Industry
Travel and Logistics
Data and AI in Travel Industry for a Memorable Passenger Experience
HIGHLIGHTS
- The hospitality industry is at a crossroads. Processes like reservations have substantially digitalized over the last two decades. While this has provided a greater reach along with location independent and convenient access for customers, it has also resulted in commoditization of customer interactions. The outcome is boxed products that lack human touch leading to unmet customer needs.
- This paper highlights the amalgamation of advanced information management along with algorithmic approach of fluidic offer management that can help mimic human like interactions to enhance personalization in a digitalized environment
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Introduction
Prior to the dot com boom, circa 2000, business transactions (reservations) with the customers and businesses within hospitality industry were primarily facilitated by agents over communication channels such as phone, fax, telex and in a few cases by email. Digitization existed primarily as a register for reservations and catalog of products and inventory (rooms). The agent representing the hotel asked questions and accordingly offered the right product/product mix based on preferences and budget of the customer. However, this was a lengthy process and was dependent on manpower with the right soft skills. With an exponential increase of hospitality ancillaries, it is impractical to depend on humans to effectively bundle and present the right set of offerings for the customers.
Over the years, the hospitality industry has embraced automation offered by direct channels such as hotel website and mobile; and indirect channels such as global distribution system (GDS) and online travel agencies (OTAs). This has enabled brands to improve their reach and expand to new markets and customer segments. Close to 72% business generated in the hospitality industry is from indirect channels.1 Contribution of human voice channels for the room reservation processes has dropped to less than 10%.2 Therefore, in the era of digitalization, hoteliers are feeling an acute need to move away from boxed products to fluidic offers which curate unique product offerings based on customer requirements.
Driving
Driving personalization in the hospitality industry for improved revenues and CX
The human element is central to the functioning of the hospitality industry right from the booking process to check out. However, digitalization has severely commoditized the industry and reduced it to a mere showcase of price-comparative products , resulting in unmet customer needs. The hospitality industry needs to find a way to reintroduce the human touch even as it looks at improving its global reach and market share. Reservations is the beginning of the customer journey and an improved customer experience at this point will ensure better sales. This paper highlights an algorithmic approach for personalizing product offerings during reservations. With this, hotels can enable meaningful customer interactions resulting in better conversion rates and improved customer experience.
Bringing Back the Human Touch
As we get ready for living in the post COVID-19 world, there is a pressing need to bring back the human touch in digitalized processes like reservations, by leveraging the learning capabilities of machines that can mimic human thinking and decision making. At present, most packages offered by hotels on their digital channels are largely similar-- comprising of specific room types with fixed ancillaries as add-on options. Knowing the customer pulse and offering him personalized offers can reduce the large cart abandonment seen on hotel websites at close to 84.63%.3 Whereas, bundling products unique to customers’ requirements and propensity to buy will enhance the conversion rate on owned digital channels thereby bringing in a better wallet share for hotels in comparison to the OTAs. Lessons can be learned from a recent research that states a vast majority of customers, at 86% are known to make a purchase when travel and leisure brands offer personalized experiences on their websites.4
Hospitality e-commerce must adopt from the retail industry, its ways to influences online buying decisions. Establishing personalized, fluidic offers on products and services starts at the beginning of the customer journey. A pragmatic approach to imbibe changing customer preferences, expanded global footprint and a new generation’s outlook towards spending and utilization of products is a growing need. Even the marketing campaigns need to go beyond past statistical approach to focus on seasonal or local influences. Leveraging machine learning and advanced analytics can play a vital role to transform customer experience and position appropriate offers. It is the corner stone to drive meaningful customer interactions, better sales conversions and ancillary revenues leading to greater customer retention.
Driving Personalized Interactions
For meaningful interactions, it is essential to understand the customer context and preferences. This will in-turn help drive a personalized travel and stay experience. Lets understand this with an example of a working couple who have two kids and are planning a family vacation. The couple intends to pursue their hobbies during the break, whereas, the children have a different set of expectations from the getaway. To meet the entire family’s expectations, the hotel e-commerce platform needs to come up with a single holiday package that ensures:
- Dynamically bring together ancillary elements specifically targeted at each member of the family
- Provide an enticing price
- And successfully convert this prospect into a sale
Below are key pointers that the industry can explore to drive unique contextual experience for such a scenario and improve its sales conversions:
1) Unlock the power of data to fuel meaningful interactions:
- Derive trends/patterns associated with targeted customer segments: Specific analytics derived from slices of data spanning multiple years can unlock trends that are attributed to various generations such as Generation X, millennials, and Generation Z. This data could also highlight trends that are related to a grouping attribute such as customers age, gender, geographic location or even seasons. Learning models will need to be updated based on frequency of change in market dynamics.
