Revamping AtliQ Grands' Revenue Strategy: A Data-Driven Success Story(PowerBI Project)
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In the dynamic realm of high-end hospitality, AtliQ Grands, a renowned luxury hotel chain, encountered revenue challenges that were impacting its competitive standing. As an ambitious Data Analyst, I took on the task of leveraging data analytics to reshape the fortunes of this esteemed 5-star hotel chain in India.
Let’s delve into some key highlights about AtliQ Grands:
➡️ A celebrated five-star hotel chain, AtliQ Grands has a significant presence in four major Indian cities.
➡️ In these metropolitan areas, AtliQ Grands operates seven unique establishments, each strategically located to serve a diverse range of guests.
➡️ The hotel chain offers four categories of rooms – Elite, Premium, Presidential, and Standard – catering to varied guest preferences and ensuring a customized stay.
➡️ AtliQ Grands ensures easy booking through six well-known reservation platforms, enhancing the convenience for its guests.
Project Overview: My objective was crystal clear – to use data-driven insights to guide smarter strategic decisions at AtliQ Grands. This involved analyzing several key datasets:
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dim_date: This dataset provided date-specific details like calendar dates, week numbers, and day types (weekdays and weekends), crucial for studying booking patterns over time.
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dim_hotels: This dataset gave us important information about each property, such as their IDs, names, categories, and locations, vital for understanding the dynamics of each hotel in the chain.
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dim_rooms: This dataset offered insights into room types, helping us analyze the popularity and profitability of different room categories.
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fact_aggregated_bookings: This core dataset included information on bookings, property IDs, check-in dates, room types, and capacities, instrumental for calculating key metrics like booking rates and occupancy.
Key Findings:
▶ Total Earnings: An impressive 1.71 billion rupees in revenue. 💰
▶ Revenue Leader by City: Mumbai, accounting for 40% of the overall revenue.
▶ City with Highest Ratings: Delhi, with an average rating of 3.8.
▶ Luxury vs. Business Segment: The Luxury category led the way, generating 1053 million rupees.
▶ Standout Property: AtliQ Exotica, earning a notable 320 million rupees in revenue.
▶ Most Popular Room Type: Elite rooms, as identified through the dim_rooms dataset.
▶ Leading Booking Platform: Makeyourtrip, a major contributor to revenue.
▶ Top-Performing Hotels: AtliQ Exotica led with 320 million rupees, followed by AtliQ Seasons at 66 million rupees, as identified in the dim_hotels dataset.
▶ RevPAR Analysis: AtliQ Exotica topped with 7.8k RevPAR, followed by AtliQ Grands at 6.5k.
▶ ADR Insights: AtliQ Seasons led with an ADR of 16.6k, with AtliQ Blu at 11.9k.
These insights are not mere figures; they represent a strategic blueprint for rejuvenating AtliQ Grands’ revenue approach. With Mumbai as a revenue bastion and Delhi as a highly-rated city, focused marketing strategies are advisable. The preference for Elite rooms suggests potential for specialized promotional campaigns, while Makeyourtrip’s dominance indicates a promising partnership opportunity.
The exceptional performance of AtliQ Exotica sets a benchmark for other properties, with strategies inferred from the fact_aggregated_bookings dataset. Additionally, optimizing the ADR at AtliQ Blu could further escalate revenue.
In summary, data analytics has opened a plethora of opportunities for AtliQ Grands. By capitalizing on these insights, the hotel chain is well-poised to reclaim its market dominance and continue leading in the luxury and business hotel sector.
This project is more than just an assignment; it's a burgeoning success story, fueled by data-driven innovation and strategic foresight.
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