Have you ever encountered a situation where a reputable hotel or agency constantly sends you generic marketing messages, which after a while, puts you off the very same hotel or agency simply because your inbox is being flooded by a tsunami of spam, junk messages and irrelevant content? Luckily, through the appropriate application of technology, this entire situation can be avoided or rectified.
With effective contextual marketing strategies, marketeers are able to create compelling and personalized campaigns that best suit individual hotel patrons by leveraging on the use of Artificial Intelligence, Chatbots and Predictive Analytics.
First, the system consolidates all current and prospective patron data across all hotel properties and business units before patron profiles are correlated with their historical transactions. This is merely the tip of the iceberg in terms of data gathering as the system will also be correlating data from external sources to establish complete patron profiles, so that the hotel is able to identify that patron’s needs, preferences and lifestyle requirements and desires.
In addition, the system will continuously refine the data based on patron interaction, gathering more information regarding customer preferences and tastes. All available data points, such as which products guests prefer, how often that particular guest stays, or what they normally travel for, will be collected in order to calculate the likelihood of a particular guest responding to a particular marketing campaign, identify which guests are likely to attrite, and identify acquisition targets.
By carrying out such data-driven marketing and creating enhanced guest profiles, a hotel would be able to provide an experience where a visit by any particular patron is akin to a return to their virtual vacation home, where all of their needs for the stay are taken care of, from the complementary white Chardonnay that is the patron’s favorite (instead of the red Merlot they aren’t fond of), down to the automatic provision of (American as opposed to European) breakfast in bed, given that the relevant patron is a well-known celebrity and prefers not to have breakfast at the hotel café. All done without the need of dedicating a sizable portion of the marketing team to gather such intelligence, freeing them to carry other tasks that demand their attention.
Hotel websites should not merely be passive booking engine, but rather, an AI-driven active platform that personalizes the entire reservation process. Using a Recommender Engine, if the system identifies viewership of hotel patrons, the engine would test different scenarios based on the call to action and optimize the experience on the website and booking engine in real time to improve conversions and increase product sales. For example, if it detects that visitors from China often search for information about oriental cuisine, it would recommend changing the way the site looks by placing oriental restaurant (with a focus on those that are linked to the hotel) information earlier on the website.
Hospitality is both a reputation- and impression-driven industry. Picture a different scenario where a fresh potential guest is about to book a room at a particular hotel, only to see on their Facebook wall that a friend of theirs has just left a scathing remark on the website. The remark however is uncalled for because it relates to the temporary closure of the hotel’s award- winning spa the day before due to a surprise visit by royalty. The AI’s ability to parse reviews and social media posts quickly and at scale will allow the hotel team to be aware of what people are saying, giving them time to respond quickly. At the same time, positive feedback can be shared and amplified (e.g. on the website itself and on the award-winning spa), whilst the marketing team reaches out to correct and deal with the situation arising from the negative feedback. In other words, the AI engine will ensure that the hotel is alerted to potential reputation damaging situations early on, providing them with the necessary time to respond accordingly.