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Does an experienced hotelier really need analytics?

14 March 2024
To succeed in the hospitality industry, it is not sufficient to simply fill up rooms. To stay ahead of the competition, it is important to thoroughly understand all aspects of the business and its market. This post emphasizes the significance of utilizing insights from three analytical categories — destination, guest, and operational — to transform the guest experience and enhance operational efficiency, substantially improving financial performance.
I love analytics and have used it since I started in the industry almost forty years ago. However, when I read industry publications and blogs, I sometimes get the impression that people think analytics is new. Therefore, I had to ask ChatGPT what analytics is in the hospitality industry and if it is essential. I was not surprised by the answer, but let's start with a definition.

What is analytics in hospitality?

Analytics in the hospitality industry refers to the systematic computational analysis of data or statistics related to various aspects of hospitality operations, including hotels, restaurants, travel, and tourism. It involves collecting, processing, and analyzing data to gain insights that can inform decision-making, improve customer service, optimize operations, and enhance the overall guest experience.

Is it essential?

ChatGPT says the importance of analytics in the hospitality industry cannot be overstated, as it provides several critical benefits:
  1. Improved Customer Experience: Analytics can help understand customer preferences, behaviors, and trends by analyzing data from various sources like booking patterns, reviews, and feedback. This information can tailor services, personalize offers, and anticipate needs, leading to a more satisfying customer experience.
  2. Operational Efficiency: By analyzing operational data, hospitality businesses can identify areas for improvement in their services, processes, and logistics. This can lead to more efficient resource use, cost savings, and improved service delivery.
  3. Revenue Management: Analytics plays a crucial role in revenue management by helping businesses optimize pricing strategies based on demand forecasting, market trends, and customer behavior. This can maximize occupancy rates and increase revenue.
  4. Market Trends and Competitor Analysis: By analyzing market trends and competitor performance, businesses can identify opportunities for growth, innovation, and differentiation. This helps in strategic planning and maintaining a competitive edge.
  5. Risk Management: Analytics can help identify potential risks and vulnerabilities within operations, from financial to reputational risks. This enables businesses to develop strategies to mitigate these risks before they escalate.
  6. Enhanced Marketing Strategies: Data analytics allows for creating more targeted and effective marketing campaigns. By understanding customer segments and preferences, businesses can tailor their marketing efforts to attract and retain guests more effectively.
In summary, analytics is a cornerstone of the modern hospitality industry, enabling businesses to make informed decisions, improve efficiency, enhance customer satisfaction, and drive growth. The ability to swiftly adapt to changing market conditions and customer preferences based on insights derived from data analytics can be a significant competitive advantage in this dynamic industry.

My comments

ChatGPT sounds very convincing, but ChatGPT has no idea what hospitality is about in real life. I had to ask a follow-up question: "What could an experienced hotelier discover by using analytics that he or she does not already know?"
I got a list of 31 different discoveries. Here are a few that are worth commenting on.
ChatGPT: Hidden Customer Segments: Analytics can reveal unexpected or niche customer segments by identifying patterns in booking behavior, preferences, and feedback. Understanding these segments allows for more targeted marketing and customized service offerings.
Again, it sounds convincing, but let's analyze the likeliness of hidden segments and the impact an unknown segment could have on revenue and profits. If the segment is hidden from an experienced hotelier, it is small and has little effect on revenue and profitability. Understanding these segments would probably lead to not doing anything and instead focus on the important, growing, and profitable segments.
ChatGPT: Guest Experience Personalization: Analytics can identify individual guest preferences and behaviors, enabling hoteliers to offer highly personalized experiences, from room amenities to tailored activities. This can significantly enhance guest satisfaction and loyalty.
It sounds fantastic, in theory. The first requirement is that the hotel ask the guests about their preferences. That rarely happens. The second requirement is to store and use the information to attract and service the guests. This is also highly unlikely since hotels do not maintain high data quality. I have stayed at 500 hotels and never had a personalized experience. The main reason is that the hotel has no clue who I am, and they never ask me anything or bother to look up my LinkedIn profile (which is very easy). To deliver a personalized experience, the hotel has to start caring about the guests before even thinking about analytics.
ChatGPT: Optimal Staff Allocation: By analyzing data on guest flow, peak check-in/out times, and service requests, hoteliers can optimize staff schedules and allocations to ensure high-quality service without overstaffing or understaffing.
Staff allocations are in a hotelier's genes. Guest flows rarely change because human behavior rarely changes. Have you seen the traffic lights some hotels use to inform guests about when to eat breakfast? Hoteliers do not need analytics to understand that guests eat breakfast later on weekends. Staffing is also about being able to sell more to each guest, which ChatGPT seems to miss. When guests want to buy drinks in the bar, make sure there are bartenders there to sell them drinks. Maybe analytics could help even an experienced hotelier to refine staffing allocation.

