A CEO's Guide: Maximizing Hotel Profits Through Data-Driven Decisions
19 September 2023
While "digitalization" continues to echo throughout the hospitality industry, many hoteliers want to be more digitally focused in their marketing efforts. However, what often goes unnoticed or is underestimated is the granular detail involved in effective hotel data management. It's not merely about collecting data but how it is processed, analyzed, and turned into actionable insights that can fuel revenue growth at a lower cost, ultimately boosting profits.
This blog post aims to demystify the various aspects of data management specific to the hotel industry. We will explore the data types needed to meet critical objectives, ranging from segment targeting and personalization to guest/customer acquisition and staff empowerment. By the end of this read, you'll understand how effective data management can be the backbone of successful, data-driven marketing strategies in the hospitality sector.
The Importance of Data-Driven Marketing
In an age where information is plentiful yet attention spans are limited, the hospitality industry faces an exciting challenge: How can we continuously engage our customers in meaningful ways? Enter data-driven marketing—a powerful tool that allows us to enhance the customer experience, streamline operations, and maximize profitability.
In the hospitality sector, one of the primary applications of this marketing approach is customer segmentation and personalization. Imagine predicting what amenities guests would like before arriving or adjusting pricing based on real-time demand. These aren't just pipe dreams but outcomes that data-driven marketing can achieve.
Objectives of This Blog
Although most leaders in the hospitality industry recognize the potential of data-driven marketing, there is often a lack of clarity on the specifics - what kinds of data are necessary and how to use them efficiently. This blog aims to bridge that gap by examining the essential data types required to accomplish critical objectives in data-driven marketing.
Why This Perspective Matters: The View from the Top
As a Hotel CEO, you may wonder why I am so concerned about the nitty-gritty details of data collection and analysis. The truth is that strategy without execution is just a daydream, and execution without strategy is a nightmare. Understanding how data affects marketing initiatives from a granular level allows for efficient resource allocation and effective team leadership. I am sharing this blog post from a Hotel CEO's perspective - to provide you with a comprehensive view that bridges strategy with execution.
Collecting relevant data from various sources is crucial to develop a successful data-driven marketing strategy. This includes customer interactions, website analytics, social media engagements, and the hotel PMS, which tracks all transactions between the guests and the hotel. You should expect to gather data points such as customer demographics, browsing behavior, purchase history, and specific preferences. Understanding the critical data types needed to target individual market segments, personalize the customer experience, acquire new customers, and more is essential. So, let's dig deeper into the data needed to gain insights to help you achieve your marketing objectives.
Targeting Individual Market Segments
Customizing our services according to the diverse needs of our guests is the cornerstone of hospitality. This allows us to improve the guest experience and optimize revenue streams across various services and amenities.
Types of Data Needed, Obstacles, and Data Quality Assessment
Specific types of data are necessary to cater to each market segment. Below, we'd like to list the types of data needed and how to collect this data. Data for market segmentation is invaluable; however, the quality of this data varies depending on the collection method and the inherent obstacles.
Reason for Traveling to the Destination
Understanding why guests choose to visit can offer invaluable insights into their needs. Is it a business trip, a family vacation, or perhaps they're attending a special event?
How to Collect: Through booking forms, post-booking surveys, and queries during the check-in process.
Obstacles: Guests may choose to keep their reason for travel private or may inaccurately represent their reason for travel.
Data Quality Assessment: Moderate. Since much of this data is self-reported and optional, it may not always be accurate or complete.
Use Case: Customizing stay packages based on the reason for travel.
Future Demand Generators at the Destination
Awareness of future events, congresses, and festivals can help pre-emptive planning. This information helps design packages or offers that align with these events, luring guests to choose your hotel.
How to Collect: Maintaining relationships with local event organizers and tourism boards and using predictive analytics.
Obstacles: Unpredictable events or inaccuracies in third-party data can be challenging.
Data Quality Assessment: Moderate to High. While local partnerships can offer reliable data, unpredictable events can introduce uncertainty.
Use Case: Anticipating high-demand events, setting aside room blocks, or creating tailored packages.
Customer Demographic Data
Information about where our guests are coming from, their age, and their willingness to spend can significantly influence our marketing tactics. For example, younger travelers might be more interested in budget packages, while older people may prioritize comfort and luxury.
How to Collect: Via booking forms, social media analytics, and potential use of third-party data providers.
Obstacles: Privacy concerns can lead to reluctance to share personal information.
