Multimodal AI and Pricing
Multimodal AI integrates and processes multiple forms of data, such as text, images, audio, and video. By leveraging the combined power of these diverse data types, multimodal AI can enhance user experience, streamline operations, and personalise services in ways that were previously unimaginable. ChatGPT 4.0, for example, is multimodal, whereas 3.5 was purely text-based.
Interactive tours are one area where this technology may come to the fore. Compelling and interactive virtual tours of hotel properties could be created by combining visual data from images and videos with textual and auditory information. Couple this with augmented reality and AI algorithms that can analyse user data in real time, and you can start to see how individual, personalised tours could be generated on the fly.
At the Arabian Travel Market conference in Dubai recently, Digital Tourism Think Tank had a wall asking people to put their predicted travel headlines for the future. One said that “99% of people would rely on AI to design their travel itinerary by 2030, " which sounds like a valid prediction. Of course, that itinerary could include activities on or off-property and, coupled with marketing automation, could handle all the associated bookings as well. All of this could be offered with real-time language translation capabilities through AI. Will this capability replace personal butlers in high-end luxury resorts though? Probably not, as the personal touch still counts for a lot, although we also envisage multimodal AI chatbots and virtual assistants maturing further.
Nevertheless, we expect to see more tailored recommendations, not just in terms of customised offers but the whole experience. Predictive modelling built from Multimodal AI inputs could, for example, predict which amenities will be most prevalent during a particular season, allowing the hotel to offer relevant promotions.
Additionally, the next evolution of AI-powered pricing involving hyper-precision pricing could take attribution selling to the next level. Hyper-precision pricing would leverage detailed data analytics and machine learning to set prices at a granular level. AI could analyse an extensive array of variables, including individual booking behaviours, real-time local events, weather conditions, and even social media trends, to determine the optimal price for each room in real-time. Subsequently, AI's ability to forecast demand will become even more accurate and nuanced. Future AI-powered pricing systems could incorporate advanced predictive analytics or econometric modelling, considering factors like historical booking data, economic indicators, flight patterns, and even local business activities. By predicting demand more accurately, hotels could optimise their pricing strategies well in advance, ensuring maximum occupancy and revenue even during fluctuating market conditions.
And, of course, integrating AI into the Revenue Management System means that pricing could also be optimised for ancillary revenue streams, such as activities, spa, and dining. AI could analyse guest spending patterns and preferences and create bundled offers and cross-sell opportunities, thereby maximising total revenue per guest.
It is not a stretch then to think about personalised pricing models where AI could tailor prices to individual customers based on their booking history, loyalty status, and personal preferences. For instance, a frequent business traveller could be targeted with special rates and offers that differ from those given to a family planning a vacation. Similarly, context-aware pricing could be achieved by considering the broader context of each booking. For example, AI could adjust prices based on whether a guest is booking a special occasion, such as a wedding or a conference, by factoring in external conditions, like regional economic trends or local developments.
Integrating voice and visual search capabilities on hospitality websites also holds exciting prospects, particularly for hotel chains. Guests can describe what they are looking for or upload images, and multimodal AI can process these inputs to deliver highly relevant search results. For example, a guest might upload a photo of a room style they like or describe their ideal holiday verbally, and the AI will find the best matches available.
Extrapolating that to its natural conclusion, it is easy to see how traditional website navigation may be replaced using voice and visual searches. You can imagine Copilot’s appearing on many more hospitality websites in the future, especially as the functionality to build your own becomes natively incorporated into DXPs and CMS systems. Additionally, structured website pages could theoretically disappear with voice searches, in particular, building dynamic pages in real-time based on the closest match of content to the search instead of just returning results that the visitor clicks on to see further information.
Marketing Automation
As AI technology continues to evolve, its integration into marketing automation systems is becoming increasingly sophisticated, enabling businesses to achieve unprecedented efficiency and effectiveness. AI enables hyper-personalisation, for example, by analysing vast amounts of data, including consumer preferences, behaviours, and purchase histories. Although hyper-personalisation (personalising at the individual level as opposed to a segment) isn’t new (Amazon’s website is a good example), we can see that more marketing teams will get to grips with it. Achieving hyper-personalisation won’t just be the domain of the big boys anymore.
But for those who can’t get there, AI-driven marketing automation systems can perform advanced customer segmentation, dividing audiences into highly specific groups based on various criteria such as demographics, behaviour, and purchasing patterns. The more data collected over time, the better the learning models will become, ensuring marketing efforts remain relevant and effective.
And then, of course, is Generative AI (or GenAI). Many leading composable DXPs now contain automated content creation as Natural Language Processing (NLP) and Natural Language Generation (NLG) technologies enable AI to generate high-quality content efficiently.
Digital Marketing
As such, we only see GenAI tools becoming more prevalent and adding value within many different systems, not just DXPs—for example, real-time adjustments across marketing campaigns. AI algorithms could determine each campaign's most effective channels, timings, and messaging, maximising return on investment (ROI). AI could also conduct A/B testing at scale, rapidly identifying the best-performing variations and implementing changes dynamically.
In fact, Optimizely’s Web Experimentation platform is not that far off already. It conducts A/B testing at scale, can connect to multiple 3rd party systems including Contentsquare and Hotjar’s heatmap solution, and utilises AI for content suggestions and to automatically identify and optimise traffic distribution to significant variations. It is not that much of a stretch to think of the scenario where you could say here are a couple of variations of a campaign landing page; here are the heatmaps and scroll maps for these pages; here are some videos about how users are interacting with the pages as well, now go and automatically optimise the content and layout for each device type for maximum ROI over this period of time. On top of that, update my dynamic display banners with new imagery to match and create a new PPC ad group using some of the revised wording.
It is, therefore, evident that programmatic advertising will continue to evolve with AI, enabling more precise targeting and optimisation of ad campaigns. By analysing demographic, behavioural, and contextual data, AI will help hotels create highly targeted ads that resonate with specific audience segments. This will lead to more efficient ad spend and higher conversion rates. You can also see that AI will not only create tailored email content but also work out the audience segmentation and then determine the optimal send times for each segment, leading to higher open rates, engagement, and conversion.
From automated email campaigns and social media posts to personalised landing pages and product descriptions, it becomes evident how AI could create a wide range of content tailored to individual customer preferences and, again, using AI to analyse the results including user interactions, how campaigns could subsequently be dynamically restructured.
Conclusions
As AI and technology in general continue to evolve, hospitality businesses that embrace AI will be well-positioned to meet the demands of the modern traveller.
The future of multimodal AI in hospitality websites promises a transformative impact, enhancing user experiences, personalising services, streamlining operations, and improving marketing strategies. AI will also enable hotels to set hyper-precise rates, predict demand with greater accuracy, and personalise prices to individual guest profiles. By integrating AI into marketing automation, marketers who embrace its capabilities will deliver more personalised, efficient, and effective campaigns that resonate with their target audiences and drive success.
Include Agency is a widely respected Optimizely, Sitecore, and Uniform implementation partner with a wealth of experience in delivering bespoke solutions for leading hospitality brands. There are endless possibilities for enhancing guest experiences and operational efficiency using AI. If you are considering incorporating AI-based projects into your hotel website, we would love to be part of the discussion.
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