Revenue Intelligence & Occupancy Analytics Dashboard
SkylineStay is a unified Revenue & Occupancy Intelligence Dashboard built to automate reporting for short-stay apartments. It centralizes bookings, payouts, fees, and occupancy insights that previously required heavy manual effort, enabling faster pricing decisions and more accurate performance tracking.
reduction in manual reporting time
faster pricing & revenue decisions
drop in booking inconsistencies
improvement in multi-property visibility
Quick Project Snapshot
Greece
Hospitality
Data Intelligence for Multi-Property Portfolio
Agile
Client Overview
The client manages a portfolio of 15–20 short-stay apartments, combining properties they own with units managed for investors. Bookings flow through Airbnb, Booking.com, and Webhotelier, while Hosthub is used as a channel manager. The client needed a fully automated reporting system because manual spreadsheets were slow, error-prone, and prevented accurate revenue tracking.
Real-time booking data ingestion
Cleanses & structures 70+ financial and operational fields
Daily auto-refresh ensures consistent accuracy
Total revenue, net profit, platform split, guest fees, commissions
Multi-month view: Today → Next 3 months
KPI cards + line charts + comparative visuals
Monthly occupancy %, stay duration metrics, platform distribution
Insights for seasonal trends and low-occupancy gaps
Drill-through to individual property performance
Filter by location, date range, platform, and property
Tooltip breakdown: fees, earnings, nights stayed
Side-by-side property comparison
Custom formulas for Airbnb, Booking.com, and Webhotelier
Tracks fees, commissions, payouts, taxes, and manager charges
Monthly net profit (before & after tax)
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Project Goals
Provide one dashboard that combines revenue, occupancy, payouts, and fees into a unified view.
Deliver daily refreshed insights so owners can adjust pricing at the right time.
Remove dependency on spreadsheets and reduce human error.
Provide accurate revenue and profit metrics for financial planning.
Challenges & Solutions
The client relied heavily on manual extraction from Hosthub and Webhotelier, resulting in inaccuracies and delays. Multiple data files had to be compared manually, creating risk of outdated occupancy and incorrect revenue insights.
We built a fully automated Hosthub API integration with daily refresh cycles. A structured data model was created using 76 essential fields, eliminating manual work and ensuring real-time accuracy.
Direct API connections caused slow refresh times, API rate-limit issues, and made it difficult to retain historical booking data. As the number of properties grew, the dashboard risked becoming unstable and unable to handle large monthly data loads.
We implemented a dedicated ETL → AWS Database → Power BI pipeline that stores structured Hosthub data in a high-performance cloud database. This approach ensures fast refreshes, complete historical retention, and smooth scalability as property volume and booking frequency increase.
Each platform (Airbnb, Booking.com, direct bookings) had its own fee structure, currency behavior, and payout logic. Manually converting these into net profit was time-consuming and error-prone.
We created a dynamic profit engine using DAX formulas based on the client’s exact financial logic, guest paid subtotal, fees, commissions, taxes, and manager charges, with separate profit views for before-tax and after-tax performance.
Tech Stack Used
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