Big Data

How Big Data can help boost tourism numbers

According to the tourism sector performance 2018 report released by Tourism and Wildlife Cabinet Secretary Najib Balala, hospitality industry is on an upward growth trajectory.

Notable growth were recorded in tourism receipts in 2018 with the ministry reporting Sh157 billion compared to Sh119.9 billion earned the previous year.

Within the same period, tourist arrivals at Kenya’s main airport – Jomo Kenyatta International Airport in Nairobi increased from 771,497 to 1,342,513 while interestingly, Mombasa International Airport dropped from 276,316 to 118, 113. Visitors arrival for 2018 grew to 2, 025,206 with Africa as the main source of market accounting for 40 per followed by Europe at 30.22 per cent.

International visitors experienced a growth of 37.33 per cent and domestic bed nights grew by nine per cent. The drivers of this exemplary performance was attributed to revitalised marketing activities, improvement on the rank of ease of doing business in Kenya which the World Bank rated at eight places improvement to number 80. There is also improved hotels infrastructure, with the Knight and Frank 2018 report ranking Kenya third on the continent after Lagos and Abuja in the Hotels Pipeline report.

In a quest to drive tourism number upwards, Kenya Tourism Board (KTB) said its target is to hit 4.5 million bed nights by June, from an estimated 3.9 million in 2018. Chief executive officer Betty Radier said recently that they have established a business development unit, which is expected to conclude the exercise of enumerating and registering the sites across the country ahead of a deadline set in June.

This move is welcome and to help KTB meet its objective, they ought to leverage on emerging opportunity. One such technology is Big Data Analytics and here is why.

Tourists can now access different sources of information, and they can generate their own content and share their views and experiences. Tourism content shared through social media has become a very influential information source that impacts tourism in terms of both reputation and performance.

For instance, according to a report by Airbnb, a digital room booking platform that leverages on shared economy philosophy like Uber, has seen 3.5 million guests arrive at listings across Africa since its inception.

In Kenya guest arrivals have grown by 68 per cent last year on Air BnB and this is set to grow as the app becomes even popular among Kenya real estate owners.

Besides, AirBnB recently launched an expeditions service allowing users the option to book “immersive” travel experiences, which includes city tours, peer reviews and recommendations, as well as meet with locals.

The new feature, titled “Trips”, aims to bring together to enjoy unique local travel experiences, from forest trail in your local village to marathon running in the highlands, to boat rides in your local river using the Airbnb app.

The tours and experiences, which can entail multi-day activities or one-off events such as concerts, are all hosted by locals are set to disrupt the hospitality ecosystem going by what we have experienced with crowdsourced platform Uber.

Adoption of this crowd-sourced platforms in the hospitality industry has led to high volume of data on the Internet reaching a level that makes manual processing almost impossible, demanding new analytical approaches. One such approach is Sentiment analysis, it is rapidly emerging as an automated process of examining semantic relationships and meaning in reviews. – The writer is an author and data scientist at Predictive Analytics Lab

By Timothy Oriedo: Author and Data Scientist at Predictive Analytics Lab

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