DIGITAL MARKETING ANALYSIS

 Title: Hotel Booking Predictive Analysis

INTRODUCTION

Hospitality Haven's humble beginnings with a single hotel in Accra, Ghana have blossom into a global hotel chain across continent. Hospitality Haven pride itself on an unwavering commitment in luxury,  impeccable service and guest satisfaction. Their properties includes luxury hotels, boutique gems, stunning resort. They are strategically located business hotels, each designed to provide unique and exceptional experience.

Business Challenge

The prevailing challenge: Hospitality Haven faces the challenge of efficiently managing the hotel bookings, pricing and occupancy rates. The challenge is further exacerbated by the competitive nature of the travel and tourism, industry which is influenced seasonality, market demand fluctuations, and evolving customer preference. The specific obstacles the company encounter includes:

• Seasonal variation.
• Pricing Dilemma.
• Customer Behavior Understanding.
• Demand Forecasting.
• Competitive Intelligence.

Rationale For The Project

• Enhance Customer Experience.
• Revenue Optimization
• Operational efficiency 
• Competitive Advantage 
• Data-Driven-Decision-Making

Aim Of Project

1. Comprehensive Data Insights
2. Customer Behavior Analysis
3. Booking Pattern Identification
4. Pricing Strategy Assessment
5. Competitor Benchmarking

Data Description

• Customer_ID: A unique identify for each customer
• Customer Name: The name of the customer 
• Gender: The gender of the customer
• Age: the age of the customer
• Nationality: The nationality of the customer 
• Booking_ID: A unique identifier for booking
• Booking_Date: The date which the booking was made
• Duration_Of_Stay: The number nights the customer stayed
• Room_Type: The the type of room booked by customer
• Room_Rate: The rate charged for the room per night
• Additional_room_cost: Additional cost associated with the room
• Loyalty _status: Indicates whether the customer has loyalty status 
• Booking_Channel: The channel through which the booking was made
• Economic_Index: An index possibly indicating economy factors related to booking
• Traveling_Purpose: The purpose of the customer travel
• Group_size: The size of the group that booking
• Competior_ID: A identifier for a competitor 
• Competitor_room_rate: Room rate offered by competitor 
• Competitor_occupancy_rate: occupancy rate of the competitor
• Competitor_promotion: Promotions offered by the competitor
• Competitor_Name: The name of the competitor 
• Competitor_Rating: The rate given to the competitor 
• Competitor_Pricing_Strategy: Pricing strategy of the competitor 
• Channel_Type: Types of booking channel used
• Local_Events: local events happening that may affect booking
• Cancellation: Indicates whether booking was cancelled.

                                                        

An overview of the Hotel data

INSIGHTS AND RECOMMENDATION

Seasonal Variation And Revenue Optimization:

• The Total Monthly Revenue indicates a peak revenue in April of GHC 1.07M, Which then drop to a lower revenue in July of GHC 837,537. This could point to a need for adjusting room rates or offering special packages during off-peak time to maintain occupancy and revenue. The "Total Revenue by Channel" Indicates a strong performance from Online Travel Agents, which contribute GHC 2.95M.

This underscores the strong importance of online presence and could justify further investment in digital marketing and online booking platforms. Offer seasonal promotion and packages to attract guest during off-peak months, potentially bundling with local events or attractions to increase appeal.

Customer Behavior Understanding:

• The data shows the most preferred Room Types is Double with revenue of GHC 2,903,191, which is crucial for targeting marketing efforts and room allocation strategies. Additionally the total Booking by Age and Gender highlight a trend where more males more rooms than female and the age range 45-55 years have the highest bookings, indicating a demographic segment that might be responsive to targeted promotions.

This underscores the strong importance of online presence and could justify further investment in digital marketing and online booking platforms. Offer seasonal promotion and packages to attract guest during off-peak months, potentially bundling with local events or attractions to increase appeal.

Demand Forecasting:

• Room booking counts are fairly even, with double booking leading at 508. This even spread of demand across room types can help the hotel in forecasting needs for investing and staffing, ensuring that they neither overbooked nor underutilized. Room bookings peaked in March with 186 total bookings and there was a decline in April, which peaked in may and huge drop in July till December.

Use the even distribution of room type to refine inventory management, ensuing that there is an optional number of each room type available throughout the year. analyze bookings pattern by room type and group size to improve staffing and resources allocation, thereby reducing cost and improving guest experience.

Competitive Intelligence:

• The "Total Bookings by Competitive Pricing Strategy" section shows a competitive edge "Premium" category for Bahamas luxury with 198 bookings, suggesting that there is a market for Premium services that the hotel could capitalize on by enhancing it own premium offerings.
• Operational Efficiency:
• with a "Total Cancellation Rate" of 18.65, the data suggests there is significant room for improvement reducing cancellation, which could involve reviewing booking conditions, cancellation policies, or enhancing pre-stay communication to encourage guest to follow through with their bookings.
• pricing Strategy Dilemma:
• The gender-base revenue analysis shows a significant difference in revenue contribution with females at GHC 2,462,578 males at GHC 8,681,004.

Investigate services and amenities offered by competitors in the "Premium" category to identify potential area for improvement or differentiation. Monitor competitor pricing strategies continuously to ensure hotel's pricing remains competitive while also delivering to value guest.

RECOMMENDATIONS

Data Driven Decision Making:

Increase investment in online booking platforms and digital marketing strategies to capitalize on the high revenue generated from Online Travel Agents. leverage customer data analysis to make informed decisions about marketing, pricing and service offerings.

Pricing Strategy Dilemma:

Considering the gender disparity in revenue contribution, develop targeted pricing strategy such women-centric packages loyalty programs to increase to increase female guest bookings. Analyze the booking and spending patterns of male guest to further tailor services and offers that resonate with the segments.