Enhancing Travel Experiences: The Role of Hyper-Personalization in Hospitality

Key takeaways:

  • Hyper-personalization remains relatively unexplored by travel and hospitality firms
  • Utilizing customer data can deliver new levels of service and experience
  • Integration of data, AI, analytics and automation is essential for success
  • Investment, assessment and expertise can help firms stand out in a competitive sector

Enhancing Travel Experiences: The Role of Hyper-Personalization in Hospitality

In practically every walk of life, consumers are increasingly expecting greater levels of personalization. Taken to its greatest extent, hyper-personalization is helping brands target customers on an individual level, to encourage loyalty and specific actions during the sales journey and beyond.

In the travel and hospitality industry, the potential of hyper-personalization has been widely recognized, but remains relatively unfulfilled compared to other consumer-facing industries. This blog explores how personalized marketing in hospitality can work in practice, and just how beneficial it can be in a competitive landscape.

What is Hyper-Personalization?

Hyper-personalization refers to the creation of the most customized, targeted, data-driven guest experiences, aimed at engaging individual users and consumers. It’s achieved through the combination of data, automation, analytical tools and automation, and the integrated use of these delivers the best results. Whereas standard personalization creates experiences based on previous customer interactions and data, hyper-personalization leverages real-time data to shape experiences as the customer interacts.Data-and-AI_banner_Service-page

Benefits of Hyper-Personalization

Before even considering hyper-personalization, businesses in the travel and hospitality sector are lagging behind with even standard personalization practices. According to Forrester, less than 40% of consumers rate companies in the sector highly for personalization.

This means moving towards hyper-personalization can deliver huge steps forward in a range of different areas, such as: 

  • Improved customer satisfaction: when guests and travelers receive hyper-personalized services – from preferred dining choices to their ideal room option – they feel highly valued and respected by the brand. This level of satisfaction encourages repeat custom, and supports a higher Net Promoter Score.
  • Stronger trust: brands that demonstrate a clear understanding of an individual’s preferences – and responsible use of personal data – will be more trusted in the long-term. This not only inspires loyalty, but also advocacy in customers that will share positive experiences with friends, family and co-workers.
  • Competitive advantage: standing out as a business that values its customers highly can be a key differentiator in the highly competitive travel and hospitality sector. Customers will always be more likely to book with a business that they know puts their expectations first.
  • Healthier revenue opportunities: building deeper connections with customers opens greater opportunities for targeted promotions, upselling and cross-selling, all of which can make a real difference to profitability. Maximizing the efficiency of marketing efforts can also help reduce costs without compromising results.

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When these benefits are realized, the importance of hyper-personalization can then be felt throughout the business as a whole, and enable:

  • Data-driven decision-making: the analytics and data involved in hyper-personalization can help foster a culture of data-driven decision-making, where guesswork is removed and businesses can work towards the future with confidence. That’s why, over 90% of businesses are already pursuing data initiatives.
  • Customizable payment solutions: having the capability to analyze spending patterns, transaction records and wider behavioral data allows payment solutions to be customized. Not only does this give customers flexibility, but it also maximizes the likelihood of bills being paid in a timely manner, which supports smoother cash flow. This is vital at a time when, according to McKinsey, more than 60% of American consumers are using at least two forms of digital payment.
  • Frictionless travel experiences: The Hilton Trends Report found that 56% of travelers search for options that will make their travel experiences easier. This can be supported by AI-powered personalized travel agents that can help craft trips and itineraries that perfectly suit customer preferences. By providing such seamless and tailored experiences, hotels can significantly increase their net promoter scores, as satisfied customers are more likely to recommend the brand to others.

Explore our blog post on: The importance of hyper-personalized user experience in eCommerce

Implementing Hyper-Personalization Tactics in Travel and Hospitality

There is so much that travel and hospitality firms can do with hyper-personalization, in no small part because of the huge volumes of data at their disposal. In many cases, it’s a lack of up-to-date and integrated solutions that have held them back, but with the right technology, areas that can be transformed include:

Icon1_Personalized pricing and offers Personalized pricing and offers:

Examples include United Airlines, who use machine learning to create personalized offers for seat upgrades, priority boarding and other services; and Hyatt Hotels, who boosted revenue by $40 million in six months by matching hotel suggestions and service offers to guest preferences and behavior.