Data Quality Assessment: Moderate. Privacy laws and individual willingness to share information can significantly affect the quality and completeness of this data.
Use Case: Offering amenities and services tailored to demographic segments such as age, nationality, or spending power.
Customer Behavior Data
This includes booking behavior (Did they book directly through our website or a third-party site?) and the length of stay. Such data can offer insights into how flexible a guest might be and what kinds of services they are likely to avail themselves of.
How to Collect: Website analytics tools and Property Management Systems (PMS) for in-hotel behavior.
Obstacles: Cookie consents, ad blockers, and incomplete capture of in-hotel activities can limit data collection.
Data Quality Assessment: Low to Moderate. Due to the optional nature of cookies and limitations in tracking in-hotel activities, this data is often incomplete.
Use Case: Developing personalized promotions and loyalty program incentives.
Customer Feedback and Reviews
Nothing speaks more clearly about our service quality than direct feedback from customers. Reviews can provide qualitative insights into what specific market segments appreciate or lack, indicating areas for improvement or capitalization.
How to Collect: Post-stay surveys sent via email, social media reviews, and direct feedback during the stay can be valuable sources. These should be systematically collected and analyzed for actionable insights.
Obstacles: Low survey response rates and potential for bias in public reviews.
Data Quality Assessment: Moderate. While the data is valuable, it often captures extreme experiences and may not be fully representative.
Use Case: Identifying service strengths and weaknesses to inform future operational and marketing strategies.
Better data increases opportunities
Understanding the potential quality of the data we collect allows us to take preemptive action to improve it. For instance, knowing that customer behavior data is usually of low-to-moderate quality, efforts can be made to incentivize guests to share more information.
By knowing what data we need, how to collect it, the obstacles we might face, and the likely quality of the data, we are better equipped to fine-tune our strategies. This in-depth understanding is crucial for providing a personalized, satisfying guest experience and maintaining a profitable hotel operation.
Personalizing the Customer Experience
One of the most important aspects of modern hospitality is personalizing the customer experience. By tailoring each guest's journey, we can significantly increase their satisfaction, encouraging long-term loyalty and ultimately boosting our bottom line. With data about guest preferences, it is easier to improve their experience.
Types of Data Needed, Obstacles, and Data Quality Assessment
Customer Preferences (Room Type, Amenities)
How to Collect: During the booking process, offer options to customize room type and amenities. Post-stay surveys can also be used to collect this data for future visits.
Obstacles: Guests may not always know what they want ahead of time or may not take the time to specify their preferences.
Data Quality Assessment: Moderate to High. Guests have a direct incentive to provide accurate information here, but the completeness of the data may vary.
Use Case: Offering a preferred room type or specific amenities during future stays.
Previous Interactions (Customer Service Chats, Emails)
How to Collect: Archive all guest interactions through customer service platforms and email correspondence.
Obstacles: Not all interactions are digitized, and the data might be scattered across different platforms.
Data Quality Assessment: Moderate. While the data is often accurate, it may be fragmented and thus require effort to integrate for a complete view.
Use Case: Recalling previous interactions and preferences provides a more seamless and personalized service.
Real-Time Data (Current Location, Local Events)
How to Collect: Utilize mobile apps and partnerships with local event organizers to collect real-time location data and information on local events.
Obstacles: Privacy concerns and app permissions may prevent collecting accurate location data.
Data Quality Assessment: Low to Moderate. Real-time data can be highly volatile and is subject to many variables, including technical issues and privacy regulations.
Use Case: Sending personalized push notifications about special offers in the hotel or nearby attractions based on real-time location.
Collect high-quality data about the guest
Despite the varying levels of data quality, collecting and applying these data types can significantly enhance guest experience and drive loyalty. Combining even moderate-quality data innovatively can offer a rich tapestry of personalized touches that make all the difference to a guest’s stay.
Data quality challenges do not diminish the incredible potential for personalizing the customer experience. When thoughtfully applied, imperfect data can create memorable experiences that keep guests returning.
Attracting New Guests/Customers
When individuals travel to a new destination, only a few may have visited before, but most normally visit for the first time. This emphasizes the continuous need for hotels to attract new guests. To create effective marketing campaigns, it is vital to comprehend why individuals choose a particular destination and what they require in terms of overnight accommodation. With this knowledge, marketers can create targeted campaigns that cater to these requirements and give their hotels a competitive edge in attracting new clientele.
