
E-commerce Growth: +40% Revenue Through Data-Driven Decisions
Built data analytics capability for online retailer. From guessing to knowing. From stagnation to 40% growth.
THE SITUATION
CLIENT:
E-commerce retailer (fashion, home goods)
Channels: Shopify, Lazada, Shopee, own website
Industry: Online retail
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THE CHALLENGE:
• Multiple sales channels, no unified data view
• Which products are actually profitable?
• Which customers should we focus on?
• Marketing spending guessed at (no ROI data)
• Inventory constantly misaligned
• Couldn't answer basic questions ("What's our profit margin?")
THE APPROACH

1
DATA AUDIT (Week 1)
What we found:
✓ Data sources: Shopify, Lazada, Shopee, WooCommerce, Google Analytics, Accounting system
✓ Problem: All separate, no unified view
✓ Data quality: Inconsistent product categorization, missing customer data
✓ Opportunity: Consolidate into single source of truth
2
ANALYTICS PLATFORM BUILD (Weeks 2-4)
What we built:
✓ ETL pipeline: Automated daily data consolidation
✓ Executive dashboard: Revenue by channel, product, customer
✓ Operational dashboard: Real-time inventory, order status, fulfillment
✓ Marketing dashboard: Campaign ROI, customer acquisition cost, lifetime value
✓ Product dashboard: Profitability by product, category, supplier
Tools used: Power BI connected to databases, automated refresh
3
TRAINING & ADOPTION (Week 5)
What happened:
✓ Team trained on dashboard interpretation
✓ Weekly insights meetings started
✓ Data-driven decision-making became the norm
✓ Executives could answer questions in minutes
THE RESULTS
BEFORE ANALYTICS:
• Revenue growth: 5% annually (stagnating)
• Profit margin: Unknown (guessed at 15%)
• Inventory: 20% overstocked, 10% out of stock
• Marketing ROI: Unknown
• Customer retention: Not tracked
AFTER ANALYTICS (12 months):
✓ 40% revenue growth (accelerated)
✓ Profit margin: Identified as 22% (not 15%)
✓ Inventory optimization: 95% stock accuracy
✓ Marketing ROI: Tracked by channel, optimized spend
✓ Customer retention: Increased from 18% to 28%
FINANCIAL IMPACT:
• Revenue increase: IDR 2B (from IDR 5B to IDR 7B)
• Improved margins: Additional IDR 400M profit (additional 2% margin)
• Reduced waste: IDR 150M (less overstocking)
• Better focus: IDR 300M savings (optimized marketing spend) Total impact: IDR 2.85B additional profit

HOW GROWTH HAPPENED
1. CHANNEL OPTIMIZATION (45% of growth)
BEFORE: Equal marketing spend across all channels
AFTER: Data showed Lazada had 3x ROI of Shopee
Action: Shifted 60% of budget to Lazada
Result: IDR 900M additional revenue
2. PRODUCT FOCUS (30% of growth)
BEFORE: Treated all products equally
AFTER: Data showed 20% of products = 80% of profit
Action: Expanded product line in high-margin categories
Result: IDR 600M additional revenue
3. CUSTOMER SEGMENTATION (15% of growth)
BEFORE: Marketing to all customers same way
AFTER: Data showed 15% of customers = 60% of revenue
Action: Created loyalty program for high-value customers
Result: IDR 300M additional revenue
4. INVENTORY EFFICIENCY (10% of growth)
BEFORE: Stock based on guesses
AFTER: Stock based on demand forecasting
Action: Better cash flow, faster inventory turns
Result: IDR 200M additional revenue
KEY DASHBOARDS THAT DROVE DECISIONS
1. PROFITABILITY BY PRODUCT
Before: "Let's sell everything"
After: "These 15 products = 80% of profit, let's focus there"
Action: Expanded high-margin products, discontinued low-margin
2. CUSTOMER LIFETIME VALUE
Before: "All customers are equal"
After: "These 50 customers = 30% of revenue"
Action: Invested in retaining top customers
3. CHANNEL ROI
Before: "All channels are good"
After: "Lazada: 3x ROI, Shopee: 1x ROI, Own site: 2x ROI"
Action: Reallocated budget accordingly
4. INVENTORY FORECAST
Before: "Let's stock more to be safe"
After: "Actual demand for each product"
Action: Reduced overstock, prevented stockouts
Timeline
Week 1: Data audit, consolidation plan
Week 2-4: Build ETL pipeline, create dashboards
Week 5: Team training, adoption
Month 2-12: Continuous insights, optimization

LESSONS LEARNED
What drove success:
✓ Started with data consolidation (had clean baseline)
✓ Built dashboards that answered real business questions ✓ Weekly insights meetings (made dashboards part of routine)
✓ Celebrated data-driven wins (built culture)
What took time:
- Initial data quality cleanup
- Teaching team to use data vs. intuition
- Changing decision-making culture
