How can yield management leverage big data and analytics to gain insights and competitive advantage?

1 Benefits of big data and analytics

Big data and analytics are essential tools for yield management, as they enable you to collect, process, and interpret large and complex data sets from various sources, such as customer behavior, booking patterns, market trends, competitors' actions, and external factors. By using big data and analytics, you can gain deeper and more accurate insights into your demand and supply curves, your customer segments and preferences, your pricing elasticity and sensitivity, and your revenue opportunities and risks. These insights can help you to improve your forecasting accuracy, optimize your pricing and inventory strategies, enhance your customer loyalty and satisfaction, and increase your market share and profitability.

3 Best practices of big data and analytics

To leverage big data and analytics for yield management successfully, you need to follow some best practices that can help you to overcome the challenges and maximize the benefits. These include defining your goals and metrics, selecting the most appropriate data sources and tools, using advanced techniques and methods to analyze and interpret your data, and implementing and monitoring your decisions. You must also make sure to align your goals and metrics with your business strategy and objectives, evaluate the quality, reliability, and compatibility of your data sources and tools, present your data in a clear way that can support decision-making, use automation, optimization, and personalization tools to implement decisions, monitor decisions and outcomes using feedback loops, testing, and evaluation methods, and adjust them as needed.

4 Examples of big data and analytics in yield management

To illustrate the use of big data and analytics in yield management, here are some examples from different industries. For instance, in the hospitality industry, hotels can use big data and analytics to segment their customers based on their booking behavior, preferences, loyalty, and feedback. They can also use it to forecast their demand and occupancy, and adjust their rates and availability to maximize their revenue per available room (RevPAR). Airlines can use big data and analytics to optimize their network planning, fleet management, route selection, and seat allocation. Additionally, they can tailor their fares, fees, and bundles to different customer groups based on their willingness to pay. Car rental companies can use big data and analytics to optimize their fleet size, mix, and distribution. Additionally, they can dynamically price their vehicles based on the demand and supply of different models, categories, and features.

5 Future trends of big data and analytics in yield management

Big data and analytics are constantly evolving, offering new opportunities and challenges for yield management. In the future, real-time data and analytics can enable faster response to changing market conditions, while prescriptive analytics can help to predict and prescribe actions for desired outcomes. Augmented analytics can enhance data analysis and interpretation, while edge computing can reduce latency, bandwidth, and cost. All of these trends can help to capture revenue opportunities, avoid risks, improve security, and increase reliability.