How Predictive Analytics Assists in Travel Marketing?

In the current technological space, Billions of data points are being generated and stored each second. The larger the volume of generated data points, the greater the accuracy of the derived analysis. This is precisely where predictive analysis proves its worth in the modernised digital tech sector and marketing industry, or more specifically in this context, the travel industry.

Travel and tourism was the second sector to have the fastest growth recorded back in 2018, right after the tech sector. It contributed almost $9 trillion to the world’s GDP and simultaneously created over 300 million new job opportunities in the same year. As one of the oldest trades that exist to this date, the travel sector has undergone multitudes of changes and improvements to accommodate all types of clients and provide them with the best travelling experience and customer services.

In 2022, the industry has noticed an upward trajectory in travelling after the colossal drop during the pandemic. This led the travel agencies to employ social media and extended media coverage to reach their potential clientele. This competitive awareness encouraged countless noticeable advancements in different aspects of the travel industry and the way it is marketed to its audience.

The developments made in the field of technology and Big Data have encouraged the use of predictive analytics in recent years to expand on business goals mainly through marketing. This creates a scope for many large-scale organisations in the travel industry to achieve a competitive advantage over their peers, which is paramount for a business to survive in this economy.

Before we discuss how predictive analytics assist a travel organisation in marketing its products and services, we should first evaluate our understanding of the technique itself.

What is Predictive Analytics? 

The term Predictive analytics refers to the predictions made by using statistics based on past data and modelling techniques about future outcomes and performance. Or in other words, it is an advanced form of data analytics.

By observing and analyzing previously stored data with the combination of statistical modelling, data mining and machine learning techniques, the system can provide accurate insights about future trends and outcomes. Let’s have a rundown of how different aspects of these techniques are combined to assist in giving out results with high accuracy rates.

• Data Mining: Data mining can be used to figure out patterns and relationships among a huge amount of data points which can then be used to outline the overall behaviour of the event they are affiliated with.
• Statistical Data Modelling: After managing the stored data through Data Mining, a statistical data model can be established that relates the collected data to their anticipated outcome. Now, whenever new data is fed to the model it can accurately predict a possible outcome for that data point.
• Machine Learning: Machine Learning is used to find patterns from the collected data points by carrying out repetitive methods and techniques.

Predictive analytics can be helpful in figuring out patterns to identify risks ad profitable opportunities based on past data collected from the transactional database, equipment log files, media files and other documents. Using predictive analytics, these stored data are then analyzed and examined by data experts to make predictions about future events.

Now with a clearer understanding of predictive analytics, we will take a look at how it has helped in travel marketing.

Use of Predictive Analytics in Travel Marketing

Optimising Marketing Campaigns

A predictive analytic model can be useful in determining a prospective consumer's reaction or response by observing the past data and behaviour of the customer. This can open up opportunities for publicised cross-selling and personalised marketing campaigns and promotions.

By managing the vast amount of customer data, predictive analytics only promote or recommend the deals and packages that align with consumer behaviour.

Segmentation of Marketing Lead

By observing the behaviour of consumers across multiple social media platforms and websites, predictive analytics can assist in segmenting the marketing leads by displaying ads on those sites. This allows the business to attract customers towards its platform and check out the deals and services it provides.

We have often noticed various ads for products or services we might be interested in, on top of websites we constantly visit. This is due to Predictive analytics gathering our data from online platforms and processing it to promote these ads to us.

Detects Potential Customers

Through keen observation of a customer's past purchases, predictive analytics can explore “expect to purchase”. When all the available data of an individuals’ purchases, likes or dislikes are analyzed it can give a clearer view of what deals or services they will be intersecting in buying from your travel business and whether their profile matches with your ideal consumer.

People post about their likes and dislikes on social media platforms and often give out similar details on other websites for various reasons. These data can help predictive analytics in creating an ideal consumer profile and then match prospective clients against the profile to promote the packages which can guarantee a sale.

Upselling and Cross-selling

Upselling and cross-selling through a proper recommendation system can increase the value of a company. In some travel companies, travel agents still recommend services to customers by having long conversations with them to find out what services they prefer. With predictive analytics, there is no longer the need to do that.

Using the currently available data on prospective consumers, predictive analytics can create a cross-selling model to determine which services of the business will attract them. It helps the company recommend relevant products to the customers by understanding their behaviour more efficiently.

Analyzing Social Media Posts

There is no denying that social media platforms play a big role in influencing consumers into buying things and driving sales for many well-defined organisations. It can encourage travel habits and the choice of destinations. Sieving through millions of posts, pictures, recommendations and reviews is not possible for any number of people to undertake without fault. Understanding the polarity of these posts, the behaviour of the general user demographic, and what travel experiences they are looking for can also be a challenging task for a company without the help of predictive analytical techniques.