Types of Data Needed, Obstacles, and Data Quality Assessment
Lead Data (Email, Social Media Engagements)
How to Collect: Newsletter sign-ups, social media interactions, and gated content can effectively collect lead data.
Obstacles: Privacy regulations like GDPR can impact the amount of data that can be collected, and users might provide fake or secondary email addresses.
Data Quality Assessment: Moderate. Due to privacy concerns and the potential for inaccurate information, the quality can be variable.
Use Case: Sending targeted email campaigns with special offers to attract potential guests.
Web Analytics (Visitor Behavior, Conversion Rates)
How to Collect: Utilizing tools like Google Analytics to track visitor behavior, dwell time, and hotel website conversion rates.
Obstacles: Ad blockers, cookie policies, and VPN usage can affect the accuracy of this data.
Data Quality Assessment: Moderate to High. It is generally reliable but can be affected by external factors like ad blockers.
Use Case: Identifying which website elements convert visitors to customers most effectively informs web design choices and campaign strategies.
Market Research Data (Consumer Trends, Competitors’ Performance)
How to Collect: Through industry reports, customer surveys, and tools that analyze competitors' online performance.
Obstacles: Quality and timeliness of third-party reports and the generalizability of consumer survey results can be limiting factors.
Data Quality Assessment: Moderate. While these data sources are usually reliable, they are also often general and not specific to your hotel's unique circumstances.
Use Case: Tailoring marketing strategies based on what is working in the industry and for competitors.
Differentiate your hotel from the competition
In the case of a destination that attracts travelers continuously, it's not a challenge for hotels to acquire new guests. The real challenge is to differentiate themselves from their competitors. The key to success is to offer unique amenities, experiences, or value that will attract potential guests to one hotel instead of another in the same destination. Hotels can obtain valuable insights into customer preferences and market trends by utilizing a robust, data-driven strategy. This, in turn, enables them to create more compelling and targeted marketing campaigns to capture the interest of those traveling to the destination, giving them a competitive advantage.
The customer acquisition process shows that even imperfect data can be precious for making informed decisions. A multi-faceted strategy that leverages web analytics, lead data, and market research puts hotels in a more advantageous position for attracting new guests.
How to overcome data quality challenges
Hotels can still reap the benefits of data-driven digital marketing, even if the data quality is not up to the mark. Though high-quality data is always preferred for accurate targeting and personalization, moderate or low-quality data can still provide valuable insights that are superior to making decisions based on intuition alone. Here are some reasons and ways hotels can use data, regardless of quality.
Why Hotels Can Benefit Despite Data Quality Challenges
- Volume Over Precision: Hotels often collect a large amount of data. While individual data points may be flawed, patterns often emerge when looking at the data in aggregate.
- Real-time Adjustments: The hospitality industry, being service-oriented, can quickly adjust its strategies. Even if initial data leads to a less-than-perfect decision, rapid corrections can be made.
- Contextual Understanding: Hotels have the advantage of context when interpreting data. Even imperfect data can be valuable when viewed in the context of a hotel's specific market, trends, and customer base.
- Benchmarking: Even if the data isn't perfect, it can still be used for internal benchmarking. Tracking how metrics change over time can provide actionable insights.
Strategies to Make the Most of Lower-Quality Data
- Data Cleansing: Regularly updating and cleaning the database can improve the data quality over time.
- Supplement with Qualitative Insights: Staff interactions with guests can provide qualitative insights that supplement quantitative data. For instance, customer service teams often have a nuanced understanding of common complaints or praises that may not be captured entirely through formal data.
- A/B Testing: Digital marketing allows for real-time testing. Even if your data is imperfect, running A/B tests on different target groups can provide actionable insights.
- Customer Segmentation: While the data may not be robust enough for highly personalized targeting, it might still be helpful for broader customer segmentation. For example, you might not know each customer's preferred room temperature, but you might know which guests are business travelers and vacationers, allowing you to market to these segments differently.
- Leverage Partnerships: Partnering with third-party platforms can sometimes provide access to better-quality data. For instance, if your booking engine or customer relationship management (CRM) system has advanced analytics, it could provide additional insights.
- Data Quality Improvement: Consider incentivizing guests to provide more information. This can be done through loyalty programs, exclusive offers, or even simple follow-up surveys post-stay.
Do not let low data quality stop you
While data quality challenges shouldn't be underestimated, they shouldn't deter hotels from adopting a data-driven marketing strategy. The key is to be aware of your data's limitations and approach analysis and decision-making with these limitations in mind. It's far better to make a well-informed decision based on some data, even if imperfect than to operate in the dark.
