In the fast-paced world of luxury hotels, AtliQ Grands faced revenue challenges that threatened its market share. As an aspiring Data Analyst, I embarked on a journey to transform the fortunes of this prestigious 5-star hotel chain in India.
Here's a quick glimpse of some noteworthy facts about AtliQ Grands:
➡️AtliQ Grands proudly stands as a five-star hotel chain with a presence in four bustling cities.
➡️Across these urban hubs, AtliQ Grands boasts a network of seven distinct properties, strategically situated to cater to diverse clientele.
➡️Within these upscale properties, guests are offered a choice of four room categories: Elite, Premium, Presidential, and Standard, ensuring a tailored experience for every visitor.
➡️To enhance guest convenience, AtliQ Grands offers reservations through six prominent booking platforms, optimizing accessibility and ease of booking.
Project Scope: My mission was clear - to harness the power of data and provide insights that would pave the way for smarter decision-making at AtliQ Grands. To achieve this, we leveraged several datasets:
dim_date - This table contains date-related information, such as dates, week numbers, and day types (weekend and weekday). We utilized this data to analyze booking trends over time.
dim_hotels - This table provided crucial details about the properties, including property ID, property name, category, and cities. It was essential for understanding the hotel chain's properties and their characteristics.
dim_rooms - This table included information about room IDs and room classes. We used this data to analyze which types of rooms were more popular or profitable.
fact_aggregated_bookings - This fact table contained data related to property ID, check-in dates, room categories, successful bookings, and capacity. It served as a crucial source for calculating key metrics related to bookings and occupancy.
Key Revelations:
▶Total Revenue: A staggering 1.71 billion rupees! 💰
▶Highest Revenue City: Mumbai, contributing 40% of the total revenue.
▶Top-rated City: Delhi, boasting an impressive average rating of 3.8.
▶Luxury vs. Business: Luxury category reigns supreme, generating a whopping 1053 million rupees.
▶Star Performer: AtliQ Exotica property emerged as the hero, raking in a remarkable 320 million rupees in revenue.
▶Room Class Leader: Elite rooms were the preferred choice among guests, showcasing their popularity, which we identified using data from the dim_rooms table.
▶Platform Power: Makeyourtrip emerged as the revenue powerhouse among the booking platforms.
▶Hotel Performance: AtliQ Exotica led the pack with 320 million rupees in revenue, while AtliQ Seasons, identified from the dim_hotels table, held its ground at 66 million rupees.
▶RevPAR Showdown: AtliQ Exotica took the lead with an impressive 7.8k RevPAR, while AtliQ Grands followed closely at 6.5k.
▶ADR (Average Daily Rate): AtliQ Seasons triumphed with an ADR of 16.6k, whereas AtliQ Blu, also from the dim_hotels table, stood strong at 11.9k.
These insights are not just numbers; they are the roadmap to revitalizing AtliQ Grands' revenue strategy. With Mumbai as a revenue stronghold and Delhi as a top-rated city, targeted marketing efforts can be focused here. The popularity of Elite rooms suggests a need for tailored promotions, while Makeyourtrip's dominance points to a lucrative partnership opportunity.
AtliQ Exotica's stellar performance highlights the potential for replication across other properties, leveraging data from the fact_aggregated_bookings table. Moreover, optimizing ADR at AtliQ Blu can further boost revenue.
In conclusion, data intelligence has unlocked a world of possibilities for AtliQ Grands. By leveraging these insights, the hotel chain can regain its competitive edge and secure its position as a leader in the luxury/business hotels category.
This is not just a project; it's a success story in the making, driven by data and innovation.
