Power BI & Data Insights Executive – E-Commerce
Linen TrailThrissur, Kerala, India13 hours ago
Job descriptionAnalyze daily / weekly / monthly order trends , average order value, and contribution by channels. Track campaign performance vs. revenue and profitability (Meta, Google Ads, Email, WhatsApp). Identify patterns in cart abandonment, discounts, and return rates . Create customer segmentation based on frequency, recency, and spend (RFM). Track repeat rate, lifetime value (LTV) , and customer acquisition cost (CAC) . Build cohorts to analyze retention and customer journey (first purchase → repeat → loyalist). Integrate data from Shopify, Contlo, and CRM tools for unified customer intelligence. 2–3 years of experience in Power BI (DAX, Power Query, data modelling). Strong skills in SQL, Excel , and data transformation. Experience connecting Power BI with Shopify, Meta Ads, Google Ads, and Google Analytics APIs or exported data. Understanding of e-commerce KPIs (AOV, ROAS, retention, CAC, LTV, RFM, etc.). Ability to independently design dashboards, automate data refreshes, and communicate insights to non-technical teams.
Linen Trail is India’s Quiet Luxury Linen Label — a slow fashion brand crafting 100% Pure Linen apparel for men. We are a digital-first D2C brand with a decade-long legacy of craftsmanship, innovation, and data-led decision-making.
We are now building our internal Data & Insights function to drive the next phase of growth through deep analytics on product, order, and customer behaviour.
Role Overview
We are looking for a Data Analyst experienced in Power BI who can help build an insights engine for Linen Trail. You will work closely with the marketing, operations, and product teams to design data models and dashboards that track everything from top-performing fabrics and fits to customer retention and repeat patterns.
Key Responsibilities
Product-Level Insights
- Build dashboards to track sales by product , color , fabric , and size , identifying bestsellers and slow movers.
- Map fabric consumption vs. inventory to aid predictive manufacturing.
- Identify top 20% products contributing 80% of revenue and recommend “Just Before Time” manufacturing volumes.
Order-Level Insights
Customer-Level Insights
Requirements
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Ecommerce Executive • Thrissur, Kerala, India
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