Third Wave Coffee

Third Wave Coffee is one of India’s fastest-growing coffee chains, with a rapidly expanding network of outlets across multiple cities. The company relies heavily on data to track performance, experiment with pricing, and understand customer behaviour across formats and regions.

During my internship, I worked on weekly data analytics projects using real operational datasets covering sales, orders, outlets, cities, store formats, and products. The data was provided in raw Excel formats and required extensive cleaning, structuring, and analysis before insights could be drawn.

Each assignment involved transforming granular transactional data into meaningful metrics, visualisations, and written insights within tight turnaround timelines.

• Analysed target versus actual sales at monthly and weekly levels, identifying high-performing and underperforming outlets and cities.
• Conducted outlet-level and city-level performance analysis using metrics such as average order value, daily transactions, dine-in versus delivery mix, and revenue per square foot.
• Studied temporal patterns in ordering behaviour, including day-of-week trends, end-of-month demand spikes, and order timing throughout the day.
• Performed store format comparisons across premium stores, kiosks, experience stores, shop-in-shop formats, and cloud kitchens.
• Analysed product and SKU trends across multiple months to understand shifts in customer preferences, including seasonal effects on beverage and food categories.
• Evaluated a live pricing experiment by calculating price elasticity and demand response for selected products, leading to clear recommendations on whether to continue or discontinue the experiment at specific outlets.
• Conducted a broader food and beverage industry comparison to benchmark Third Wave Coffee against major domestic and international competitors on scale, revenue, and performance indicators.

I worked extensively with Excel, using formulas, lookups, and structured calculations to extract insights from large, multi-sheet datasets. Over the course of the internship, I learned to optimise my workflows, transition from manual methods to formula-driven analysis, and ask for timely support when technical constraints arose.

The experience strengthened my ability to approach ambiguous datasets, identify the right questions to ask, and communicate insights clearly through charts, tables, and concise written summaries.

This internship was my first exposure to real-world business data at scale. It helped me develop analytical discipline, comfort with imperfect data, and an appreciation for how structured analysis supports everyday operational and strategic decisions in growing businesses.