Improving Data Quality
The importance of accurate data cannot be overstated in the hospitality industry. Making informed business decisions and creating effective marketing strategies requires reliable data. Hotels must ensure data accuracy and reliability to succeed in the industry.
Action List to Improve Data Quality in Hotels
Improving data quality is not just a one-time task; it's an ongoing process that requires a dedicated strategy. Below is a tailored action list aimed at aiding hotels in enhancing their data quality for more effective decision-making and marketing.
Existing Customer Data
- Review and Standardize Data Entry Practices: Establish standard operating procedures for data entry across all departments to ensure consistency.
- Regularly Update PMS, CRM, and Loyalty Program Records: Allocate resources to keep customer records up-to-date.
- Data Cleansing: Utilize data cleaning tools to identify and remove duplicate or outdated records.
- Validation Checks: Incorporate validation checks within the hotel PMS to prevent errors during data entry.
- Obstacles: Inconsistent data entry, outdated information, duplications
- Data Quality Assessment: Moderate
- Use Case: Keeping PMS and CRM records current for accurate marketing campaign targeting.
Data Quality Metrics (Accuracy, Completeness, Timeliness)
- Implement Quality Metrics in the hotel PMS: Utilize metrics such as accuracy, completeness, and timeliness to evaluate data quality.
- Regular Audits: Schedule and perform data audits at consistent intervals to identify quality issues.
- Quality Scorecards: Create scorecards that rate the data on various quality parameters for easy tracking.
- Obstacles: Lack of standardized metrics, abstract qualities hard to measure
- Data Quality Assessment: High
- Use Case: Regular data audits for quality assurance
High-quality data boosts ROI
Improving data quality is a fundamental step for hotels that aim to stand out in a fiercely competitive market. High-quality data empowers better decision-making and boosts the ROI of targeted marketing campaigns. The road to optimal data quality is ongoing. Still, with continuous audits, validation, and up-to-date record maintenance, hotels can achieve a level of data quality that enables them to excel in today's data-driven world.
Don't compromise on data quality. Evaluate your current data management practices and take proactive steps to elevate your data's reliability and accuracy.
Integrating Data Across Platforms
Creating a unified view of customer interactions is crucial for hotels looking to optimize their services and marketing strategies. The first choice is centralizing the Property Management System (PMS) as the hub for all guest data, providing a more cohesive view of guest behavior and spending. It enables the hotel to consolidate all guest-related financial transactions into a single folio, making it easier for the hotel and the guest to track expenditures. Below is an elaboration of how this can be set up:
Types of Data Needed, Obstacles, and Data Quality Assessment
PMS (Property Management System) Data as the Central Hub
How to Collect: All other departmental systems—such as the POS for food & beverage, the spa system, and the golf system—should be configured to feed their transaction data into the central PMS. This allows for an aggregated view of a guest's expenditures and interactions.
Obstacles: The critical challenge is achieving seamless integration between the departmental systems and the PMS. Data formatting inconsistencies and transfer delays can compromise the quality and timeliness of the data.
Data Quality Assessment: High if integrated correctly. Since the PMS is the master record, data quality can be very high if regular audits and validation checks are in place.
Use Case: Generating comprehensive guest folios that include all expenditures, leading to more personalized post-stay engagement, like tailored offers based on overall spending and preferences.
Other Operational Systems (POS for Food & Beverage, Spa System, Golf System, etc.)
How to Collect: All other operational systems should be configured to feed transactional and guest interaction data directly into the PMS. This integrated approach ensures a comprehensive view of each guest's activities and spending is available in a centralized location.
Obstacles: The primary barriers include achieving seamless integration between the various operational systems and the PMS and ensuring data is synced in real-time. There may also be challenges related to consistent data formatting and accurate attribution of transactions to the correct guest folio.
Data Quality Assessment: Moderate to High. The data quality largely depends on the seamless integration between the systems and regular data audits. The data quality can be very high if these factors are managed well.
Use Case: A unified guest folio that captures all expenditures across various hotel services and amenities. This comprehensive view enables more personalized engagement and marketing efforts, from bundled packages based on historical spending to targeted promotions that consider the guest's full range of activities during their stay.
Maximize the use of the hotel PMS
Centralizing all guest data into the Property Management System (PMS) offers hotels a coherent and comprehensive method for tracking guest behavior and spending. While integrating multiple operational systems poses challenges, the benefits, such as improved customer service and targeted marketing opportunities, can be significant.
