What is a Big Data in The Travel Industry and How Can It Benefit Your Business
The utilization of big data analytics has the potential to significantly enhance operational capabilities, provide a competitive edge, and uncover new business prospects for organizations. In the travel industry, big data analytics has emerged as a vital tool for businesses. Travelers and businesses generate a vast amount of data during their search for suitable travel products, including destinations, flights, and hotels. Furthermore, their travel experiences create extensive datasets. These datasets, combined with data from other sources, are utilized for predictive analysis, trend identification, and issue resolution.
This article aims to elucidate what is big data in the travel industry and how big data analytics can be advantageous for the hospitality industry.
Three Categories of Big Data Analytics in Tourism
1. Descriptive Analytics
Descriptive analytics involves the analysis of real-time and historical customer data. Its objective assessment enables businesses to anticipate future occurrences effectively. In the context of tourism, descriptive analytics can be utilized to reduce costs by offering last-minute discounted hotels and enhancing forecasting accuracies, such as predicting 80% of full-price sales or 50% of early booking sales.
2. Predictive Analytics
Predictive analytics is employed by travel companies to forecast long-term trends based on previous patterns and trends. For example, it helps identify the types of trips (study, business, romance, health and wellness, etc.) and geographical destinations that will likely be popular in the upcoming season.
3. Prescriptive Analytics
Prescriptive analytics represents an advanced version of predictive analytics that employs simulation scenarios. In addition to generating forecasts, prescriptive analytics assists travel companies in identifying the most promising business strategies to maximize profits and reach customers.
Analyzing Big Data in the Travel Industry
The collection of data from open sources and third-party platforms is a challenging task in itself. However, analyzing and extrapolating this data for practical use is an even more complex endeavor. This is where analytics comes into play. Analytics platforms gather data from various sources, organize and segment it, and derive meaningful insights.
Given the sheer volume of big data, manual processing, and analysis are infeasible. Modern technologies employed by analytics platforms enable the extraction of valuable and actionable insights for businesses. Predictive analysis is also employed to identify emerging trends in specific industries.
Key Advantages of Big Data in Travel
Let's now examine the benefits that travel companies can derive from big data.
1. Revenue Management
Big data enables effective revenue management by optimizing costs and accurately predicting revenues in both the short and long term. It facilitates precise calculations of occupancy rates, minimizing the risk of unexpected costs and providing predictability in terms of profit levels.
2. Enhanced Analytics
Big data in tourism encompasses the utilization of historical and real-time data, unlike traditional analytical approaches that rely solely on historical data. This makes big data solutions more effective in predicting drastic shifts in trends, as exemplified by the impact of the COVID-19 pandemic.
3. Seasonal Management
The ability to swiftly process vast amounts of information from the target audience enhances the effectiveness of seasonal marketing and enables optimized long-term forecasting. Consequently, businesses can make informed decisions when selecting new geographical destinations and tour formats, rather than relying on random choices.
The Application of Big Data in the Travel Industry to Drive Profitability
How is big data being utilized in the travel industry? Let's explore some examples of its application in this business niche.
1. Revenue Optimization
By leveraging big data, businesses can obtain accurate information regarding potential profits based on the satisfaction and expectations of existing and future customers. This facilitates simplified pricing procedures, precise forecasting of peak periods of maximum demand, and the provision of relevant services aligned with current market trends. Utilizing big data profit optimization tools like Pruvo allows hotel resellers to take advantage of post-booking price fluctuations in hotels you already sold and maximize their profitability.
2. Reputation Improvement
In an era where individuals readily express their opinions on social networks, businesses need to pay careful attention to reviews and actively manage their reputations. Special reputation management services analyze the overall sentiment and tone of voice in these reviews to enhance reputation management practices.
3. Strategic Marketing
Big data, with its vast collection of dates and associated numerical information, enables the accurate prediction and modeling of future business strategies. Creating such models often requires additional tools based on artificial intelligence.
4. Personalization of Customer Experience
Big data assists in comprehending customer preferences and needs, facilitating a more personalized approach. With the aid of forecasting tools, businesses can predict customers' future requirements influenced by emerging tourism trends.
5. Marketing Research
Big data allows businesses to gather information about competitors and target audiences in real-time, based on last year's or even older reports. This technology offers unparalleled precision for research purposes.
6. Targeted Marketing
Due to the diverse range of customers in the travel industry, developing a single target marketing strategy can be challenging. However, big data can analyze an extensive number of representatives from the target audience, segment them into distinct groups, and facilitate a targeted approach for each segment.
Challenges of Big Data in the Tourism Industry
To provide a balanced review, it is essential to consider the challenges that big data solutions may encounter in the travel industry.
1. Privacy and Security
The generation of big data surpasses the capacity to collect, process, store, and analyze it effectively. Traditional IT security systems often lack the necessary flexibility and scalability to adequately protect this information. Thus, advanced solutions are required to ensure the security of analytics data.
2. Data Ownership
Given that big data in the tourism industry originates directly from users and companies, compliance with GDPR and HIPAA policies is crucial.
3. Data Handling
Processing real-time big data necessitates special technologies, typically involving machine learning and artificial intelligence, to avoid excessive resource consumption.
4. Data Storage
Businesses commonly utilize public or private cloud environments to store big data in the tourism industry. However, storing such data can be expensive due to the requirement for high-performance equipment.
By addressing these challenges, the tourism industry can harness the power of big data effectively.
To summarize, big data analytics in the tourism industry goes beyond being a mere trend; it is a valuable tool for understanding the market landscape and customers, both potential and existing. This understanding forms a solid foundation for personalized approaches and accurate predictions of customer preferences.