All businesses accumulate vast amounts of raw data and managing this information properly is essential to stay competitive. Data entry and document conversion services play a key role in converting paper documents into various digital format, which streamlines management and allows information to be shared and analyzed. By analyzing data, businesses can identify trends and patterns and get valuable insights for strategic decision making. Today, data analytics is proving critical for revenue management.

What is Revenue Management?

Revenue management involves the use of data analytics to predict consumer behavior and make decisions the pricing of individual products and services. When conceived and implemented correctly, revenue management optimizes financial performance. The concept of revenue management is especially applicable in industries such as hospitality and airlines which have a perishable inventory. Based on consumer demand trends, prices can be adjusted to increase earnings and sales by selling the right product to the right customer at the right time for the right price using the right tools through the right channels ( In the hotel industry, revenue management aims to provide the right room to the right person at the right time and place, which will maximize revenue and profit.

Role of Data Analytics in Revenue Management and New Challenges

Effective revenue management depends on integrating data from various systems and sources and analyzing the information to implement the right strategies to optimize resource use and revenue. A LinkedIn article lists the key areas where data analytics impacts revenue management in the hotel industry as:

  • Pricing Decisions: Data analytics helps revenue managers make pricing decisions. By studying past trends and comparing competitor pricing patterns, they can determine the ideal prices for rooms in each category.
  • Channel Management: Analyzing data is important to identify which channel is performing well, seasonality of bookings, the region from where more bookings are coming, the sale prices of various room categories on different channels, and more. This information can be utilized to maximize revenue from each channel.
  • Booking Patterns: Analyzing data on demand for different room types based on region, season, and market segment, managers can forecast occupancy and design appropriate pricing strategies.
  • Data Filtering: Analyzing and processing relevant data will help in the generation of accurate and timely reports for informed decision making.

However, today, revenue management tactics have gone beyond pricing and inventory management. The conventional method of analyzing historical demand patterns such as booking lead times, booking patterns by segments, and occupancy trends by season, day, week or month to determine the best possible room rate at a given point of time has become obsolete. Analyzing performance and estimating demand and demand patterns have become unpredictable as they are dependent on multiple external factors.

The hospitality and airline industries are particularly vulnerable to disruptions such as economic crises, wars and epidemics. Though these sectors usually recover fast from such disasters, the COVID-19 pandemic has badly affected their resilience and ability to bounce back. Revenue managers have to rethink their data and analytics strategy to optimize operations and profits.

New Elements in Data Analysis for Revenue Management

For hotels to survive and stay competitive in the COVID world, experts recommend that data analytics for revenue management should include the following:

  • Real-time Market Demand Indicators: According to a hospitality net article, it is essential to have a complete understanding of the competitor landscape for competitive pricing. Hotel prices for every room type and individual options available for each room type should be analyzed 365 days in advance. Knowing these real-time market demand indicators is important to ensure optimal pricing for every potential new booking.
  • Inbound Search Volume by Source Market: Examining real-time trends in flight and booking search volume can provide an idea of how demand for a destination grows over time, notes Atomize. Predicting which dates will see increased demand over time before reservations begin can help hotels adjust rates in advance and get bookings at optima rates.
  • Macro Perspective of Demand: Various factors impact demand pressure for a destination: travel agent hotel booking searches, how often hotel prices change, hotel cluster search analytics, and flight search data trends. Understanding these factors is important to understand market demand and ensure appropriate pricing.
  • Online Reputation Ranking: Before they book a hotel room, most customers will compare the online reputation scores of hotels available across various online booking platforms. People typically rank their stay experience based on factors such ambience, cleanliness, comfort, location, facilities, staff, value for money, etc. While a hotel will not have a direct control over its reputation score, its service delivery standard will impact these factors. Revenue management strategies need to incorporate reputation data analytics to understand what’s important to potential guests.
  • Data on Flight Search and Potential Travel Patterns: In the COVID-19 scenario, analyzing flight search data is especially important for hotel revenue management. Hotel bookings and stays are closely linked to flight travel patterns. Understanding flight search data is crucial to identify travel intent and hotel booking prospects.

Effective data analytics depends on having clean data in the required format. Data entry outsourcing can ensure that even complex data is organized properly so that different visualizations and analysis can be performed effortlessly. Outsourcing companies also provide document conversion services to convert unstructured content into data that is ready for analysis. Relying on these solutions can make the data analytics task easier for revenue managers in these challenging times.