Kaufverhalten von Hotelgästen

The hotel industry has always been an integral part of the travel and tourism sector and has significantly contributed to the global economy. However, the buying behavior of hotel customers has undergone a drastic change in recent years due to technological advancements and changing consumer preferences. This blog post explores the factors that influence the buying behavior of hotel customers. The post covers various factors such as price, location, facilities, online reviews, brand reputation, loyalty programs, and online booking. The psychology behind a hotel customer's buying behavior is complex and can be influenced by a variety of factors such as perception, emotion, social influence, perceived value, cognitive dissonance, and habit. The post also explores the impact of big data and technologies such as virtual concierge services or automated guest communication with WhatsApp for hotels on the hotel industry and how it can aid hotels in positively impacting hotel customer's buying behavior.

Main factors that influence a hotel guest's buying behaviour:

• Price: Price is one of the most critical factors that influence the buying behavior of hotel customers. Customers are always looking for the best deal and value for their money. The price of a hotel room will depend on various factors, such as the location, facilities, and room type.
• Location: The location of the hotel plays a significant role in the buying behavior of hotel customers. Customers are willing to pay more for a hotel room that is located in a prime location, such as a city center or near a tourist attraction.
• Facilities: The facilities offered by a hotel also impact the buying behavior of customers. Customers are more likely to book a hotel that offers excellent facilities, such as a swimming pool, spa, gym, and restaurant.
• Reviews: Online reviews play a vital role in the buying behavior of hotel customers. Customers tend to read online reviews before booking a hotel room. Positive reviews can influence the decision of a customer to book a room, while negative reviews can deter them from booking.
• Brand Reputation: The reputation of the hotel brand is another crucial factor that influences the buying behavior of hotel customers. Customers are more likely to book a hotel that has a good reputation in the market.
• Loyalty Programs: Loyalty programs offered by hotel chains also influence the buying behavior of customers. Customers are more likely to book a room with a hotel chain that offers loyalty programs, such as free upgrades, discounts, and other perks.
• Online Booking: The rise of online booking platforms has revolutionized the way customers book hotel rooms. Customers can now compare prices, facilities, and reviews of different hotels and book a room from the comfort of their homes.

The buying behavior of hotel customers has changed significantly in recent years. Customers are more informed and have higher expectations from the hotels they choose to stay in. Hotels must adapt to these changing trends by offering competitive prices, excellent facilities, and great customer service. By doing so, hotels can attract and retain customers and build a loyal customer base.

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The Psychological Factors Influencing Hotel Customer Buying Behavior

The psychology behind a hotel customer's buying behavior is complex and can be influenced by a variety of factors, both conscious and unconscious. Understanding these factors is crucial for hotels to attract and retain customers. Perception plays a vital role in a hotel customer's buying behavior. Customers tend to form an opinion about a hotel based on their perception of its brand, reputation, and online reviews. This perception can be influenced by advertising, word-of-mouth recommendations, and personal experiences.

Emotion is another critical factor that influences a hotel customer's buying behavior. Customers tend to make decisions based on their emotions and how they feel about a particular hotel. Positive emotions, such as joy and excitement, can lead to a customer booking a hotel room, while negative emotions, such as fear and anxiety, can deter them from doing so. Social influence can also play a significant role in a hotel customer's buying behavior. Customers are influenced by the opinions of others, such as friends, family, and online reviews. Social proof, such as high ratings on review sites, can encourage customers to book a hotel room.

Perceived value is the customer's assessment of the benefits they will receive in exchange for the price they pay. Customers tend to look for the best value for their money when choosing a hotel. This perceived value can be influenced by the hotel's location, facilities, and reputation. Cognitive dissonance occurs when a customer experiences a feeling of discomfort or unease after making a decision. This can happen when a customer has to choose between two hotels that are both attractive. To alleviate this discomfort, customers tend to look for additional information, such as online reviews, to confirm their decision.

Habit is another factor that influences a hotel customer's buying behavior. Customers tend to develop habits, such as staying at the same hotel chain or booking through the same online platform. This habit can be influenced by loyalty programs, convenience, and past experiences. A hotel customer's buying behavior is influenced by various psychological factors. Hotels need to understand these factors and use them to their advantage to attract and retain customers. By offering excellent customer service, creating a positive brand image, and providing value for money, hotels can appeal to the psychological needs of their customers and build a loyal customer base.

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Ways Big Data, Datamining and Predictive Analytics can Improve Hotel Customer's Buying Behavior

Big data can be a powerful tool for hotels to positively impact hotel customer's buying behavior. By leveraging data from existing systems like point of sale (POS), property management system (PMS), and loyalty systems, as well as new sources like acoustic and visual smart sensors, hotels can gain valuable insights into customer behavior and preferences. Here are some ways big data can aid in a hotel's ability to positively impact hotel customer's buying behavior:

