Who wants adverts? It’s not a trick question; just think about it for a moment.
Yes, there are many organisations and individuals who make their living from selling adverts. There’s another group that wouldn’t be able to offer their current service if it wasn’t supported by the money they make from carrying adverts. These people most certainly want adverts.
If you work in the advertising or marketing industry, or have an ad-funded business model, try to pretend you don’t for a minute. Try to pretend you’re an “average Joe”, a private citizen, a member of the public, a consumer.
As you go about your daily life, trying to make a living, spending time with friends and family, looking for entertainment, keeping fit etc, do you at any point think to yourself, “oh, what I’d really like now is to see an advert for something”?
Probably not. In fact, you’re probably subconsciously ignoring the advertising around you. If you do become conscious of advertising, especially in a digital context, it’s probably because it got in the way of something you were trying to do, leading to irritation, annoyance and frustration. Not exactly the set of emotions the advertiser was hoping to generate with their campaign.
For many, passive irritation with digital advertising isn’t enough. The use of ad-blocking software is now mainstream. In the UK, 39 percent have installed ad-blocking software on their computer, mobile or tablet. In the USA this rises to 47 percent. The majority of future “consumers”, 18-24 year olds, are using ad-blockers (approximately 55 percent of them in both regions).
Even though people recognise that many digital services that they enjoy for free could not exist without ad-funding, they’re going to block those adverts anyway because they’re annoying.
Who Wants Advertising?
So, in the future, who wants advertising?
Probably not people outside the advertising industry. But there is an audience that is quite likely to want advertising or its equivalent in the future: algorithms.
The experiences we have via our digital devices and the content we become aware of is increasingly mediated by algorithms of some sort (Facebook’s EdgeRank, Google’s PageRank, etc). We see what the algorithm thinks we want to see. This extends into ecommerce environments, of course, with Amazon’s algorithmically generated homepage and product recommendations being a good example. Online grocery (Tesco, Carrefour, etc) is another area where algorithms shape the shopping experience, bringing products to our attention that it calculates we have a high propensity to purchase.
This algorithmic selection process is important in online grocery shopping because people tend to repeatedly buy the items already on their favourites list. It can only be a matter of time before such a service offers shoppers the automated ability to “order what you bought last time”, removing a large degree of human decision-making and minimising the marketing and advertising (or interruption) opportunities.
The Rise Of The Digital Assistant
The latest evolution of this type of algorithmic mediation is only beginning to make its presence felt. I refer to the rise of the “digital assistant”. All the big players have a digital assistant of some sort and TechCrunch have a handy overview here: http://techcrunch.com/gallery/a-battle-royale-of-digital-assistants-the-big-5/
Google have Now On Tap. Apple will release Siri Proactive with iOS 9 later in 2015. Microsoft has Cortana. Amazon has Alexa. Facebook entered the fray at the end of August 2015 with M. These digital assistants or smart agents are almost exclusively powered by complex algorithms that match what is known about you, your tastes and your context, to a set of products and services “out there” on the network. Facebook’s M also draws on the input from human operators that work with the algorithms.
Digital assistants are designed to respond to human queries and increasingly to proactively predict and act on the needs they perceive you to have--to take action without you needing to ask.
The algorithms powering digital assistants will need to know about products and services in order to act as truly “smart agents”, serving the needs of their human shoppers and researchers. In order to be useful, they’ll need to be aware of the available product universe; what the benefits of each product are for their shopper; if the pricing matches their expectations, and a host of other variables. The techniques necessary to make smart agents aware of products and services are very different to those used to acquire human attention. Advertising for algorithms may look more like a data feed or open database.
If algorithmic smart agents continue to develop as intermediaries between people, products and services, then those agents may well be good targets for “advertising”. People, research suggests, might not be.