Self Service Analytics: How Small and Independent Hotels Can Use Sentiment Mining to Leap Ahead in Post-COVID Revival

Written by: Sanjay Nadkarni, Ph.D.

The importance of guest reviews in the hospitality industry is unambiguous. In the pre-Covid-19 world, an entire business ecosystem evolved around analyzing reviews to gauge sentiment. Considerable research has confirmed the link between review scores and revenue. Though estimates on the magnitude of impact may vary, there is clear evidence of a strong correlation between guest sentiment and revenue metrics.

Hotel businesses that can afford the resources have invested in the development of guidelines and SOPs to handle guest reviews in the public domain.

The objective: climb to the top of the ranking hierarchy on a multitude of review sites with the expectation that this would translate into more bookings. Some may go to the extent of engaging in “black hat” tactics such as posting fake reviews that are both critical of the competition and complimentary of their own business. In the bargain, they may or may not get caught out — depending on the sophistication of the algorithms at work in the back-end of these review sites. In many instances, trying to game the system with such tactics in order to come out on top winds up becoming a losing strategy.

Review sites deploy ranking algorithms that vary in consistency and transparency. They are sometimes perceived as having an algorithm bias in organic rankings for hotels where there is a paid relationship in place — wherein, the extent of the bias is directly proportional to the monetary value of the relationship. Such perceptions are purely anecdotal and difficult to conclusively prove or disprove given their circumstantial nature.

Those most susceptible to be on the wrong end of algorithm bias tend to be the hotels that do not have the wherewithal or resources to engage in paid relationships with the review sites. Smaller brands are often also time-poor in their abilities to monitor and respond to reviews. The smaller the brand, the more elastic the demand. Independent hotels and small chains tend to be more sensitive to their reviews and rankings, with little or no bargaining power with the review sites. While on the other end, their competition may be using legacy sentiment mining platforms — which may be clunky and expensive but also assist in staying ahead in the rankings.

Other than feeling helpless, what can such hotel businesses do? Imagine a scenario where, despite providing the best hospitality and garnering rave reviews, your business appears nowhere near the top of the stack on review sites. Who is to blame? Pointing fingers at the deep-pocketed competition or at the review sites themselves will not help. This is not about who is right or wrong, but about the sheer disadvantages faced by small hotels on account of their scale in the game.

There is hope. The democratization of data science is having a spillover effect that allows for the development of agile, innovative and yet affordable solutions that can be leveraged by small, independent hotels to blunt the advantage traditionally enjoyed by large hotel chains. As data-driven decision-making gains currency across sector verticals, every aspect of the hotel business is seeing an impact. Insights derived from mining data using complex and expensive enterprise-level platforms can now be gleaned with leaner, user-friendly and more economical self-service analytic tools available on the SMAC (social, mobile, analytics, cloud) stack.

What used to be the preserve of large chains in terms of BI and analytics prowess is now accessible to all. It is another question as to why the big chains are not mainstreaming these agile new solutions as rapidly as they should. This is their shortfall. Small and independent hotels have the innate advantage of being nimble enough to leapfrog into adoption of these agile platforms. Data-driven decision-making capabilities that were “nice to have” before Covid-19 are now necessary to accelerate the post-Covid recovery journey — and this includes mining the guest experience through sentiment analytics.

In the post-Covid landscape, reviews will assume even more importance, and the focus will increasingly pivot towards health, safety and hygiene. The ability to collate, analyze and respond to guest feedback in near-real time will set the winners apart. With priorities shifting from a value for money (VFM) to a value for health (VFH), adoption of such agile tech is the perfect opportunity for a fresh start for small and independent hotels.

Sanjay Nadkarni, Ph.D. is Director of Research & Innovation at Emirates Academy of Hospitality Management. Nadkarni’s domain expertise is in the convergence space of digital, analytics and sustainability in the service sector. 

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