pricing & Promotions | Measure pricing & discount impact | Margin-safe pricing + optimized promo planning |
| π― Marketing Efficiency | Evaluate campaign performance & efficiency | ROI improvement + reduction of wasteful spend |
| πΊοΈ Expansion Strategy | Identify high-potential regions & channels | Expansion roadmap + demand hotspots |
For more realtime business impact, I framed the following counter-questions for stakeholders across Marketing, Product, Sales, Production, and Growth Section:
| Area | Key Question | Business Decision Enabled |
|---|---|---|
| π― Growth | Acquisition vs Repeat β what is the 3β6 month uplift target? | Growth roadmap |
| π° Marketing ROI | Which are the traget and Priority metrics for next upcoming months : ROAS / CAC / Cost per Repeat / Margin after spend? | Budget allocation & campaign |
| π¦ Product Strategy | Priority Optimization which one volume or margin? | SKU roadmap & pack-size optimization |
| π Channel Focus | Priority metric: Retail / D2C / Marketplace- what is the 3β6 month uplift target? | Channel strategy + execution focus |
Built an end-to-end AWS ETL & BI analytics platform processing 1M+ data records across CRM, ERP, Production, and Marketing data using Amazon S3, AWS Glue, Athena, and QuickSight.

| WHAT | WHY |
|---|---|
| π§ Business Problem | Sales in Karnataka and Delhi were lagging behind other major states, indicating uneven regional performance. |
| π Insight | Lower conversion and seasonal engagement were observed compared to western and southern markets. |
| π― Action | Targeted discounts and festival-led campaigns (Diwali & holiday offers) were rolled out in Karnataka and Delhi. |
| β± Timeline | Campaigns were active for 8 months. |
| π Impact | Delhi sales increased by 21% and Karnataka by 28% compared to the pre-campaign baseline. |
| π‘ Outcome | Sales distribution became more balanced, improving overall performance across regions. |
| Before Campaign | After Campaign |
Team Size: 2
Author: Priyanka De
Proflie - Priyanka De
