(untitled) (International Journal of Latest Technology in Engineering Management & Applied Science, 2026)
The hospitality sector increasingly relies on operational data to guide pricing, yet many operators still raise or lower prices uniformly across all units. This paper analyses hotel bookings in terms of occupancy and sales across seasons and events, and develops a proposed unit-level smart-pricing and selective-marketing mechanism. The study follows a descriptive–analytical approach using actual operational data for 95 residential hotel units operated by a hospitality company in Riyadh and Al-Madinah, Saudi Arabia, covering January to June 2026 (181 days, 9,028 occupied nights, SAR 4.22 million in confirmed sales), organised through an interactive web dashboard that is publicly accessible online. Independent-samples (Welch) t-tests were used to test the significance of the observed differences. The results show clear monthly variation, a dominant Airbnb channel, and — most importantly — that the occupancy–sales relationship is not directly proportional but is mediated by the average daily rate (ADR): some units combine low occupancy with high sales, while others show the opposite. The effect of Ramadan differs sharply by city, with occupancy and rate rising in Al-Madinah but falling in Riyadh; weekends significantly outperform weekdays; and the cancellation rate reaches 10.3%. The study concludes with a set of quantified, calibratable pricing rules that link each pricing decision to the event, season, city, day type, channel, and the actual performance of the individual unit.