- Derive accurate preferences for new and transient customers: Analyzing and identifying trends from data of similar customer segments can be utilized to derive precise preferences for new customers. Algorithms can be designed to process historical data of services/ product consumption during customer stay, introspect customer loyalty data for precise bundling of products on offer and infuse it with social media analytics for accurate recommendations.
2) Develop a rich and versatile product catalog: This serves as a repository of available products and services. A versatile engine underpinned by robust structure, hierarchy and attributes will enable sophisticated search, contextualization and bundling capabilities. This can be used along with deep learning and machine learning to process catalog rules.
3) Build algorithmic interventions to address the needs of new and existing customers: It is crucial to identify first time/ one-time customers and repeat customers by getting data attributes about the customer. This can help create real-me contextual suggestions to build packages based on their preferences and propensity to buy. Algorithmic models should enable such identification and mapping of packages based on learning trends of similar customers with specific data attributes.
4) Incorporate context mining and behavioral predictions to develop effecttive bundles:
- Business rules aid in bundling ancillaries: The core product for hospitality is a room. There is a necessity to build business rules for additional products or services sold with the core product on digital channels to ensure effective product bundling and to avoid bundling of contradictory products together. For instance, movie on demand cannot be purchased without ultra-high-speed wifi; or a next to elevator component cannot be purchased along with next to fire exit component.
- Present bundles with high buying propensity: Hospitality can take a cue from the retail industry on how product elements are presented to the customers. Enlisting many choices of products or packages may complicate the decision-making process. Therefore, based on the buying propensity, hoteliers can present the top few packages with a concrete value proposition to drive quicker decision making.
- Effective campaigns for incremental utility: The above approach could be utilized to run campaigns by leveraging historical data from past campaigns. This enables marketing teams to understand the acceptability of campaign with customers and develop a scientific approach towards launching targeted campaigns with bundled products to a specific group of customers.
- Close loop feedback with revenue management and pricing: There needs to be a handshake with the revenue management system to learn from past interactions and propose a right price point. This can eventually develop into a dynamic pricing system.
5) Implement a balanced human-machine interplay: Enabling business to define, control and evolve the system of behavior, including defining evolution of meta data management and setting context of business priorities, should ensure machines work in tandem with business priorities.
6) High performance architecture is an imperative: Every unique e-commerce request triggers multiple complex algorithms. Delivering a seamless response at a fraction of a second is an imperative, which requires high performance computing to be an essential element of such an engine. Delivering the right combination of an offer from a multitude of possible combinations, enables an exponential customer experience on a digital platform. The design should also address business scalability without needing frequent changes to the IT landscape (see Figure 1).
An architectural approach to fluidic bundling
A combination of the above enables hospitality business to move away from boxed combination of products and fulfil unmet needs by enabling fluidic offers unique to every customer’s needs.
Figure 1
Levers to build a fluidic offer engine
Figure 1
Conclusion
With the tech-savvy, always connected Gen Z coming of age, the demand for personalized products and experiences will increase. This has led to businesses exploring options that can provide better customer engagement and value to its stakeholders. For the hospitality industry, the market standard commercial off-the-shelf (COTS) products which drive customer personalization by processing large set of data based on linear groups of customers have limitations. These products are unable to cater to their diverse needs and customer personas.
To be future-ready, hospitality players need to provide a seamless, differentiated, and memorable experience. They need to ensure their customers are provided with personalized services from the planning stage to booking and through the stay. With advancement in technology, machines
can augment human thinking. Ushering an interplay between machines (AI) and human, will enable hoteliers with a long-term objective of understanding their customers’ unique requirements in real time and offer relevant products. Meaningful customer interactions will aid in building brand confidence and differentiation in a competitive marketplace.
