Artificial Intelligence has certainly been a buzzword in the attractions industry for some time now. But what do we mean by AI, in the context of the leisure and entertainment sector, and how can attractions operators use it to enhance their communication, improve their business operations and ultimately grow their business?
There is a tendency to be sceptical about the rise of AI in our everyday lives, particularly when it comes to topics like chatbots, algorithmic decision making and data gathering. In this article, with the help of Convious, a leading eCommerce platform for the leisure industry, we will aim to counter some of the myths and misconceptions around AI and outline the opportunities. Read on to discover how AI can boost revenue opportunities, improve the visitor experience, and streamline operations.
It’s not all self-driving cars and fears of robots taking over the world – AI-powered solutions can save operators time and money across different business functions to increase personalisation and guarantee fast response times. This kind of technology can also help attractions to identify opportunities to grow, using data-driven factual insights.
A career in tech
Sander Nagtegaal is chief product officer at Convious and CEO/co-founder at Unless. Having worked in the internet industry since the 1990s and piloted several tech start-ups, he has an in-depth knowledge of the world of machine learning and AI. He joined Convious in 2022 and used this experience to steer major developments in the company’s processes.
His latest project, which he started in 2017, is Unless, which offers a no-code platform to create, launch and test personalised widgets in any existing website or dashboard. This platform allows users to drag and drop a layer of extra functionality in other websites, regardless of their original technology and without distracting their developers.
“The Unless platform is what brought me to work with Convious,” he explains. “For businesses in the experience economy, Convious provides a full range of connected, drop-in modules that provide for the entire visitor journey – so our partners can focus on delighting their visitors, without worrying about anything else. The Unless technology supports this vision very nicely. In fact, it is one of the most compelling use cases that I have seen so far. The partnership between our companies is really strong.”
AI in the attractions industry: the importance of personalisation
The use of artificial intelligence in the visitor attractions industry is a direct result of the popularity of AI in several other industries; it is a logical consequence of its rise in eCommerce in general. However, much of its growth in this sector is also powered by the trend for personalisation.
“In eCommerce, the expectations of customers are already more leaned towards a personalised experience than a one-size-fits-all approach,” explains Nagtegaal. “Not only do tailored storylines convert better, but the customers also expect nothing less, as it improves their experience a lot. So, personalisation has been ingrained in the user experience now. It’s a commodity.”
Personalised marketing is a technique that uses data to engage with both current and potential consumers, in order to provide an enhanced marketing experience. Essentially, it means that businesses are identifying and catering to the preferences of their individual customers. For example, a theme park might use data to identify which of its visitors frequently dine on-site, and then send them offers accordingly.
Making the guest experience better
The driver behind it, in terms of the attractions industry, is that you make the visitor experience easier. When you show them the information or offers that they want, without having to search, it’s a more streamlined experience. This makes them happy and so, in turn, leads to more return visits.
Companies with effective personalisation strategies routinely “drive 5 to 15 percent increases in revenue and 10 to 30 percent increases in marketing-spend efficiency,” according to McKinsey & Company.
Without personalisation, real people hugely outperform websites when it comes to selling things, explaining things, or even keeping people’s attention. For instance, if you talk to anyone in a bar, it is easy to keep them engaged for about 20 minutes or so. But on a website, you have about ten seconds to keep their attention.
“The reason is that humans can adapt their storyline to their audience in real-time: we are the masters of personalisation. But with the “hyper-personalisation” we have available today, websites can do something similar. So, AI-powered personalisation is not only better in terms of user-friendly experience (and yes, that can be in the transactional part of the customer journey, as well as in the attractions themselves), but also it is much better for doing business.”
Personalisation evolves
In recent years, personalisation has gone from being a ‘nice-to-have’ to a must-have. McKinsey & Company research reveals that today’s consumers demand personalised experiences while making purchases online. According to the Next in Personalization 2021 Report, 71% of consumers expect personalised experiences when they shop online, and 68% of consumers become frustrated when they don’t get this degree of individualised service.
Initially, personalisation didn’t go much beyond the “people who bought this, also bought that” model, popularised by Amazon. Then, around ten years ago, segmented A/B testing emerged, meaning that it was possible to prove what worked for which group. Big companies like Netflix then began to use machine learning models to do things like showing personalised artwork for movies and series, using A/B testing at scale to finetune the models.
“That was a game changer,” says Nagtegaal. “So, AI is really pushing personalisation to a new level.
“Ever since, eCommerce companies have been trailblazing this trend. And now, led by companies like Convious, the visitor attraction industry will follow. It will be a revolution, but maybe not the kind of revolution that you imagine: as customers expect a highly personalised, frictionless experience, the companies that can’t keep up will simply disappear. In that sense, it is probably better to call it an evolution – a rather spectacular one, though.”
And AI will be one of the main drivers behind it.
How does Convious use AI and machine learning to help attractions operators?
Convious primarily uses machine learning to create models that can predict how venue visitors behave. The difference between Artificial Intelligence and machine learning (ML) is that AI is a much wider concept. The term AI describes intelligent machines that can simulate human thinking and behaviour, from self-driving cars to OpenAI ChatGpt language models. Machine learning is a subset of that, and it allows machines to learn from data without being programmed explicitly.
For example, Convious uses this type of technology to power its dynamic pricing feature:
“Based on historical data of buying behaviour, versus contextual data like the day of the week or even the weather forecast, our machine learning algorithm will train a model. When visitors come to the online ticket shop of one of our partners, the shop will ask this model for the best price based on its training. The price will then fit the expectations of this partner best, given the context of the world around him – so, based on environmental factors.”
