The Wall Street Journal reports on how retailers are striving to keep consumers, current and potential, on their sites, physical and virtual. The tools and technology they have deployed offer a template for hoteliers to emulate and even enhance.
The Journal article headlined ” Retailers Turn to Silicon Valley to Lure Customers” notes that high street is using “personalization” in their efforts to attract and retail clients. For instance, “Sunglass Hut is employing deep learning (a machine learning technique modeled loosely after the human brain) and image-recognition technology from San Francisco-based Sentient Technologies Holdings Ltd. for its e-commerce site, When shoppers click on a pair of shades, the “see similar styles” the option uses image recognition to show other sunglass choices, instead of predicting what the person might want based on what other people have purchased.” In an scarily eery echo of the existential dilemma posed by OTAs to hotels the CEO of Salesforce.com‘s Commerce Cloud points out that “with online pricing and inventory easily accessible, consumers are increasingly becoming brand and retailer agnostic”.
While deep learning and image recognition seem to lend themselves more readily to OTAs with their unstated goal of commoditizing hotels they clearly could have considerable implications for hotel companies. Unfortunately, many hoteliers and hotel companies are focusing on robots and their implications for hotels. While there, potentially, is a significant service and cost advantage to employing robots in the front desk (Hen-na hotel Japan), room service and the bell desk they have little, if any, implication for customer acquisition and retention. Instead a customer driven AI and machine-learning initiative can amplify service immeasurably.
For starters, mobile check-in, already in place in many hotels, obviates the step of having to ask the guest’s name as a scan would determine that. From there, using a version of SAP’s app developed for retailers, a hotel can quickly dig into a trove of publicly available personal data, including his or her last hotel stay and whether the person prefers still or sparkling water, bed type etc along with, potentially, some of his or her public social media presence to better serve them during their stay. This could include direct messaging to guests highlighting a hotel/resort’s features that match their profile, matching local attractions and outlets to their perceived needs and flight and fare alerts. The resultant heightened level of customer service gets layered with each stay going on to aid the customer retention process.
Few companies delve as deeply into data science as Airbnb which uses technology to advance their exponentially growing global footprint even while obfuscating when it comes to compliance in a host of increasingly restrictive jurisdictions seeking the unicorn’s compliance. Airbnb has deployed a variety of tools including image recognition to gauge if there is a match between host and guest, natural language processing to (arguably falsely by monitoring review boards) elevate the level of reviews and collaborative filtering to glean preferences from an aggregate of related hosts.
Some of the foregoing techniques could be used (and perhaps are) by hotel companies to personalize the customer experience. For example there are off-the-shelf image recognition services such as google cloud vision that can be integrated with a hotel company’s app with the latter being used for sentiment analysis to analyze emotional facial attributes in response to specific customer-hotel interactions. As Microsoft’s general manager of world-wide retail notes “Digital transformation is upon you whether you want it or not”. Embracing it ahead of the curve can only be a net positive for hoteliers.