What does the concept of artificial intelligence (AI) conjure up in the mind of the consumer? Will our children be replaced by fun-loving androids as the eponymous 2001 Steven Spielberg film A.I. suggests? Or perhaps grown adults will suddenly be replaced by robots in the workplace?
While all of that may seem a little far-fetched, in reality, AI is already integral to many consumers’ daily lives – in the form of image and voice recognition on mobile devices; personalised viewing suggestions on streaming platforms such as Amazon Video or Netflix; or voice interaction/recognition analysis incorporated into search engines such as Google.
AI has also gained recognition in the healthcare sector – machine learning applications that have the potential to assist hospital staff in routine tasks such as keeping a patient’s treatment records up to date are being tested and the voice-controlled Amazon Echo device, Alexa, can assist patients at home with tasks such as reminding them to take medication or arranging a GP appointment. AI also made news within the gaming industry. Earlier this year, a bot named Liberatus learnt the rules and strategies associated with poker before going on to beat four world-class poker players over a three-week tournament.
And in the digital advertising industry, AI is also emerging as a necessary tool for marketers to better engage with their customers. So, with AI firmly on the agenda, how can businesses stay on top of the digital marketing ecosystem and achieve the optimum balance of technology and human intervention?
The current role of AI in digital advertising
In recent years, the digital world has become increasingly aware of, and reliant upon, AI technologies. To ensure the responsible and transparent development of AI, technology giants including Google, Facebook, Amazon and (most recently) Apple established the ‘Partnership on AI’, which aims to promote the benefits to marketers and consumers, and alleviate any concerns about the impact of AI on daily life. But amid these times of speculation, marketers are beginning to realise that one thing is for certain: AI is a reality, and will inevitably have an impact on the digital advertising industry.
The first thing for marketers to understand is how AI is already influencing digital advertising. Several ad platforms already incorporate machine learning technology and Natural Language Processing (NLP) to enable the delivery of more relevant content to consumers, as well as creating more cost-effective targeted algorithms and campaigns. NLP works by semantically analysing data at a granular (i.e. page) level – in real time – to comprehend and process words, emotions, and context just as the human brain would. By making use of these sophisticated technologies, marketers can make decisions in seconds as to when and where they should be placing their ads to best reach and engage their target audience.
Taking digital advertising to new heights with AI
With the proven potential of AI growing daily, many industry experts are making predictions about its role in the future of online advertising. So exactly how will AI impact areas such as data processing, brand alignment, and ad placements for marketers?
Honing in on the data with first-party propensity profiling
With programmatic set to account for more than three-quarters of UK display advertising in 2017, marketers are placing more and more importance on the use of first-party data to target audiences through the delivery of quality ads – despite the quantity of impressions served. Machine learning can already be used to filter and refine large volumes of data – and when used to its full potential, it can analyse and predict customer moods, tastes, and needs to build a propensity profile based on their tendency to interact with a brand or specific message. Marketers can use these first party profiles to adjust and optimise accordingly for their campaigns.
For brands, building up first party data sets with customer feedback and digital interactions is a base for AI. As a starting point, brands can match customer interest/behaviour profiles in response to brand campaigns with first party data - we’re not far from the day when all major brands will “learn” from their daily digital customer interactions to create their own propensity profiles. This will help ensure the most effective and continuous buyer-seller relationship using a programmatic environment to deliver personalised messages at scale.
With access to such rich data to stimulate and capture interest from the consumer, the process of lead generation can be revolutionised by AI. The abundance of information readily available online has made it more important than ever to break through the noise in ways that mass-untargeted advertising cannot.
Understanding a consumer’s need
Knowing what resonates with a consumer is the holy-grail of digital advertising. Taking the information on what interests and content a consumer likes to engage with means digital publishers can produce a content recommendation engine to understand what content they are likely to engage with in the future. Ultimately, this means advertising yields can be maximised as inventory can be sold based on audience segments, dependent on the interests and likelihood of consumers to engage.
There are many ways in which AI can help – and is already helping – optimise campaign results. Such advances include optimisation engines that support campaigns from the perspective of the best buying/purchase and delivery solutions, understanding the best contextual placements, and dynamic creativity solutions where AI is used to determine the most effective creative.
Through cognitive and semantic technologies, AI can be used to determine how appropriate a brand’s ad placement will be within a certain contextual environment, and therefore how relevant the ad will be to that particular audience. With video becoming one of the fastest growing ad formats today, as highlighted by research from IAB/PwC, contextual video placements in particular are benefiting from AI technology. Outstream and in-read formats – which can appear anywhere on the page – compared to traditional video ads, which run before, during or after an online video – now account for 40 per cent of total video ad spend.
With the help of machine learning capabilities and looking beyond simplistic keyword classifications, marketers can detect trends in user traffic and behaviour to enable contextually relevant ad alignment.
Unifying omnichannel marketing
With the rise in omnichannel marketing strategies to harness the explosion of consumer data now available, AI will play a key role in the integration of several different messaging platforms to create a unified user experience that will one day include the use of chatbots and virtual assistants as standard. Marketers will move away from focusing on each channel separately and, with the help of AI, start to assess their marketing campaigns as a whole.
While chat bots are not yet capable of sentience to provide a realistic human experience, AI enriched bots and customer engagement tools can be effective. However, for the full benefits to be realised, AI must be deployed transparently and in a way that is relevant to consumers.
So while it is safe to say that we are still a world away from technological singularity – i.e. androids knocking at your door – now is the time start to thinking about how AI can and will affect your business, and how you can use machine learning and semantic technologies to deliver more relevant campaigns than ever.
Giovanni Strocchi, CEO, ADmantX
Image Credit: John Williams RUS / Shutterstock