The travel industry, worth an estimated $9.5 trillion in 2023, has long been a prime target for tech giants like Google and Meta, which are looking to leverage AI to grab a bigger share of the lucrative travel market.
AI has the potential to have a major impact on how consumers research and plan their trips, moving them away from traditional search platforms and reshaping the entire user journey.
In this article, we explore the rise of AI assistants in the travel industry, their capabilities, and how they may impact travel brands’ visibility and marketing strategies going forward.
Historically, Google has tried to capture as much of the travel market as possible through SERP features such as hotel and flight search and booking capabilities.
AI Overviews (formerly SGE) also has a focus on the travel industry, and Google featured it in The Keyword Blog in March 2024.
While the release of our AI Overview has gotten off to a rocky start (to say the least), we need to recognize that AI is a big part of the future of Google Search and other parts of the Google product ecosystem.
While there’s been a lot of attention on the impact of AI Overview on website traffic, I think the bigger question is how Google and Meta’s AI products will change the way users discover and research online.
Meta AI is currently in beta in some countries, but based on testing, it has the potential to rival Google's AI offerings.
Meta also plans to launch the product on Facebook, Messenger, WhatsApp and Instagram, instantly increasing market penetration to 2 billion monthly active users who have access to Meta AI.
On the Meta AI website, the intention is for Meta AI to play an active role in group chats (across different platforms) to help people plan and prepare itineraries for outings, meetings, travel etc. However, because it's a group experience, rather than searching on Google and sending links in chat, the group can be involved in the discovery process.
Why is this important?
We’ve speculated and explored how the AI ​​overview will impact traffic, but Meta AI is likely to move users away from their old Google search and keep them within the Meta ecosystem.
By the time users eventually leave the Meta ecosystem and migrate to Google, they may already be a long way down the road.
For example, if you interact with Gemini and ask it to show you “European vacations for families,” you'll see destination suggestions. If you continue the conversation and narrow your search to all-inclusive resorts for families in Greece, you'll see more suggestions.
In the past, without AI intervention, you might have clicked on the number one ranked Tripadvisor link, a list of the top 10 resorts matching your query.
Beyond the fact that this is now a zero-click search, there are wider implications that TripAdvisor's top 10 lists will differ from the recommendations provided by Google's AI.
This means that the user journey has already shifted to a different channel, and resorts and destinations should be able to stand out by investing in their TripAdvisor reviews and profiles, gaining awareness and traction through brand touch points.
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Understand how users search and stack up queries
Users rarely go to Google to perform a single search, but are more likely to be query stacking.
Query stacking is the process of refining a search query in multiple iterations to arrive at the information a user seeks.
Often, you'll start with a broad, vague search and then refine and specify your search terms based on the initial results.
Successively more specific queries leverage the search engine's understanding of context and intent to deliver more relevant results, helping users narrow down exactly what they need.
Broad search is a problem Google has been tackling for years: during its 20th anniversary week in 2018, the company demonstrated how it was using neural matching and synonyms to address 30% of queries (at the time) and improve users' search journeys.
Within the travel industry, this journey is already becoming more diverse, with travel consumers following and being influenced by travel influencers on platforms like TikTok, and then using the platform to consume more content about the destinations they are researching.
The impact on users will be greater than ever before and will be long-lasting – the impact of Game of Thrones on tourism in Northern Ireland is a good example.
Historically, television series were broadcast and then housed on VHS box sets, but in modern times, they live on through streaming services, with extensions being commissioned.
Understand the potential impact of AI on travel user behavior
The impact of AI on the user journey will vary depending on the type of user, which will change and evolve depending on the purpose for which they perform a search.
At the highest level, we categorize these user types as learners, shoppers, participants, and purchasers.
For users researching their next outing:
Learners are users at the beginning of their journey. They are users who have done a broad and relatively vague information search and are trying to narrow down their options. AI can take this stage of the journey in a different direction than previous search results. Participants are users who are trying to participate and read user-generated content and reviews on known and reputable platforms. AI has minimal impact here, but it can summarize content and surface different sources for users. Shopper and Purchaser user types are much further down the funnel in the travel consumer context, and as consumers are shopping around for the best deal before they buy, many of these user needs are simply met directly on the website.
Measuring and monitoring the impact of AI in the travel research process
While we can only infer the impact of users remaining within the Meta AI ecosystem over time by observing the number of clicks and impressions for stable search term rankings, there are more reliable ways to measure the impact of AI Overview on user behavior and performance.
You can view these trends in Google Search Console, but we don't plan to distinguish AI Summary clicks and impressions from “regular” clicks and impressions.
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