01
Data Preparation
I imported the Excel dataset into Power BI and used Power Query to prepare the data for analysis: checking the relevant field types and organising the fields for reporting.
← Data Analytics
Data Analytics / Business IntelligenceIndependent Portfolio Project
Power BIPower QueryExcelData AnalyticsBusiness IntelligenceData Visualisation
Hotel Booking Performance & Customer Insights
An interactive Power BI analysis of hotel bookings, 2010–2019
An interactive business intelligence analysis exploring hotel booking trends, customer demographics, geographic demand, payment preferences, and hotel performance between 2010 and 2019. Developed in Power BI to transform booking data into actionable business insights.
Original Power BI Dashboard
The original dashboard
Original dashboard designed and developed in Microsoft Power BI.
Click the dashboard to enlarge it.
Download Original Power BI Report ↗
Opens the original .pbix report on Google Drive in a new tab.
What the dashboard contains
Four KPI cards: total bookings, booking value (SGD), average stay, average hotel rating
Two interactive slicers: Origin Country and Destination Country
Six visualisations covering trends, origin markets, ratings versus price, hotel value, age groups, and payment methods
- Project type
- Independent Data Analytics Portfolio Project
- Dataset
- Practice hotel booking dataset
- Reporting period
- 2010–2019
- Primary platform
- Microsoft Power BI
Project Overview
What this project examines
This project examines hotel booking activity between 2010 and 2019 to identify trends in customer demand, booking behaviour, geographic markets, payment preferences, and hotel performance.
Using Microsoft Power BI, I developed an analytical dashboard that combines key performance indicators, interactive filters, and comparative visualisations to communicate meaningful business findings.
The analysis goes beyond presenting figures. It identifies opportunities for customer segmentation, targeted marketing, payment optimisation, and hotel performance evaluation.
Business Questions
Questions the analysis set out to answer
These questions guided the dashboard design and the analysis behind it.
- 01
How did hotel booking activity change between 2010 and 2019?
- 02
Which origin countries generated the most bookings?
- 03
Which customer age groups contributed most to booking demand?
- 04
How did booking values differ across hotels?
- 05
What relationship exists between hotel ratings and average booking prices?
- 06
How were bookings distributed across payment methods?
- 07
What business actions could be recommended from the observed patterns?
Tools & Analytical Approach
How the analysis was built
02
KPI Development
The dashboard tracks four headline measures: total bookings, total booking value in SGD, average length of stay, and average hotel rating.
03
Data Visualisation
I combined line charts, horizontal bar charts, a scatter plot, a donut chart, KPI cards, and country slicers so the different questions could be explored from one view.
04
Business Interpretation
I read the visualisations to identify booking trends, high-activity customer groups, geographic differences, payment preferences, and hotel performance patterns.
Interactive Dashboard
Explore the data yourself
This is a working recreation of the original Power BI dashboard, built from the same underlying booking records. Change either country filter and every KPI card and chart recalculates from the filtered data.
Loading the interactive dashboard…
Executive Summary
The headline findings
- Booking Growth
- Hotel bookings increased significantly between 2010 and 2019, with a particularly strong rise of 60.91% between 2014 and 2019. Annual bookings grew from 5,905 to 9,502 during this five-year period.
- Hotel Performance
- Grand Hyatt recorded the highest total booking value at SGD 47,084, outperforming the lowest-ranked hotel, Simply Charmed B&B (SGD 14,571), by 223.13%.
- Geographic Demand
- Booking activity varied across the seven origin countries, with volumes ranging from 5,952 to 12,170 bookings, indicating differences in customer demand across markets.
- Hotel Ratings and Pricing
- Silver Sun Bed And Breakfast recorded the highest average hotel rating (4.37), while Bourbon Bliss had the highest average booking price (SGD 245.61).
These figures reflect the original unfiltered Power BI analysis.
Key Insights
What the data shows
Insight 01
Sustained Booking Growth
Annual hotel bookings increased by 98.08% between 2010 and 2019, nearly doubling over the reporting period.
Bookings rose from 5,905 in 2014 to 9,502 in 2019, indicating particularly strong growth in the latter years.
Insight 02
Concentration in Key Origin Markets
Thailand recorded approximately 12.2K bookings, while Malaysia, Singapore, and Indonesia each contributed around 12K.
These four countries represent the strongest customer-origin markets, indicating where booking activity is concentrated.
Insight 03
Core Customer Age Groups Drive Demand
Customers aged 25–34 (16.9K), 35–44 (16.5K), and 45–54 (16.4K) accounted for approximately three-quarters of all bookings.
This indicates that customers aged 25–54 represent the primary booking demographic.
Insight 04
Diverse Payment Preferences
Payment methods were distributed relatively evenly: Internet Banking 20.21%, Debit Card 20.08%, Wallet 20.01%, Credit Card 19.94%, and Cash on Delivery 19.76%.
No single payment method dominated customer transactions.
Insight 05
Hotel Performance Varies Across Measures
Grand Hyatt recorded the highest total booking value at SGD 47,084; Silver Sun Bed And Breakfast had the highest average hotel rating at 4.37; Bourbon Bliss recorded the highest average booking price at SGD 245.61.
These findings demonstrate why hotel performance should be evaluated using multiple measures rather than a single indicator.
Strategic Recommendations
What a business could do next
Recommendation 01
Sustain Booking Growth
Investigate factors associated with the increase in bookings between 2014 and 2019, including customer demand, destination popularity, and hotel availability. Use the findings to inform growth planning and establish measurable booking targets.
Recommendation 02
Prioritise High-Activity Markets
Develop targeted marketing campaigns for Thailand, Malaysia, Singapore, and Indonesia, where booking volumes are highest. Investigate opportunities to increase demand in lower-volume markets, including Cambodia and Vietnam.
Recommendation 03
Strengthen Customer Segmentation
Focus customer acquisition and retention initiatives on the highly active 25–54 age segment. Test tailored promotions, loyalty offers, and destination recommendations while exploring opportunities to attract younger and older customers.
Recommendation 04
Maintain Flexible Payment Options
Continue supporting all five payment methods because customers use them at similar rates. Monitor transaction costs, failed payments, and payment completion rates before prioritising any individual method.
Recommendation 05
Evaluate Hotels Using Multiple Performance Metrics
Assess hotel partners using booking volume, booking value, average booking price, and customer ratings. Investigate successful properties and identify opportunities to improve lower-performing hotels.
These are proposed business recommendations derived from the analysis, not actions that were implemented in a real business.
What This Project Demonstrates
Skills demonstrated
- Analytical Thinking
- Framing business questions and examining patterns across multiple dimensions of hotel booking data.
- Data Visualisation
- Selecting appropriate chart types and building a cohesive dashboard with clear KPIs.
- Customer Insights
- Analysing demographic groups, geographic markets, and payment preferences.
- Business Intelligence
- Transforming raw booking records into performance indicators and comparative analysis.
- Data Storytelling
- Translating dashboard findings into clear insights and practical recommendations.
- Dashboard Design
- Organising information to support quick interpretation and interactive exploration.