“Just let the Machines do the Work”: Marriot’s Opportunity to Build on Starwood’s Digital Expertise

How Marriott Can Build From Starwood’s Machine Learning Expertise

Starwood’s early bet on machine learning solutions

The recent explosion in use of artificial intelligence and data analytics in the hoteling industry is no coincidence. In the past decade, the proliferation of digital technology has raised consumer expectations of convenience. Hotel brands face mounting pressure from data-driven disintermediaries – like Expedia or Priceline – and non-traditional substitutes – most notably Airbnb. Accordingly, revenue growth has slowed for the industry[1] and hotel booking windows are shrinking[2].

To compete, hotels have had to lean into the new digital world. One could argue that no major brand has done that better than Starwood, which was acquired by Marriott in 2016. Starwood’s strategy has long included building a competitive advantage in digital expertise as a means of driving guest loyalty[3]. It was among the first to introduce innovations such as smartphone check-in, key-less entry, and robot bellhops[4] to its suite of hotels.

In 2014, Starwood invested over $50 million to develop ROS, a state-of-the-art automated dynamic pricing system[5]. While dynamic pricing is now standard in the industry, ROS is unique in its comprehensiveness and machine learning orientation. It automatically calibrates pricing based on hundreds of variables, including booking/ cancellation patterns, competitor pricing, weather and climate, and booking patterns on other sites.[6] And, as ROS learns, it prices more efficiently. Starwood has credited ROS with a 20% improvement in pricing since its development.[7]

Starwood’s machine learning foray into customer engagement notably resulted in ChatBotlr, a chatbot that gives guests the ability to make service requests via text message. According to Marriott, “by leveraging natural language understanding and machine learning, ChatBotlr gets smarter the more it interacts with guests. Early findings show that 2 out of 3 Aloft guests are interacting or making requests with ChatBotlr and the service has [reached] a five-second response time.”[8]

Marriott’s challenge and path forward

Since acquiring Starwood, Marriott has doubled down on the Starwood’s investment in machine learning and IOT (Internet of Things) architecture. Their strategy, according to then Senior Vice President of Digital George Corbin, highlights a mobile-first mentality to personalization of the guest experience and real-time engagement.[9] Marriott’s short-term focus involves using artificial intelligence to anticipate what loyalty members want in their hotel stays and reacting real-time through a messaging system called mPlaces. [10] The medium-term focus appears to center around pulling in even more data to drive personalization and responsiveness. In 2017, Corbin highlighted what the future could look like for Marriot. [11]

[Marriot could pull in] information that … from your own interaction patterns with us, as well as some intent-based data from how you came to us, where you came to us from, what you were looking for there, and then leverage[e] that to dynamically adjust some of the content and the visuals and the messaging that you now begin to see in the app. … If you think about Google or Siri … the phone knows to listen to you. Our app could leverage that maybe and then direct us to a particular search or amenity or hotel. We would do that in those environments at the request of the member to develop the hotel room of the future. If consumers are being accustomed to talk to their homes they will expect to be able to talk to their rooms.[sic]”

A bright but cautious future ahead

In this author’s opinion, Marriott’s strategy is sound. By leveraging learnings from Starwood across its portfolio of hotels, Marriott is creating the revenue synergies I hoped to see from the acquisition. Further, research supports Marriott/Starwood’s thesis around the ability machine learning and dynamic customer engagement to create unique value in the hospitality space. [12] However, Marriott’s focus on personalization should not overshadow other ways in which machine learning can create value for customers; two areas come to mind. First, more can be done by Marriott/Starwood in using machines to optimize the use of time by its staff in everything from the check-in process to post-stay engagement. As Frank Reeves, co-founder of hotel technology company Avvio, notes “Little things, such as [dynamically] estimating when to refill soaps, can reduce time spent by staff knocking on doors and improve the guest experience.[13] Secondly, they should explore using machine learning to expand how they think about their customers. Nascent research points the ability to use machine learning technology to create more dynamic clusters of guest types that evolve over time. Such capabilities would improve the ability of Marriot to segment and target customers over the long run.

The question remains for Marriott/Starwood: In a space that is increasingly developing these digital capabilities – where Hilton is partnering with IBM to introduce robot concierges, for example[14] – how do you maintain a defensible competitive advantage in technology innovation? Only time will tell.

(782 words)

[1] CBRE 2018 Trends in the Hotel Industry. https://www.cbre.com/research-and-reports/2018-U-S–Hotel-Outlook. Accessed 13 Nov 2018.