Icon2_Pre-arrival surveys Pre-arrival surveys

Encouraging hotel guests to complete a survey before they arrive provides vital information on their preferences. This allows staff to make hyper-personalized preparations to the customer’s liking, such as room type, room temperature and even the firmness of the pillows.  

Icon3_Customized guest services and amenities Customized guest services and amenities

The first two points can come together enabling hotels to provide hyper-personalization, such as for services and amenities during a guest’s stay that they are most likely to be interested in.

Icon4_ AI-based Virtual Concierge AI-based Virtual Concierge

Applications on hardware within rooms or on guests’ mobile devices can connect them to personalized recommendations across dining, attractions, activities and other services. Furthermore, it delivers a high quality service far cheaper and at a far greater scale than a human concierge could manage.

Icon5_Geotargeted notifications Geotargeted notifications

Personalized notifications and information can be sent to guests’ mobile devices when they approach the hotel or other points of interest, including relevant discounts and offers.

Icon6_Surveys and feedback loops Surveys and feedback loops

Obtaining feedback and data from customers after their stay or trip serves two purposes – understanding the success of current hyper-personalization measures, and gaining insight on individual preferences that can be used the next time the customer books.

Icon7_Disruption management Disruption management

Using intuitive insights and real-time data streams to flag up problems as early as possible, and take decisive and personalized action to resolve any disruption or delays that customers face.

In Summary: How to Implement Hyper-Personalization in Your Marketing

It’s clear that hyper-personalization will be an increasingly important part of the future for almost every travel and hospitality business. Firms who aren’t getting it right will be left further and further behind by their competitors who are.

The key is to identify and work towards customers’ “Zone of Tolerance”, where they feel familiar and content with experiences that work seamlessly and are intuitive to their needs. From this foundation, firms can work towards the “Zone of Delight”, and develop experiences that stand-out from the crowd and live long in the memory.
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On a practical level, three things are needed to make this possible:

  • Investment in technology: deploying the right analytical tools, AI powered solutions and integrated platforms to make hyper-personalization efficient and effective.
  • Regular assessment and adaptation: continuous monitoring and improvement of hospitality technology to keep offerings competitive, and adapt to new customer and market trends.
  • Deep sector and technology expertise: seeking the support of a third party provider who not only understands what’s required from a technological perspective, but also understands the needs of travel and hospitality firms specifically.

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Exploring Data & AI’s Role in Enhancing HR Functions

Key Takeaways

  • Data and AI are full of potential for HR, but take-up is low so far
  • Data and AI can transform HR decision-making, onboarding and employee engagement
  • Challenges around ethical use of AI, data privacy and workforce buy-in need to be addressed
  • Now is the time to get on board, with more innovations in the pipeline

The demands on HR teams as part of successful modern businesses are perhaps bigger and more varied than they’ve ever been. A well-run HR function goes beyond employee processes and services, and incorporates training, workplace culture, employee wellbeing, and efforts around diversity and inclusion.

All this means that many HR teams are actively on the lookout for ways to increase efficiency, and artificial intelligence is making a real difference in that area.  The ability to use chatbots to automate employee-facing procedures, transform onboarding processes, and develop more engaging and immersive training programmes can all help HR take their operations to the next level.

While many organizations have started using AI for HR-related activities in the last year or so, SHRM has found that take-up is still only around 25%. As this blog will demonstrate, there are plenty of upsides for early adopters who get on board with the role of AI in HR now.

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Into the Future: How Agentic AI is Changing the Game in 2025

Key Takeaways

  • Agentic AI is steadily progressing towards providing more versatile agents with cross-sector and collaborative capabilities.
  • GenAI will persist in Agentic AI workflows, particularly where creative output is required.
  • RegTech could highly influence the direction of Agentic AI innovations pertaining to data cloud solutions, reasoning engines and connectors.

