THR's opinion
“Destination brand love” and Machine Learning: unlocking new ways to evaluate tourism destinations
What is destination brand love?
Brand love, a concept that has gained a significant traction during the recent years, is one of the most influential marketing constructs in the travel industry. The term is defined as the degree of emotional and passionate affection that a satisfied consumer has for a particular brand. For the destination branding sector, the concept of brand love expands to a whole new level: the feeling of love a visitor holds for a destination.
Brand love is a compelling indicator for the overall success of a destination. Destination branding is usually established to initiate positive connections and to clarify the differences and competitive advantages between one place and other places. Broader destination attractiveness can be measured through various KPIs: number of returning visitors, online searches, number of key attractions, etc. However, destination brand love is a sentiment associated with the emotional attachment, when a destination holds a special place in a visitor´s heart.
Well-developed destination brand love is an excellent asset for a destination to distinguish itself from competitors. Destination branding establishes a strong ground for the acquisition of new travellers, as based on various sources of research, and positive destination image has been proven to be a better and more reliable predictor of loyalty compared to other marketing concepts such as satisfaction.
Measuring the destination brand love
Let´s say you believe your destination is already loved by the tourists. But how much? A useful way to measure if a tourist loves destination is to ask about the propensity to return, in other words, to measure destination loyalty. Other emotional attachment indicators are positive associations, affection, pleasure, and passion. While the latter concepts can be challenging to measure, brand loyalty offers a clear distinction between four approaches: cognitive, attitudinal, conative, and behavioural loyalty towards a brand.
While in the past measuring brand love has imposed a great challenge due to the limited amounts of data available, during the last 10-15 years the Internet has provided destinations with a tremendous data resource: online reviews.
Millions of tourists express their opinions, concerns, sentiments, and experiences online. While being a powerful tool to capture what travellers love about a destination, online reviews contain endless amounts of unstructured data, which is where data science adds substantial value. This allows to measure not only how much tourists love the destination, or how loyal they are to the destination, but also what particular concepts of the place are the ones evoking pleasant feelings and the desire to come back again and again.
Machine Learning and destination brand love: unlocking the insights
Machine learning (ML), a powerful method of automated data analysis, is not a new concept in the travel industry. ML offers a uniquely powerful technology in the form of text mining that allows transforming the free (unstructured) text, such as online comments, into “normalized, structured data suitable for analysis or to drive machine learning (ML) algorithms”. Compared with traditional qualitative text analysis methods, such as surveys or questionnaires, text mining enables researchers to study an enormous amount of textual data more easily.
Why is it important for the brands of destinations? A recent study of the connection between destination brand love and disruptive technologies adopted Machine Learning to identify the topics discussed in destination reviews. Several keywords were identified in each topic and then an individual content analysis was carried out to find out which of those keywords were positive, in other words, which words represent the brand love. In short, Machine Learning worked as a powerful tool to rapidly extract precise information from vast amount of data sources.
The key takeaway from the study is that destinations now possess an extremely powerful and rather inexpensive tool to gain insights directly from their visitors in their own words. It allows marketers to extract the core of what is best in the destination and use it to develop appealing strategies of place branding that highlight its unique selling proposition points.
Conclusions
Every destination wants to be loved. In the digital era, measuring destination brand love has become a relevant, but time-consuming and costly process that does not always bear clear results. This is where harnessing the right technology can turn traveller’s perception of a destination into a favourable strategical angle.
The combined use of Machine Learning and text mining offers a quick, powerful, and time-saving approach to look at what travellers really think of a destination. Capitalizing on the data insights and turning the key aspects of what travellers adore in a destination into an immerse experience is what makes a real difference in terms of competitive brand marketing. Not only it enhances all types of brand loyalty, it also allows to generate more traction for the destination, which in turn means more new visitors, more positive experiences and more destination brand love.