[2] Boulton, Clint (2018). Starwood taps machine learning to dynamically price hotel rooms. CIO magazine. Accessed 13 Nov 2018. https://www.cio.com/article/3070384/analytics/starwood-taps-machine-learning-to-dynamically-price-hotel-rooms.html l

[3] Vondrasek, Mark (2015). Redefining service innovation at Starwood. McKinsey & Co. Accessed 13 Nov 2018. https://www.mckinsey.com/business-functions/operations/our-insights/redefining-service-innovation-at-starwood

[4] Boulton 2018

[5] Alexsoft (2018). How the Hospitality Industry Uses Performance-enhancing Artificial Intelligence and Data Science. Accessed 13 Nov 2018. https://www.altexsoft.com/blog/datascience/how-the-hospitality-industry-uses-performance-enhancing-artificial-intelligence-and-data-science/

[6] Boulton 2018

[7] Norton, Steve (2015). Starwood Hotels Using Big Data to Boost Revenue. Wall Street Journal. Accessed 13 Nov 2018. https://blogs.wsj.com/cio/2015/02/10/starwood-hotels-using-big-data-to-boost-revenue/

[8] Marriot International 2017. Marriott International’s AI-powered Chatbots on Facebook Messenger and Slack, and Aloft’s ChatBotlr, Simplify Travel for Guests Throughout Their Journey. Accessed 13 Nov 2018. http://news.marriott.com/2017/09/marriott-internationals-ai-powered-chatbots-facebook-messenger-slack-alofts-chatbotlr-simplify-travel-guests-throughout-journey/

[9] Marriot International 2017. Marriott Reimagines Its Mobile App To Meet The Needs Of Modern World Travelers. Accessed 13 Nov 2018. https://news.marriott.com/2017/02/marriott-reimagines-mobile-app-meet-needs-modern-world-travelers/

[10] Ting, Deanna (2017). What Marriott Learned From Starwood’s Loyalty and Digital Expertise. Skift. Accessed 13 Nov 2018. https://skift.com/2017/02/13/what-marriott-learned-from-starwoods-loyalty-and-digital-expertise/

[11] Ting 2017

[12] Aluri, A., Price, B., & Mcintyre, N. (2018). Using Machine Learning to Cocreate Value through Dynamic Customer Engagement in a Brand Loyalty Program. Journal of Hospitality & Tourism Research.

[13] Reeves, Frank 2018. How Artificial Intelligence will bring the human touch back to hotels. Travel News Daily. https://www.traveldailynews.com/post/how-artificial-intelligence-will-bring-the-human-touch-back-to-hotels

[14] Hilton 2016. Hilton And IBM Pilot “Connie,” The World’s First Watson-Enabled Hotel Concierge. http://newsroom.hilton.com/corporate/news/hilton-and-ibm-pilot-connie-the-worlds-first-watsonenabled-hotel-concierge



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Student comments on “Just let the Machines do the Work”: Marriot’s Opportunity to Build on Starwood’s Digital Expertise

  1. Very interesting read! Thinking through the “customer journey” at a hotel from my own perspective, it does seem that there are many areas where machine learning (and technology more broadly) could help enhance the experience. To your last point on how to differentiate using innovative technology, I imagine there is opportunity for hotels to leverage customer data from loyalty programs to learn more about their guests and create personalized offers / experiences.

    As an example, IHG has a program called “Accelerate” that offers quarterly promos to Rewards Club Members. The promos are personalized at the customer level, but a major complaint is that they often don’t seem relevant to the guest’s travel habits (article here might be an interesting read: https://www.headforpoints.com/2018/04/14/ihg-accelerate-q2-summer-2018/). Perhaps this could be the type of area where machine learning could help?

  2. Very thoughtful analysis. Machine learning and AI is indeed transforming the travel industry, as all of the main players rush to leverage machine learning / AI algorithms to establish competitive advantages over their peers. I think your last question regarding the sustainability of these competitive advantages is a good one, especially as it pertains to the travel industry. Travel is a deeply personal decision. With the democratization of data, consumers are smarter than ever about the multitude of options available to them. As such, consumers will continue to demand more personalized user experiences to convert customers and drive loyalty.

    Machine learning enables corporations to provide much more highly personalized experiences with their customers. In my opinion, given this dynamic in today’s age, the first-movers within the travel industry to establish deep, intimate relationships with customers will be the ones to shape the industry over the foreseeable future.

  3. Great read! I wonder if the applications of ML on the higher-end brands within Marriott/Starwood will be more limited. While ML-induced pricing and chatbots sound great for the Aloft, I wonder if high-end patrons will be turned off by prices that bounce around — they certainly would be by chatbots.

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