Three analytics categories

I believe in analytics. What makes sense for hotels? Let's leave ChatGPT and instead categorize analytics in hotels. Here are three main categories: 1) Destination analytics, 2) Guest analytics, and 3) Operational analytics.

1. Destination Analytics

The first category focuses on understanding the market to capture at least a fair share by creating a well-thought-out strategy. Destination analytics focuses on analyzing data related to the location or destination where the hospitality service is provided. This includes studying market trends, tourist flows, competitor analysis within the destination, events, local attractions, and seasonal patterns. The goal is to understand the broader context in which the hospitality business operates, identify potential opportunities for attracting tourists, and anticipate fluctuations in demand based on external factors. Insights from destination analytics can help in strategic marketing, creating partnerships with local businesses, and tailoring services to meet the expectations of visitors drawn to the destination for specific reasons.

2. Guest Analytics

The second category focuses on understanding what the guests want and what they are prepared to pay for. The challenge is to match the right guests with what the hotel can offer. Guest and customer analytics concentrate on collecting and analyzing data related to the guests and customers. This involves deep dives into customer behavior, preferences, spending patterns, feedback, and loyalty. Businesses can gain insights into what drives guest satisfaction, loyalty, and repeat business by leveraging data from various touchpoints, such as bookings, social media interactions, reviews, and on-site interactions. Guest analytics could be the foundation for personalizing guest experiences, improving service delivery, designing effective loyalty programs, and creating targeted marketing campaigns. Still, it requires that the guest is willing to share relevant information. Hotels need to talk to guests and not just rely on data. The ultimate aim is to enhance guest satisfaction and loyalty by selling more products and services, leading to increased revenue and profitability.

3. Operational Analytics

The third category focuses on maximizing the flow-through or profit based on the revenue generated by the hotel's strategy based on the opportunities at the destination and what the guests buy. This is where many hoteliers thrive and already know everything. Cost control has too much of an unbalanced focus, so analytics would help inform the hotelier to balance effort and time with potential profit increases. Operational analytics involves analyzing the hospitality business's internal processes, performance data, and logistical aspects. This includes data on staffing, inventory management, energy consumption, maintenance, and service delivery times. Hoteliers focus on each line in the profit & loss statement but often miss the potential to improve processes to increase productivity. The focus should be on improving efficiency and optimizing the use of resources while maintaining or improving service quality. Insights gained from operational analytics can lead to more informed decision-making regarding process improvements, resource allocation, and investment in technologies or innovations that streamline operations and enhance the guest experience.
Each of these analytics categories is " forward-looking." If the hotel understands the market and the guests better, it can grow revenue in the future. If the hotel understands the guest better, it can streamline the delivery of the experience and increase profit in the future. These categories play a crucial role in the hospitality industry's strategic and operational decision-making process, offering different lenses to view the business and identify opportunities for growth, improvement, and competitive differentiation.

Final thoughts

Hoteliers should start using ChatGPT to get ideas on improving their businesses. The list of 31 discoveries that ChatGPT put together for me is precious as a starting point for further thoughts and actions.
However, ChatGPT is often too general and misses the point, so it is more useful if you can pair the information with solid hands-on experience from the industry.
I purposely omitted financial analytics since these are lagging KPIs analyzing historical data that you cannot change or do anything about. However, you can still learn from historical data and discover patterns that can lead to decisions that will improve profits in the future.
Focusing on destination, guest, and operational analytics will make a massive difference in a hotel's success.