Which US state is famous for its extra-small soft drinks? Mini-soda! ;) Jokes aside, the tourism industry was outpacing the global economy till 2019, and then it took a nosedive in 2020. Yes, you know the reason. But the good news is travel & tourism are regaining traction. And the tourism industry is leveraging tech to accelerate things up. One such impactful and transformational tech for the travel and tourism sector is Big data. This insight aims to be your guide on “Big Data In Tourism”. Post-reading this insight, you’ll know:
Table of Contents
Part 1 What is big data in tourism?
Part 2 How you can harness/extract big data using web scraping?
Part 3 Business use-cases of big data in tourism
Part 4 Big data challenges in travel & tourism
What is big data? Big data is an approach to systematically extract, process, and visualize large data sets. What does that mean? Suppose that you’ve personal details i.e, name, age, gender, country, etcetera of 1000 customers who have visited France in 2020. Is this big data? Not really. But if you’ve data about a million people who hit different corners of the world, the hotel they stayed at, the food they ordered, the places they visited, events that took place in different geographies, different online/offline resources they utilized etc., then ideally, it should be considered Big data. In a layman’s lingo,
So, you use
What sort of big data can be captured in the tourism industry?
To extract travel & tourism big data, you can prefer:
Tourism web scraping is an approach to programmatically extract data from travel & tourism-focused websites. You can use web scraping tools or write your scripts to extract data from these websites. For example, let’s say, you need hotel & restaurant data i.e., prices, reviews, services provided, location etc., from “Booking.com”. You can easily scrape hundreds and thousands of hotels & restaurant data from Booking.com within a few minutes.
Use web scraping tools if you need
2. Internal & external resources
The key to reviving tourism & sister sectors is to harness the power of culture and creativity, optimizing travel operations, personalizing offerings, delivering seamless experiences, and unlocking new growth channels. Big data can be of help here:
1. Tourism Market Research
In the last decade, the penetration of mobile devices has positively catalysed the amount of data yielded by different sources. In the tourism sector, the data falls under three categories:
2. Rationally allocating traffic resources
Real-time traffic flow state identification and prediction could be the answer to alleviating traffic congestion at tourist attraction points and on tourist routes:
3. Operation management of tourist attractions by analysing tourist behaviours
4. Estimation of travel demands
Travel demands have their roots in the “demand” concept of economics. Tourism demand generally means, tourist arrivals & tourist expenditures. You can collect and analyse tourist arrival data or expenditure data based on your objective, whether it is to maximize the tourist footfalls or to maximize the expenditure. For example, tourism package planners can customize their plans to suit the pockets of tourists from a particular source country. Let’s say, if the average expenditure of tourists from country XYZ is more, then maybe national tourism boards can plan to aggressively promote tourism in the USA, and even plan with service providers and tour package planners to lower the prices. This may positively catalyze the tourist in-flow.
5. Revenue Management
Hotels and restaurants can have information around occupancy rates, current bookings, prices, etcetera and combine it with external data like climate conditions, school vacations, local events, flight information, etcetera to effectively forecast the demands and make strategies for maximizing the revenue. For example, sensibly hiking the prices.
6. Brand Management, Competitor Monitoring & Customer Experience
91% of young customers trust online reviews. Today, social media is so powerful that one negative tweet from an influencer can drastically bring down revenues for a business. It’s important to monitor your brand image by keeping a tap on social media, blogs and online review platforms. On a positive note, you can also monitor what customers are liking about your service and highlight it in your marketing campaigns, improve it further, etcetera. You can not only analyse customer sentiments for your brand but also
7. Personalized Marketing
Diversity, leisure, business travel, meeting relatives, etcetera are the leading factors influencing people to travel. If you know the intent behind travel, you can personalize your marketing strategies to clock more sales. The more qualified data you have, the better you can execute targeted personalized marketing.
8. Intelligent Travel Bots
The use of big data for NLP is an industry-agnostic use case. Social media textual big data can be well used for feeding machine learning algorithms. As these tourism-related social media posts are mostly by tourists, it’s easy to develop intelligent customer-facing bots to address their questions in a language the tourists understand.
*** Cybersecurity & Data Privacy:**
Web scraping tools have made it damn easy to extract tourism big data from the web. But big data has its challenges too. With increased reliance on tourism big data, the risks of data breaches are equally high. With every breach, trust, confidence and brands are put at risk. Data governance & data ethics is another big concern related to tourism big data.
*** Analysing Unstructured Data**
Though it is easy to scrape and collect data using web scraping tools, the web is filled with dirty, unstructured data which is tough to analyse. The efficiency of ML algorithms remains a challenge.
UNWTO has forecasted 1.8 Billion international tourist arrivals by 2030. Successfully leveraging the big data, and other digital transformation technologies will be key to unlocking and harnessing new growth channels in the tourism industry. In this insight, we gave you an in-depth overview of “Big Data In Tourism”, how to extract travel & tourism data, big data use cases in tourism, challenges, etcetera. With technological advancements, we are seeing an unprecedented flux in customer behaviour, business operations, and the way people live and communicate. One tweet can impact businesses in unpredictable ways. It’s important to take calculated, validated, evidence-driven business decisions.