As this disruption continues and evolves, there will be many opportunities for innovators to exploit changing and growing media consumption. All the more so given that the structure and size of the incumbent marketplace inhibit the agility required to respond to change proceeding at such pace. From an investment perspective, the challenge is to identify the potential winners in this new landscape.
A new game for advertising
Take, for example, the advertising sector, where the big agencies once excelled at monetising television in a world where viewers had few channels to choose from and the industry had a good idea of who was watching what and when.
Today, by contrast, there are billions of potential viewing experiences to choose from – and for advertisers to book inventory against – courtesy of channels like YouTube.
Pinpointing the right opportunity for a given advertiser is no longer the preserve of instinctive and mercurial advertising executives – it requires a technology solution.
Entertainment AI is one business offering such a solution. Gresham House Ventures recently supported fundraising at the company to acquire GTChannel, a YouTube network of content creators focused on car enthusiasts. Using machine learning technologies that can pull in millions of hours of content and identify specific moments of interest within it, EAI’s aim is to provide advertisers with incredibly focused opportunities to market to an engaged audience.
Such advertisers will pay more for this highly targeted inventory; EAI will, therefore, generate additional revenues for content creators.
The model will also create new affiliate marketing opportunities for the network itself, offering viewers watching a “how-to” video an opportunity to buy the products featured, for example.
The application of EAI’s unique technology is not limited to YouTube. It can also transform the monetisation of live broadcast content. In last year’s Rugby World Cup, viewers on Japan’s J Sports network were able to click through from images of individual players on-screen to buy replica shirts.
Such a service can be curated in real-time, promoting those players having a good match (and easing back on those not performing so well).
Such innovation requires disruptors to harness a combination of technologies, from machine learning to video analytics. Again, this is bad news for the incumbent providers.
Advertising agencies that have for many years depended on acquisition and consolidation for growth find it very difficult to adopt new technologies; their size and scale mitigates against early adoption.
The barriers to entry that such agencies once counted on, moreover, no longer apply. Small players simply need a disruptive technology to enable them to steal a growing slice of the pie.
Indeed, while agencies benefit from consolidation and disruption, digital adoption has rapidly increased fragmentation, to the advantage of smaller businesses with scalable technologies.
The end of third party data
There are so many examples of change at pace. The rise and fall of third-party data in the form of cookies provides a cautionary tale.
Prior to GDPR and broader anxiety about data privacy, the ability to install cookies on the devices website visitors appeared to offer advertisers seeking to exploit emerging programmatic marketing tools with a golden opportunity to target with great accuracy.
Now, however, the use of third-party data is rapidly fading.
Instead, there is a concerted move towards zero-party data, where consumers willingly offer up significant data about themselves in return for curated content.
Take the growing number of clothing recommendation services, which collect subscriber’s data – everything from style preferences to body size – and allow selected advertisers to aim directly at them. For innovators that move quickly, this idea will prove valuable.
Subscribers to YouTube and Netflix, for example, are effectively volunteering data about themselves so that content providers can make them targeted offers. Online communities are another rich source of such data.
Mumsnet is also a good example, as is Yappy, a personalised e-commerce proposition where dog owners create a unique avatar of their pet, volunteering personal data in return for an enhanced and bespoke online experience.
This is an age of mass-personalisation and granular stratification. Tribe, another disruptive business where we have invested, provides an example of that in practice. It identifies small-scale influencers not yet on the radar of large agencies – Instagram accounts with a few thousand followers, perhaps – and then uses data science techniques to identify the products and services best-placed to sell to this very specific audience.
It’s a scientific approach to advertising that is powered entirely by technology.
Racing to engagement
Elsewhere, other types of opportunity are emerging. The video games sector, for example, was riding high even before the COVID-19 crisis forced people to stay at home, often off work with little to fill their time.
Its distribution model – games increasingly available for download online rather than in a boxed version – was also ideal for the pandemic.
Leaders in the sector such as Codemasters have been quick to recognise what is possible from collaboration and outreach.
Its popular F1 series involves close work with the rights holders in motor racing; both sides see the games as an opportunity to build engagement in each other’s audiences.
The advent of e-gaming adds to the mix, with crossover events held during the lockdown, such as professional motor racing drivers competing online with professional gamers – further building the brand.
Again, none of this would be possible without the confluence of a broad range of technologies and, as in other industries, video gaming businesses are only just beginning to recognise what is possible.
In the race to capitalise on such opportunities, however, small and nimble is set to win the day.
David Leahy is an Investment Manager at Gresham House Ventures.
