4 Ways to Achieving Recovery & Growth in the Hospitality Industry

Aditya Durai
April 11, 2022 8 minute read

The global smart hospitality market has been estimated to grow to a valuation of $4132 billion by 2025 [1] – and while the predominant contributors to this growth have been streamlined revenue management, improved marketing automation, and better third-party integration, among others, factors such as improved customer experiences, better customer retention, reductions in operational costs, and access to global markets continue to be top priorities for the segment.

However, given the shocks that have impacted the hospitality industry in the past two years, namely, significant drops in bookings, closures, and travel restrictions across the globe, as well as customers’ stronger focus on health and safety, businesses have faced multiple setbacks – the decimation of business travel and the slow recovery of the leisure travel market, and close to 660,000 layoffs [2] and losses to the tune of £200m every day in 2020, in the UK alone. [3] While the sector is on the path to recovery, here are a few ways in which data is enabling resilience, growth, and superior customer service for businesses:

1. Streamlining planning & marketing through automation

With levels of demand and supply fluctuating across seasons, geographies, governmental restrictions, and public health situations, businesses can utilize intelligent ML capabilities to sort through online reviews, information, customer sentiment, and more to get actionable insights on changing global scenarios. Advanced analytics solutions here can help drive greater booking volumes by analyzing data, predicting fluctuations in bookings, and recommending the best courses of action. Following this, data-driven dynamic pricing can be leveraged to generate special discount rates during low seasons and maximize occupancy rates.

Further, by gaining access to the demographic and psychometric information of online users, as well as data across third-party platforms, apps, and social media channels, hospitality businesses can tailor their marketing strategies and diversify occupancy across guests, in-person events, and conferences.

For example, for hotels doubling as quarantine spaces and hospitals, data analyses can help monitor health statuses, indicate the need for virtual consultations, and develop personalized room service and healthcare plans for occupants. Further, with hybrid events becoming more commonplace, intelligent monitoring can be used to both ensure safety on premises as well as monitor traffic and engagement through virtual platforms, indicating avenues of better service diversification and improvement.

Given the massive shocks to the industry in the past couple of years and the need to shore up responses to changing public health situations, AI is set to offer greater visibility and intelligent tracking, helping businesses accelerate planning cycles and account for shorter periods of relaxations amidst restrictions. In the longer term, such technology will not only help businesses recover previous levels of demand but also quickly pivot to reach out to new segments and undiscovered geographies.

2. Enhancing front-end customer experiences & safety

With social distancing and safety requirements in place, the hospitality industry has innovated to create new, safe experiences, using QR codes, contactless check-ins, computer vision-enabled thermal scanning, as well as wearables and sensors to adhere to safety protocols.

For example, a major hotel chain replaced room keys with wearables, allowing guests to use their smartwatches to unlock rooms, elevators, and gyms, [4] in an attempt to make stays more contactless.

Ranging from creating cleaning schedules to personnel shifts and accurate distancing enforcement – data can be collated from these multiple sources to help businesses adhere to regulations across geographies while cutting down on the manual tasks of observation. For instance, alerts can be instantly set up in cases of non-compliance with PPE norms, while incoming customer traffic can be similarly forecasted and anticipated, right down to hours and minutes, to ensure contactless services.

Further, bots have been widely touted as the next generation in consistent guest experiences, set to take on housekeeping, baggage handling, security, room service, bartending, and a quarter of jobs in the industry by 2030. [5] However, more immediate applications for robots now include eliminating human error in tasks ranging from check-in and room allotment to room service and cleaning. For example, a hotel chain operating in Manchester, London, offers AI concierge services that help guests check in and out, respond to queries, and order room service. What’s more, a hotel in Nagasaki has become the first in the world to be fully staffed by multilingual robots for check-in and checkout processing. [6] Such adoption in use is expected to help meet the demand for safe and sanitized rooms, contactless processes, as well as a connected customer experience.

