Turning Data
into Decisions
A collection of end-to-end analytics projects spanning retail, fintech, hospitality, and food-tech — built with Power BI, Excel, and statistical analysis.
Customer segmentation, statewise performance, and product sales analysis across India using Power BI dashboards.
Analyzed 7,298 credit card customers to study credit utilization patterns across income, education, and demographics.
Deep-dive into 58.7K bookings and 166M revenue across 22 states, analyzing booking trends, hotel types, and customer segments.
Statewise order patterns, most-ordered food items, average ratings, and top city performance across India.
Smart Bazaar
Customer Analysis
Performed customer analytics to identify behavioral patterns and marketing opportunities across Indian states. Built multi-page dashboards visualizing product sales, regional performance, and profitability metrics using Power BI and Excel.
- Apparel dominates — Western, Sport, Ethnic & Sleep Wear account for 4 of the top 5 product categories by sales volume.
- Northern states (Haryana, Assam, UP) consistently outperform southern and eastern counterparts in overall sales.
- Profit margins are healthy across top categories — Western Wear leads with ₹8.65L profit on ₹40.4L sales (~21% margin).
- Grocery staples (Vegetables, Milk, Butter) show strong volume but lower margins — typical of FMCG segments.
Demonstrated ability to use business analytics tools to derive strategic marketing insights. The dashboard enables category managers to identify underperforming regions and prioritize high-margin product lines. Statewise analysis supports targeted promotions and inventory planning across India's diverse retail landscape.
Credit Utilization &
Customer Segmentation
Built an interactive Power BI dashboard analyzing 7,298 credit card customers to study credit utilization and financial behavior. Designed KPIs and segmentation analysis across income, education, marital status, and age groups to identify high-utilization segments and support lending strategies.
- Lower-income customers (<₹30K) have the highest utilization ratios — 14× more than high-income (111K+) customers.
- Post-graduate customers show highest utilization, suggesting education level correlates with credit dependency.
- Married customers (52%) drive most utilization, likely due to household expenses and lifestyle spending.
- Males have 75.47% higher average credit limits (₹12.63K) vs females (₹4.11K) — a significant gender gap in credit access.
- 94% of customers are in the Gold tier — opportunity to upsell Platinum benefits to eligible high-spending segments.
Generated insights to support credit risk assessment, customer segmentation, and data-driven lending strategies. The dual-dashboard approach (Credit Utilization + Customer Profile) enables risk teams to proactively identify over-leveraged segments and design targeted credit limit revisions, while marketing teams can identify upsell pathways for Platinum conversion.
OYO Hotel Booking
Analytics Dashboard
Developed a Power BI dashboard analyzing 58.7K bookings and ₹166M revenue to evaluate hotel booking trends and performance. Covered monthly trends, peak booking times, location analytics, hotel type performance, and customer behavior segmentation.
- December is peak season with 8.2K bookings; July is lowest at 2.2K — suggesting strong year-end travel demand.
- Evening hours (18:00–21:00) drive the most bookings (14.6K) — optimize marketing for evening push notifications.
- Maharashtra is the #1 state; Shimla, Delhi, and Panjim are top destination cities.
- 75.22% of payments are post-checkout — suggests trust in OYO's pay-later model.
- 64.55% of guests are non-couples; leisure travelers dominate (77.79%) over business travelers.
Identified leisure travelers and couples as the dominant booking segments, supporting targeted marketing strategies. Analyzed booking time patterns to recommend optimal push notification windows. Location intelligence revealed underserved states (Bihar, Chhattisgarh) with growth potential for OYO's expansion strategy.
Zomato Order Tracking
Dashboard
Built an interactive Zomato order tracking dashboard analyzing statewise order volumes, most-ordered food items, average order value, food ratings, and top performing cities. Identified key demand patterns and regional food preferences to support restaurant and logistics decisions.
- Biriyani dominates all other items by 35%+ — a clear category leader worth prioritizing for restaurant partnerships.
- Condiments (Mint Sauce, Onion Chutney, Red Sauce) feature heavily — indicating high add-on order behavior worth upselling.
- Rajasthan leads statewise orders (275), driven by Udaipur — a tourist-heavy city with high food service demand.
- Average food rating of 3.489 suggests room for quality improvement — targeting restaurants below 3.0 for intervention.
- Average order value of ₹295.5 positions Zomato in the affordable-mid segment, reflecting India's price-sensitive market.
Dashboard enables food-tech operators to identify regional demand hotspots, optimize menu recommendations, and improve delivery logistics. Item-level frequency analysis reveals upsell opportunities through condiment bundling, while city-level rankings support restaurant acquisition strategy in underserved but high-potential markets.