Social Media Analytics
Storing social media analytics in a Property Management System (PMS) is a controversial decision, depending on the goals and capabilities of the hotel's data strategy. Here are some points to consider:
- Holistic View of the Customer: Having social media data in the same system as reservations, spending, and other interactions could provide a 360-degree view of the customer, which is valuable for personalization and service improvement.
- Unified Data Analysis: A centralized data store can make it easier to perform comprehensive analytics, integrating insights from social interactions with other types of customer data.
- Streamlined Operations: A single system for all customer data could simplify operations and reduce the number of different systems staff must be trained on.
- Data Complexity: Social media data can be quite different in structure and scope compared to the transactional data typically stored in a PMS, which could complicate data management and integration efforts.
- Privacy Concerns: Storing social media data could raise privacy issues that may require additional layers of data protection, compliance checks, and, potentially, consent from the guests.
- System Limitations: Not all PMSs are built to handle the scale and complexity of social media data, and adding this capability could require a significant investment in system upgrades or customization.
- Data Relevance: Social media data can be very noisy and could include a lot of irrelevant information. Hotels need robust data analytics capabilities to filter out the noise and derive meaningful insights.
- Separate but Integrated Systems: Instead of storing social media data directly in the PMS, hotels could consider using a specialized Customer Relationship Management (CRM) system that integrates well with the PMS. This approach can offer the best of both worlds: specialized handling of different data types and the ability to integrate data for unified analytics and customer insights.
- Data Warehousing: Another option is to use a data warehouse to consolidate data from multiple sources, including PMS and social media analytics. Advanced analytics and business intelligence tools can derive insights from this centralized data pool.
While adding social media analytics to a PMS has advantages but presents some challenges and risks. Hotels must carefully weigh these factors against their specific needs, capabilities, and compliance requirements.
Raising Level of Data Analytical Skills
Empowering hotel staff with the ability to make data-driven decisions is vital for staying competitive in the industry. Staff who understand how to interpret data can identify guest preferences, operational efficiencies, or revenue opportunities more quickly and accurately.
Providing Intuitive, Insightful, and Interactive Systems
- Systems like Demand Calendar
- How to Implement: Introduce Demand Calendar as a centralized platform where staff can access key performance indicators, forecasts, and other analytics tailored to the hotel industry.
- Obstacles: Staff members may face a learning curve when adapting to new technology. There may also be integration challenges with existing systems.
- Data Quality Assessment: High. Demand Calendar is designed to provide accurate and reliable analytics.
- Use Case: Offering interactive dashboards and real-time analytics to enable quick decision-making based on current trends and forecasts.
Importance of Data Quality
- Built-in Data Quality Functions in Demand Calendar
- How to Implement: Utilize the built-in features of Demand Calendar for data validation and quality checks, ensuring that the team works with complete and accurate data.
- Obstacles: Convincing team members to maintain high data quality can sometimes take time and effort. It requires ongoing education and reinforcement.
- Data Quality Assessment: High. Demand Calendar's built-in functions are designed to ensure high data quality.
- Use Case: The system can alert staff when there is incomplete or inconsistent data, guiding them through correcting it for better analytics and decision-making.
By incorporating user-friendly systems like Demand Calendar and emphasizing the importance of data quality, hotels can significantly improve their staff's analytical skills. This leads to better decision-making, more efficient operations, and increased revenue and guest satisfaction.
Conclusion: Managing data correctly will drive profitabilty
The ever-evolving landscape of the hotel industry makes it essential to adapt and innovate continually, and one of the most effective ways to do this is through data-driven marketing. As we've discussed, data plays a crucial role in hotel management and marketing—from targeting individual market segments and personalizing the guest experience to acquiring new customers and improving operational efficiencies. The quality of this data directly impacts the accuracy and reliability of the decisions made, making it indispensable for achieving key objectives.
But more than data collection is needed; it must be high-quality, integrated across various platforms, and analyzed effectively. Intuitive and interactive systems like Demand Calendar can significantly help raise data analytical skills among staff members, ensuring accurate, reliable data for every decision.
Therefore, the call to action is clear: It's time for hotel industry professionals to assess and significantly improve their data management practices. Whether starting from scratch or fine-tuning your existing strategies, the effort you invest in managing your data today will pay off in more effective marketing, better guest experiences, and, ultimately, increased profitability for your hotel.