According to Forbes, 53% of companies are using big data analytics today, up from 17% in 2015, with Telecom and Financial Services industries the fastest adopters. The importance of big data doesn’t revolve around how much data you have, but what you do with it. You can take data from any source and analyse it to find answers that enable:
• cost reductions
• time reductions
• new product development and optimised offerings
• smart decision making.
Big Data is commonly described through the four Vs: volume, variety, velocity, and veracity of data. Because it involves unstructured, semi-structured and structured data, it requires advanced analytical techniques to process and manipulate the data which makes it more challenging compared with traditional analytical tasks.
The rapid emergence of information and communication technology (ICT) has had a significant impact on people’s daily lives and in turn has provided access to a considerable variety of data and information. The tourism industry is one of the leading sectors that has adapted to the evolving technology and the availability of new data sources which includes credit card transactions, mobility-related data, booking behaviour and, especially, the sharing of experiences.
Travelers are now more likely to research and plan their trips online and in turn share their experience and recommendations for other travelers on sites such as TripAdvisor, Expedia, VirtualTourist and LonelyPlanet. Online social media, such as Twitter, Instagram, Facebook, FourSquare, Sina Weibo, and GooglePlus, also play a significant role in creating electronic word-of-mouth (e-WOM). Reviews posted on social media are often short, yet written to reflect a particular emotion, opinion or experience. These reviews are of great interest to marketers, service providers, managers, and destination brand builders, as they help to develop or correct destination image, to target marketing, and to improve service quality.
Importantly, travel websites and platforms, blogs and online social media present cost-effective ways to collect rich, authentic, and unsolicited data on travelers’ opinions. Online content that reveals customer opinions is potentially a highly valuable source of feedback and information for tourism decision makers. In an increasingly competitive landscape, where more and more destinations seek to benefit from the globally expanding tourism industry, and where new business models disrupt traditional supply chains (e.g. Airbnb and Uber), such customer intelligence is critical. Obtaining pure and unfiltered feedback in real time is particularly pertinent, given that tourism is transitioning from a service economy to an experience economy, where tourists are more ’savvy’, have higher expectations and demand more personalised services.
The amount of data being generated by travelers is beyond human capacity to manually search for and analyse. Social media alone generates millions (or more) of data points of possible interest over short periods of time. Twitter posts, as well as some other social media data, are useful because they typically contain time-location stamps, allowing analysis of spatial phenomena. An analysis of Twitter posts from the Great Barrier Reef region in Australia generated close to 200,000 tweets over a 9-month period, which were analysed by keyword and sentiment analysis to gain an understanding of environmental conditions of the Reef, as perceived by visitors and residents.
However, there are several limitations to using such data. First, each platform is typically used by a particular user group, which is not representative of the wider population. Twitter, for example, is dominated by English language users, often from the USA, and excludes large markets, such as Chinese visitors who prefer to use Wechat or Weibo. Furthermore, when using information from social media data, it is important to understand people’s different cultural and geographic backgrounds. Just like with traditional surveys, different cultures express their views and feelings differently, and they also have different priorities or expectations of a successful holiday. Information provided in social media interactions is highly subjective. Thus, comparing posts directly between different user groups is problematic.
Ultimately, Big Data will only answer those questions that have been asked with particular domain knowledge and previous experience. Collating multiple data in itself will not generate useful research questions, nor will it provide meaningful insights. It’s important to remember that the primary value from big data comes not from the data in its raw form, but from the processing and analysis of it and the insights, products, and services that emerge from analysis. The sweeping changes in big data technologies and management approaches need to be accompanied by similarly dramatic shifts in how data supports decisions and product/service innovation.