This leads to a better conversion for the operator, as well as mitigating peaks in visits. It can also help to make more accessible venues, in terms of pricing. Depending on the situation, tickets may be more affordable than at other times, allowing for a broader audience to enjoy the venue. One study found that dynamic pricing pleases guests and operators alike, boosting revenue while also allowing bargain-hunting visitors to feel like they have found a good deal.
Machine learning aids personalisation
In addition, the Convious platform offers several personalisation options that work based on the segmentation of online visitors into audiences. Audience segmentation is done with a combination of statistical methods and machine learning models.
“The result is that we group people by their respective traits and behaviours, which we can then use to show them tailored messaging and content, in emails, with mobile push notifications, or on the partner’s website. So, this even includes changing the copy of the existing partner’s website if that is part of the package. That all happens automatically, and it is different for each individual visitor. After all, you can be part of many audiences at the same time.”
The firm is also working on augmenting its crowd control systems with machine learning models to better predict visitor numbers and help with supply chain management improvements.
The myths and misconceptions: is AI dangerous?
There has been some negativity around the fact that AI is increasingly being used in our everyday lives. We’ve all been frustrated at a chatbot or wondered at just how much the content we see is governed by algorithms.
“I am not sure if it is a misconception to be worried about your privacy and data collection. There are a lot of examples of when something has gone wrong, and not just in the context of AI. Luckily, we have a lot of legislation in the EU, UK and now the US as well to safeguard this and to draw clear lines. At Convious, we value that highly and put in a lot of effort to follow these rules.”
“Also, for example in the case of our dynamic pricing algorithms, there are other laws regulating this. It is not allowed to offer different people different prices at the same time. So, when it comes to pricing, a dynamic algorithm should show the same price to people if they look at the website at the same moment within a single country. A price may be different a little bit later though if the weather changes or something else occurs. We stick to these laws.”
The risks
One of the main risks of AI (and machine learning) is that a model is as biased as the data that you feed it. For example, in 2016 Microsoft launched an AI Twitter chatbot, which it called an experiment in “conversational understanding”. It was fed with general Twitter conversations and taught to behave like a human. Within hours, it started tweeting racist and sexist replies to other users, sparking controversy before it was quickly taken down.
As a result, a new class of machine learning models was developed, primarily aimed at explaining the black-box reasoning of the original models.
“I think that chatbots are a different beast altogether,” adds Nagtegaal. “The most practical problem with chatbots is not that they aren’t human – the problem is that they can be super frustrating when they don’t understand you and give irrelevant answers. So, if you offer them, you must be sure that they are really good.
“Convious does not offer a chatbot. We will only do this when we know it will perform impeccably.”
The opportunities
AI by itself does not mean much. It’s just technology. But technology can help to implement things that make a big difference, like hyper-personalisation or dynamic pricing. Both may help to take the frustration out of the customer journey.
“It’s what we think about every day, and what is the core of the Convious vision: how can we help our partners to give their visitors a frictionless user experience? Like, if somebody sits on their couch on Thursday, and suddenly thinks about going to a park on the weekend – all the steps towards that goal we provide for and simplify. And of course, this will eventually translate into more profits for the parks.”
In short, as long as the technology providers operate in an ethically correct way, abiding by regulations, AI will simply make life better for both visitors and attractions operators.
This kind of technology can improve the visitor experience and therefore boost revenue. It can also help on the operations side; with machine learning, operators can anticipate trends to optimise supply, based on prior analysis of users’ purchasing behaviour and their assessment of the experience. Machine learning models are much better at this than humans.
AI even has the potential to help operators to identify areas where they can grow in the future. The amount of data that you can input is pretty much limitless, so the granularity also is, therefore, limitless. With machine learning, operators could see predictions not only for the total amount of visitors they can expect but also which areas will be the most popular.
“You can see trends very clearly, and that helps to prioritise efforts, not only in direct resource management but also in the development of extensions to existing attractions.”
AI in attractions: future trends to watch
Looking ahead, Nagtegaal says that the use of AI in the attractions industry is likely to expand greatly, from using AI-powered classification of incoming messages and pre-populating responses using language-based AI tools to the introduction of a new generation of virtual assistants with conversational skills that will leave today’s chatbots in the dust.
For attractions operators, crowd control is an area where AI can have a huge impact:
“More venues will be able to use technology like this, with cameras monitoring visitors and algorithms then managing dynamic resources to scale up and down in real-time, based on the number of people that the algorithm spots in different attractions – purely based on a video stream. The same goes for security aspects.”
He also says that AI will continue to revolutionise eCommerce, with language models changing the game for content marketers.
“Merchandising will change a lot, too,” he adds. “Dubbed “searchandising” by some, there will be a blend with personalised search capabilities and shopping, resulting in spot-on personalised offerings.
“Personalisation in the attractions themselves has endless opportunities. Based on what you know about a visitor – like previous visits or even real-time behavioural analysis of their current visit – could change the behaviour of the attraction itself entirely. Think about personalised gaming experiences or video stuff, you name it!”
In conclusion, AI will help to introduce a new kind of automation that focuses on enhancing the human customer experience – rather than just being efficient.
“I like to look at it as “technology growing up”. We are not there yet, but I expect a lot of changes in the industry in the next five years. After all, the attractions industry is all about making people happy. And to do that, you will need to empathise with them – which is exactly what AI does.”