• Personalization: Big data can help hotels personalize the customer experience. By analyzing data from loyalty systems and POS, hotels can understand customers' preferences and tailor their experience accordingly. For example, a hotel can use data to recommend room types, amenities, and services based on the customer's previous purchases and preferences.
• Pricing: Big data can also help hotels optimize pricing strategies. By analyzing data from PMS and POS, hotels can understand customer demand patterns and adjust prices accordingly. This can help hotels offer competitive prices and attract more customers.
• Operational Efficiency: Big data can help hotels improve operational efficiency. By analyzing data from smart sensors, hotels can monitor and optimize energy consumption, occupancy rates, and staff utilization. This can help hotels reduce costs and improve the overall customer experience.
• Marketing: Big data can also help hotels improve their marketing efforts. By analyzing data from loyalty systems and POS, hotels can understand customer behavior and preferences and develop targeted marketing campaigns. This can help hotels attract new customers and retain existing ones.
• Predictive Analytics: Big data can help hotels make better predictions about customer behavior. By analyzing historical data from PMS, POS, and loyalty systems, hotels can predict future customer demand patterns and adjust their offerings accordingly. This can help hotels offer the right products and services at the right time, improving customer satisfaction and loyalty.

Data mining and predictive analytics are essential tools for hotels to gain an edge versus the competition, providing insights into customer behavior and preferences. Hotels can easily identify and predict patterns and trends that can aid in decision-making and positively impact hotel customer's buying behavior. Here are some ways data mining and predictive analytics can aid a hotel in the above:

• Customer Segmentation: Data mining can help hotels identify customer segments based on various factors, such as demographics, booking behavior, and spending habits. By segmenting customers, hotels can develop targeted marketing campaigns and tailor their offerings to specific customer needs and preferences.
• Personalization: Predictive analytics can help hotels personalize the customer experience. By analyzing data from loyalty systems and POS, hotels can identify customer preferences and make personalized recommendations for room types, amenities, and services.
• Demand Forecasting: Predictive analytics can also help hotels forecast customer demand patterns. By analyzing historical data from PMS and POS, hotels can predict future customer demand and adjust their offerings accordingly. This can help hotels optimize pricing strategies, improve operational efficiency, and enhance the overall customer experience.
• Reputation Management: Data mining can also help hotels manage their reputation. By analyzing data from online review sites and social media, hotels can identify customer complaints and respond appropriately. This can help hotels address issues and improve their reputation.

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How a Virtual Concierge Can Enhance Guest Communication and Experience

A virtual concierge can transform guest communication and elevate the overall hotel experience by automating interactions and providing personalized services through platforms like WhatsApp. Here's how:

• Efficient Guest Communication: A virtual concierge can handle up to 80% of standard guest inquiries, ensuring quick and accurate responses to questions about check-in/out times, amenities, and local attractions. This reduces the workload on staff and ensures guests receive prompt assistance.
• Personalized Services: By leveraging data from the hotel's PMS and other systems, a virtual concierge can offer personalized recommendations and services to guests. For instance, it can suggest dining options, spa treatments, or activities based on the guest's preferences and previous stays.
• Upselling Opportunities: The virtual concierge can identify opportunities to upsell additional services, such as room upgrades, special packages, or exclusive experiences, thereby increasing ancillary revenue for the hotel.
• 24/7 Availability: Guests can access the virtual concierge at any time, ensuring they receive assistance even during late hours or peak times when staff may be busy. This constant availability enhances the guest experience and satisfaction.
• Convenience of WhatsApp: Utilizing WhatsApp for guest communication ensures high engagement, as it is a platform guests are already familiar with and frequently use. This leads to higher response rates and more effective communication.

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Underutilization of Data and Analytics in Hotels: Reasons and Examples

Despite the potential benefits of data and analytics in improving hotel customer's buying behavior, hotels are still underutilizing them in several ways. Here are some examples:

• Lack of Integration: Many hotels still use multiple systems that do not integrate with each other, making it difficult to analyze data effectively. For example, a hotel may have separate systems for POS, PMS, and loyalty programs, which may not communicate with each other seamlessly. This can result in data silos, which make it difficult to gain a comprehensive view of customer behavior.
• Limited Use of New Data Sources: While hotels have access to new data sources, such as smart sensors, they are not fully utilizing them. For example, hotels can use acoustic and visual smart sensors to collect data on customer behavior, such as how long customers stay in the room and what amenities they use. However, many hotels are not leveraging this data to make better decisions.
• Limited Focus on Unstructured Data: Hotels are also underutilizing unstructured data, such as social media and online reviews. Many hotels focus only on structured data, such as data from POS and PMS, and ignore unstructured data, which can provide valuable insights into customer behavior and preferences.
• Lack of Data-Driven Culture: Finally, many hotels do not have a data-driven culture, which limits their ability to effectively use data and analytics. For example, many hotel staff may not be trained in data analysis or may not have access to the necessary tools and resources to effectively analyze data.

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Concluding

In conclusion, the buying behavior of hotel customers is complex and influenced by various factors. These include price, location, facilities, online reviews, brand reputation, loyalty programs, and the rise of online booking platforms. Hotels need to adapt to changing trends by offering competitive prices, excellent facilities, and great customer service to attract and retain customers. The psychology behind a hotel customer's buying behavior is also influenced by perception, emotion, social influence, perceived value, cognitive dissonance, and habit. Hotels need to understand these factors and use them to their advantage to build a loyal customer base. Big data can also be a powerful tool for hotels to positively impact hotel customer's buying behavior by enabling personalization, pricing optimization, improving operational efficiency, and enhancing marketing efforts.

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