More importantly, multilingual chatbots, as a form of conversational AI, are set to augment guest experiences, handling multiple inquiries at the same time, stepping in to make up for labor shortages, and even keeping customers engaged through consistent and tailored messages. Chatbots linked to websites, social media platforms, and apps can also provide 24/7 customer support to guests, helping convert website visits into bookings, especially during lean periods. Through customized, personalized journeys, messaging around safety and enhanced customer experiences can further be reinforced, giving guests greater visibility into hotel experiences and building customer trust.

3. Tailoring customer experiences with ML

Given recent market situations, hospitality businesses are increasingly turning to technology to help improve booking rates and understand customer sentiment. By tracking guests’ activities online, the data obtained can be combined with information gained from surveys, social media, and more to create unique and personalized experiences for guests – for instance, through tailored local getaway plans and work-cations. With the greater demand for localized travel and unique vacation experiences, information across social channels can be analyzed to recommend lesser-known destinations, create tailored marketing messages, and even offer AR/VR tours of exotic locations, according to individual customer profiles.

Further, for guests visiting locations, custom room temperatures, menus, music, lighting, and so on can be provided to elevate customer experiences, using information obtained through advanced algorithms. For instance, in recent times, a luxury hotel brand has used ML-driven applications to provide personalized experiences for guests, ranging from booking to dining. [7] The brand reported finding that 80 – 90% of guests tend to modify their breakfast orders – information that can be used to streamline and modify room service significantly. Factors such as customer behavior on apps, third-party sites, and so on can be used to develop personalized messages and enable better marketing attribution. Data management platforms and cloud technologies can further help businesses scale this growth, optimizing technological investments, ensuring better integration, and increasing transparency in the longer term.

4. Aiding sustainability & innovation through smart technology

Data-driven decisions can not only be used to improve revenue management but also aid environmental conservation efforts through smart energy, waste, and water monitoring tools. Given the rising standards for net-zero emissions across industries and the necessity of sustainable operations for customer satisfaction, businesses are now increasingly turning to analytics to gain real-time visibility into emissions, operations, and methods of reducing carbon footprints. This is true of the hospitality sector as well: for example, an American multinational hospitality chain has been able to achieve carbon emissions reductions equivalent to removing 390,350 cars from streets while saving over $1 billion in utility costs [8] with the aid of analytics-driven planning and decision-making.

Intelligent tools can further be implemented across event management efforts to save time and costs – 3D models of event spaces can be created to plan arrangements, present templates from previously organized events, host virtual demonstrations, and even facilitate smoother communications among various teams simultaneously. In addition to cutting down on the use of physical resources, such innovation can further boost engagement as well as planning cycles, helping businesses optimize their outreach initiatives. Meeting such sustainability and resource optimization goals through informed planning can help businesses tide through the challenges brought on by the pandemic to adopt forward-looking, innovative approaches to hospitality.

The future of hospitality: Intelligent and data-forward

AI is reshaping the hospitality industry as we know it by enabling dynamic and disruptive changes through technology. From front-desk operations, room service, valet services, and cleaning to maintenance to energy use monitoring, it is being leveraged to augment efficiency across different avenues. What’s more, advanced applications that are set to take shape in the future of hospitality include robots doubling as support staff for late-night shifts, robot bellhops, and even all-robot staff – while these innovations are still in the making, the digital age will continue to pave the way for next-level customer experiences, and new horizons for hospitality.


Aditya Durai

A seasoned data science practitioner with nearly 8 years of experience, Aditya Durai, Principal, MathCo, spearheads multiple enterprise-wide data science initiatives and delivers successful business outcomes for leading Fortune 100 enterprises. With deep knowledge of algorithm design, statistics, and machine learning, Aditya has been instrumental in building over 100 solutions, including yield optimization in manufacturing plants, image processing, object detection for retail shelf optimization, and forecasting solutions for supply chain planning. In addition to his many achievements, he acts in an advisory capacity to multiple Fortune 500 enterprises for data science solutions across merchandising, pricing, and trade promotion optimization.