ITEP Research: The fullness and prices determine the performance of Greek hotels

Hotel businesses in Greece continue to focus strongly on traditional performance and revenue-related performance, while the adoption of artificial intelligence (AI) is still at an early stage.

This demonstrates a new study by the Institute of Tourism Research and Forecasts (ITEP) in all Greek hotel units, entitled "The Use of Artificial Intelligence in the Functioning of Greek Hotels".

Hotel businesses show that they continue to focus on measurements directly related to demand and pricing policy. The most widespread indicator of performance monitoring in Greek hotels is the percentage of completeness of rooms, which is monitored by 71% of hotels, followed by the average daily price (ADR) with 59%.

Following, with clearly lower rates, indicators such as average residence duration (41.4%), direct booking rate (38.5%), and revenue per available room or REVPAR (36.8%).

Interestingly is a relative lag in indicators such as customer satisfaction (32.4%), total operating gross profit (TGOP) (32%), and working costs (29.1%), showing that quality and profitability are not yet at the center of their strategy.

Particularly alarming is the very low monitoring of viability and functional efficiency indicators: Revpam only 1.7%, 9.4%renewable energy rate, customer acquisition costs 7.6%and 12.3%staffing index.

Research has also shown that although using modern tools, a significant proportion of hotels continues to apply non-automated methods. Almost half of the hotels (48.2%) manage their reservations via channel manager, while a significant rate (45.1%) continue to do so manually online. Less common are reservations via hotel software/CRS (14.4%) or agencies (17.4%).

Artificial Intelligence: Positive Perception, limited application

Artificial intelligence, although recognized as important, remains on the sidelines of the daily functions of hotels. Only 22.7% of hoteliers say they use it, while 52% have not incorporated it at all.

Nevertheless, more than half of the professionals in the field see AI positively (50%) and consider themselves to be directly concerned (56.4%).

The most common AI applications are ChatGPT (19.5%), chatbots (8.5%), analysis and response to online customer reviews (10.7%), and predictive analysis (10.2%). Other possibilities, such as facial identification or automatic menu creation, have very low use rates (below 5%).

High interest in AI in bookings and marketing

The majority of hoteliers believe that AI could help more (60.2%), finances (53.8%), and marketing (53.6%). The following are data analysis (45%), customer relationship management (36.7%), and cybersecurity (33.4%).

The main benefits recognized are time savings (42.3%), improvement in functional efficiency (32.1%), sales increase (25.5%), and improved communication/ marketing (24.2%). However, the cost reduction (23.1%) seems to be lower in business perception.

The obstacles to the adoption of AI mainly relate to a lack of information (38.9%) and security and privacy concerns (27.7%). The following are the lack of support from the administration (26.4%), strict regulations (25.9%), installation costs (23.2%), and technical complexity (20%).

93.8% of the hotels involved in the survey operated independently without a chain, and 39.6% are on a seaside destination, followed by hotels in the countryside (22.3%).

90.6%, and therefore the majority of their customers, visit it for vacations and leisure, with 7.1% residing for business and only 0.7% visiting them for conferences, exhibitions, or other events (MICE).