Augmented Intelligence (AI) is all around us. While the perception of AI on the film screen may thrill viewers with a vision of humankind chained to robots and computer systems, the reality is that in 2017, we will be leaning on AI systems to help us make smarter decisions. Many of us are increasingly becoming more reliant on helpful prompts and personalised entertainment, for example, by adopting smart meters as part of a connected home. And, as we do so, our reluctance to use automated systems will tip into a realisation that we can be more efficient and more creative when harnessing the power of AI.
By definition, the volume, frequency and velocity of this data means it is no longer efficient to attempt to manage, optimise, visualise and activate campaigns using traditional, manual techniques. If we accept that all media will be addressable and programmatic, we should also accept that all media will be machine learned at some point. It is only a matter of when and the pace of this transformation, rather than if it will occur. This, in turn, has been fuelled by an explosion in cloud computing and continuing innovation in chip technology to keep pace with the computational demand. This shows no sign of decreasing, and in fact, represents the true transformation the internet has always heralded.
As AI is now becoming more mainstream, many techniques are being used by brands, from robotics, machine learning, voice recognition, semantic learning, VR and many others. You may have seen the Zenith Trends piece for 2017 that describes where these techniques can be applied throughout a user journey.
In my view, the breakthroughs in AI for marketing will come as a result of significant automation and the true integration of these techniques at customer level. What this means in practice, is a vastly superior customer experience, as every touchpoint and customer preference is connected and mined by machine learning techniques that optimise each interaction based on any given KPI – a web visit, brochure request, a sale etc. The objective is that this experience, and the techniques used to optimise them, are invisible to the consumer. This will result in dramatic cost reduction and significant improvements in engagement at all stages of the customer journey.
A major part of this innovation will include the ability to optimise content in real-time well beyond aggregated segments, and instead to individual consumers, combining all other “signals” about a given consumer within a single platform. This will herald the era of the machine learned customer journey that will significantly outperform traditional research or segment-based techniques. This will also enable consumers to pass positive and negative feedback directly to a single data source (single customer view) that will drive all interactions with a brand.
There is no doubt AI will bring significant change, but also significant benefits to marketing as we know it, and this is a process that is now unstoppable. This will initially include the integration of existing techniques at customer level to drive personalisation and increasingly positive experiences; this is evidently beneficial to sales, service and re-purchase, but AI will also be increasingly used in customer acquisition. For many brands, the wealth of data available from social feeds, as well as rich transactional and third party data, creates both a challenge and an opportunity. Conventional social listening, for example, is often constrained by the logic that is forced on a given query – such as time periods, geographies, key words and demographics. This often returns a large dataset, but not the crucial insights that are needed to modify campaigns, packaging or distribution through the retail channel. Equally, these queries are often undertaken after the fact rather than in advance of known changes in consumer behaviour or needs. The application of machine learning, particularly with a natural language interface, will enable queries easily understandable to marketeers without a technical background – an area we will see both investment and business benefit.
In these examples, the real benefit from AI is the ability to tie large of amounts of data to a specific outcome (a sale, enquiry or web visit) and then optimise that outcome as more data arrives and at a speed that was not possible before. There is no doubt that this means traditional processes will improve, disappear and be streamlined and that automation is an inevitable consequence of this innovation.
We should embrace this, and recognise that it does not replace or diminish creativity or strategic thinking – it should be used to empower it.
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