Digital Strategies for Attractions in 2018

In 2016 the UK soared past Mexico and Germany to become the 6th most visited tourist destination on the planet. Competition has never been fiercer among thousands of historic sites and visitor centres across the country to tap into the growing market of domestic and international visitors.

While national theme parks have always benefited from economies of scale in marketing from newspapers to cereal boxes, smaller less established venues have often had to be more creative in their outreach initiatives. For such attractions, the rise of digital media has been indispensable as a route to market.

Pictured: available offers could be a prerequisite or the last push that leads consumers to visit an attraction.

Evolving over the years from text to photo to virtual reality, digital media has continued to offer innovative means of engaging with an audience. In a 2014 report into the effect of high-quality listings on consumer perceptions, Google found that on average those sites which offered ‘rich’ media listings generated as much as twice the interest as those without.

As we enter 2018, some of the biggest names in tech are now primed to escort us to a new age of experiential marketing. Samsung, Google, Facebook, Playstation and HTC each have their own virtual reality headsets, with Apple rumoured for a 2018 announcement, and there is no shortage of content with bloggers, advertisers and TV shows keen to explore 360 video as a new medium.

Looking to the future, Mark Zuckerberg is aiming for 1 billion users of Facebook’s Oculus, with the intention to create a full virtual reality for users to experience concerts and galleries from the comfort of their own homes. This is all part of his eventual ambition to create an augmented reality where users can share in simulated experiences.

The Cutter & Cutter gallery in L.A has a virtual tour online, which includes exhibit information.

As a more immediate stepping stone, Google has been building a network of thousands of media producers to accelerate the introduction of their virtual tours, an extension of street view. With notable adopters such as English Heritage and National Trust in 2017, virtual tours are poised to help attractions turn interest into excitement as a highly engaging means of conversion.

Such introductions of new technology have a two-fold impact on the way we consume rich information. On the top-side, early adopters can benefit from a first-mover advantage, gaining widespread recognition over their competitors, new technological shifts are always driven by a small number of facilitators and an expanding audience


In addition to technological driven changes, changes in social attitudes have also lead to the emergence of new platforms to promote great experiences. Confidence in online reviews has continued to increase in recent years, with 19% of respondents reporting that they always trust online reviews, and a further 45% having confidence where reviews are corroborated, up from 8% and 40% respectively in 2015.

High numbers of positive visitor reviews indicate a great user experience and demonstrates the venue is reputable and trustworthy.

This increasing reliance and trust is immediately apparent when looking at Trip Advisor’s growth rate. In 2006, Trip Advisor had around 10 million total venue reviews, of which around 34,000 venues were visitor attractions. Ten years and one smartphone boom later, there are now 760,000 visitor attractions listed and 465 million total reviews, with more than 20% year on year growth. This meteoric rise is symptomatic of an increasing reliance on technology to help consumers research and book new experiences.

A similar trend can be seen in the use of voucher codes. Whereas coupons for visitor attractions were once in the form of wrappers and newspaper cut-outs, savvy consumers now scour the web to decide between similar experiences, or reduce the costs of those they would prefer. On average, searches for coupons in the UK have increased 38% year on year for the past 10 years, with search volumes now over 20 times in 2017 what they were in 2007.

What we have and are continuing to see is a veritable explosion in routes to market. Though the mobile boom has passed us, our consumers are still learning and trusting in new methods to plan and research days out. The use of online booking facilities, for example has risen from 10% of museums in 2010, to nearly 30% today.

The sum of these shifts means that Museums and attractions now more than ever must have their finger on the pulse of digital media trends. With each surge in a platforms’ popularity comes a fresh new audience to market to, and the more engaging the content, the more likely this can be translated to footfall from excited new visitors, each keen to share their experiences.




Surfing the 6th Wave

Most of us will have been happy this past week to see rising pressure from Elon Musk and others to the UN to  ensure that we never make Terminator a reality by weaponising artificial intelligence. Personally, If Microsoft’s Twitter bot has had any impact I think we should keep it away from the internet too!

Have no doubt, robots are already here. In 1996, Deep Blue was able to beat a grandmaster chess champion by thinking further ahead than could be possible from a human. Just last year, Google’s Alpha Go beat the world champion at Go. The reason behind the 20 year gap comes down to Moore’s law and a little bit of science fiction.


Moore’s Law

In 1965, Gordon Moore predicted that computing power would continue to increase two-fold roughly every two years. Since that point it has proven its accuracy. A clear example can be found in memory cards which have rapidly progressed from Kilobytes to Gigabytes over the last 20 years.

In chess, there can be an average of 35 possible moves per turn, in Go this increases to around 250. This means in contrast, thinking 5 moves ahead would take over 18,000 times more processing power for Go than for Chess. At 20 moves, this increases to nearly 120 Quadrillion times. This meant that to have any kind of foresight would take massive amounts of computational power, but even with Moore’s law, the same Brute-force method used for chess would be unattainable in Go for decades.


A little bit of Sci-Fi

Aside from exponential computing power, we have also started to use that computing power to develop machine learning algorithms. By setting objectives for programs, we are essentially able to write programs that write themselves. For Alpha Go, this meant playing itself to narrow down it’s options to the most appropriate moves in each situation – in effect, it programmed itself with the required experience to beat grandmasters.

This is just one example, Google has been training their machine learning algorithms to deal with a range of scenarios based on set parameters. This objective rather than hard-coded approach to robotics means that the applications are limitless. Combine this with the development of neural networks and soon we will be looking at robots which can identify their environments and act accordingly, acting in an office as self-driving cars do on the road.



In terms of real world applications, Boston Dynamics is as close as they come. Their quadrupedal robots have proven themselves durable enough to work in the field capable of overcoming both rough terrain and a swift boot to the side. More recent developments are capable of lifting and jumping unaided while balancing on two wheels.

Other developments within robotics have seen robots which can work as a hive-mind to solve problems, spider-bots which can learn to walk again after having limbs disabled and robots which can demonstrate “hand-eye” co-ordination superior to humans.


What’s Next?

Broad technological developments in this manner have always generated a wave of innovation across the board. The economist Nikolai Kondratieff recognised similar trends with the inventions of hydro power, steam and then electricity.

Schumpeter later discovered that these innovation shifts were actually increasing in frequency. Arguably as each wave precipitated the development of the next through increases in idea transmission and resources.

Industrial revolutions have always displaced labour as soon it has become economical to do so. Windmills replaced human power; looms replaced human dexterity; cars replaced Horses; electronics displaced elevator operators and vast swathes of clerical staff have been made redundant by data processing software.

This next development then, the start of technology capable of making rational judgement, surely spells the end for work as we know it. As with all technologies, the more it is used, the better it is funded, the greater the growth and the more applications will open up. As more variables can be understood, quantified and compensated for, artificial intelligence and its infinite simulations of logic may yet prove to surpass our own abilities.

How long then until a machine is capable of picking and packing an order in a warehouse scenario? How far are we really from completely automated marketing, which knows more about our habits and preferences than would be economical for a salesperson to know? How far are we from a machine that can supervise other machines?



It is certain that the next few decades will foresee drastic shifts in how we work. The allocation not just of resources but of human labour will surely pose the next big questions for economists of the future. It is likely that social skills will prove the last hurdle for machine learning as we emerge from the uncanny valley; until then, it can’t hurt to know how likely you are to be replaced in the next 20 years.