It’s no secret that personalisation is vital for building lasting customer relationships and nurturing brand loyalty. AI holds the key to creating and delivering successful personalised engagement, and travel and airline businesses are keen to adopt this technology in their customer-facing applications.
The reality, however, is that few are currently able to scale AI across their organisation. According to industry research, published in Amperity’s State of AI for Hotels & Airlines, AI adoption is widespread across the sector, but applications remain experimental. Just 12.5% of companies say they are ready to scale their use cases.
The challenge isn’t ambition. Nearly all (96%) businesses in the sector are planning to maintain or increase AI spending over the next 12 months. The problem lies in two major barriers that prevent AI from scaling effectively: a lack of technical expertise within teams and low confidence in the data that AI tools rely upon, due to fragmented or unreliable customer information.
How to reduce reliance on technical teams
Keeping pace with rising consumer expectations means tailoring customer engagement and presenting meaningful, real-time offers based on individual preferences. Although travel businesses know that AI is going to help them achieve this true personalisation, at scale, only 35% currently use AI in guest experiences.
One reason for this is the inability of non-technical teams to independently access data they need, and act on the information provided. AI usage among travel and airline brands remains concentrated in marketing, customer support and sales. But less than a third of professionals in these teams say they can manage customer data without the support of their IT department. This is delaying, and in many cases denying, teams the ability to tailor customer communications.
What teams need are intuitive tools, empowered by GenAI, that simplify the process of accessing customer insight. These platforms allow non-technical people to ask questions using natural language and discover such things as: what their most valuable customers purchase most often, what form of content they are most likely to engage with and on which channels they are doing this.
AI training is still an important consideration for all business users, who need to understand how AI can add value, where its limitations lie and what safeguards should be put in place to ensure responsible use. But these GenAI capabilities are now helping teams to access crucial intelligence quickly and apply this to customer engagements at scale.
How to build confidence in customer data
Accessing data is one thing, but having confidence in that information is another. This is an area where travel companies struggle. Less than a quarter claim to be very confident in their ability to understand and act on customer data.
This is often because data is separated and siloed across different systems and channels. More than half of businesses (58%) report that their customer data is fragmented or incomplete. This can impair visibility, lead to inaccurate reporting and increase the risk of human error, while also adding IT costs. It also increases the chances that duplicate customer profiles will be created across those different channels.
Consumers commonly engage with travel brands across several touch points including email, mobile, apps and in-store. They will also use various identifiers, such as abbreviated names, alternative email addresses, etc., when they do so. Companies need to deploy AI tools that can unify this data and stitch together information coming from different channels. If they don’t, there is the real possibility that they will end up sending conflicting or irrelevant communications to the same person. The consequences of this can be damaging as it risks annoying and alienating customers.
Building a solid customer data foundation
To enable fast and accurate omnichannel communications, it’s vital for companies to have a customer data platform (CDP) that is enabled by identity resolution. To build high levels of confidence in the operational identities required for personalisation and broader marketing audience targeting, companies will need to blend deterministic and probabilistic matching strategies.
The research shows, however, that just 18% of travel businesses have this identity resolution technology in place. This is preventing companies from accurately viewing booking histories, identifying behaviour patterns and unlocking potential of AI for the tailored engagements necessary for building brand loyalty and increasing the lifetime value of a customer.
The evidence shows that organisations with a CDP are much better placed to ensure customer data is ready for use in marketing or analytics. The latest generation of CDPs will automatically consolidate data across various communication channels, detect and resolve identity issues and provide travel businesses with a true, 360 degree profile of each customer, based on all interactions across each channel.
These platforms are also enabling businesses to advance their AI deployments. More than half (54%) of businesses with a CDP report daily use of AI – this compares to 28% for those without. Half of CDP-enabled businesses use AI in guest-facing deployments, compared to less than a fifth (19%) of those without. Businesses are also five times more likely to have adopted AI across business units, when they have a CDP.
Preparing for an Agentic AI era
Next generation CDPs are also helping companies prepare for another major trend reshaping customer data management – the rise of agentic AI. Agents are already capable of observing behaviour, interpreting what it means and taking action autonomously.
For example, imagine a situation where a flight has been delayed or cancelled. In this scenario, a combination of agents can now work together to provide customers with a solution. In an instant, one can spot the problem, another will find alternate solutions, while a third will send the best options to the customer. The customer doesn’t need to wait – they simply receive a notification in real-time. Some human orchestration is still required and guardrails are important to ensure communications hit the mark. Most important to note, however, is that it only works if those agents have access to accurate data.
The travel sector is clearly at an inflection point on its road to full AI adoption. It’s moving from pilot projects and early stage experimentations to broader deployments and scaled execution. Success in customer facing applications, however, will depend on an organisation’s ability to provide non-technical teams with access to high quality, unified customer profiles.
Modern CDPs help businesses to make faster, smarter decisions that will help to drive growth. With these solid data foundations in place, businesses can deploy and scale AI-enabled customer facing applications more readily. This is the key to creating meaningful engagements that build brand loyalty, drive up the lifetime value of a customer and, ultimately, give businesses the competitive edge.