The global AI market continues to grow at a rapid pace. According to Hostinger, a compound annual growth rate of 28.46% is expected from now through to the end of the decade. And while generative AI has grabbed most of the headlines, there are plenty of other types of AI that can serve businesses well in the years to come.

One is agentic AI, which takes the principles of generative AI to the next level, expanding the involvement that AI can take in day-to-day work and reducing the amount of human input required to get the most out of the technology. This blog explores agentic AI, what it means for your organization, and how best to apply it now and in the future.


What is Agentic AI?

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Good agentic AI solutions can make their own judgment calls, make decisions in context, and adjust objectives and workflows in real time as circumstances and situations evolve. They can move between different tasks and applications in a logical order to maximize the efficiency of processes, and can also understand and execute instructions given by humans in natural language as and when required. They can also autonomously navigate complex decision trees, and self-improve through reinforcement learning and continuous feedback looks.

The ability to take the bigger picture into account is the key area in which agentic AI differs from conventional AI platforms. Being able to leverage huge datasets, major computing power and large language models (LLMs) mean that agentic AI can plan out what it needs to do, then go and do it.


The Evolution of Agentic AI Systems

Agentic AI can be seen as the logical next step from the conversational AI platforms that have become commonplace in recent years. What used to be relatively simple chatbots, gradually expanded in functionality to handle requests and processes based on natural language and autonomous driven decision-making.

Agentic models take this further by moving beyond ‘request and response’ processes and towards more complex systems that are based around actions and workflows, such as Large Action Models (LAMs). These differ from AI copilots in that they have much more autonomy and independence to make their own decisions, using their own understanding to make choices without needing input from human endeavor.


What Are the Building Blocks of Agentic AI?

An agentic AI architecture is typically made up of three core components, each of which makes its own valuable contribution:

Perception: the integration of data from many different sources, in order to gain the most detailed understanding of the situation possible. This can include text, still images, video, audio, and even information from sensors gained from IoT devices.

Cognition: the processing of the information gained at the perception stage, in order to make the right decisions for workflows and processes. This is achieved through the use of deep learning models, and leveraging the results of previous experiences.

Action: using the cognitive decisions made to execute complex tasks and workflows, control algorithms to ensure precision, create feedback loops that can make dynamic adjustments as required, and even robotics where the actions required are physical rather than digital.

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One of the reasons that agentic AI is so full of potential is the sheer breadth and diversity of the data stores it can make use of. This can include unstructured data, structured data, embeddings and vector stores, and even knowledge graphs. The fact that agentic AI can operate in both digital and physical contexts also expands the possibilities of real-world use cases for the technology.


Pros and Cons of Agentic AI

If deployed correctly and in the right places, the scale of the benefits that agentic AI can deliver is enormous, including:


01_efficiency Efficiency:

Being able to not only process vast amounts of data, but also make contextual decisions faster than humans, can make everyday workflows much quicker, more efficient and more accurate.

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Transformative Effects of Artificial Intelligence on Financial Services

Introduction

According to a global survey conducted by McKinsey in 2021, 56% of financial institutions have embraced artificial intelligence (AI) in various operational aspects. This survey has shown a profound evolution within the industry, where AI is increasingly recognized as a catalyst for innovation and efficiency.

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Unleashing the Power of AI: Best Practices for Enterprise Strategy and Deployment

Introduction

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Discover the power of AI in supply chain & logistics

 

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AI in the workplace: Is there a place for humans and technology?

 

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AI-Driven Insights for Retail Success: A Data-Driven Approach

 

Continue reading “AI-Driven Insights for Retail Success: A Data-Driven Approach”

The importance of hyper-personalized user experience in eCommerce

 

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Risk vs Reward: AI development for payments

An increasingly digitized world means that the way payments are made has become increasingly digitized, too. Digital payments are delivering new levels of convenience and assurance for billions of people all over the world, whether it’s speed of transaction, financial security, adaptation to new consumer trends, or access to personalized finance services.

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