Artificial intelligence (AI) and machine learning (ML) have huge potential to drive a new generation of creative brand experiences. They are at the forefront of a powerful shift that will bring brands closer to consumer expectations, passions and emotions. Assistive and smart technologies are catching up and we’re already facing a new world of possibilities.
AI and ML can be applied in many ways. The use of machine learning to power business decisions and product recommendations is becoming widespread. We experience it when we buy on Amazon, watch television on Netflix, hail an Uber or tag friends on Facebook. There are more creative experiments out there such as “The Next Rembrandt app”, “machine music composition” and “TV show script generation” that use ML to create new art (with mixed results). While AI is poised to transform our industries and technologies, just like electricity did in the mid-twentieth century, AI has the potential to change art, creativity and the way brands and agencies create the next generation of experiences.
It’s easy to hear all the buzz and think of AI and ML as new or recent developments, but they have a long history. AI has been researched since the dawn of computing but in the past few years it has become more powerful, flexible and accessible. This is down to heavy investment from companies like Intel, Google, Apple and Facebook, leading to faster, cheaper hardware with better algorithms.
The key to a successful machine-assisted experience is data. Converting big data into useful data is a difficult challenge. This is where agencies and brands have a huge opportunity. Netflix has been successful in making sense of consumer data, to the point that it now knows which shows and casts will become hits, before they have even been filmed.
One big issue is that most of the data being captured isn’t smart. Often, it doesn’t reflect consumer interests and takes a lot of analysis (and sometimes plain guesswork) to come up with insights that drive strategy and creativity. Traditional web and mobile analytics don’t work as expected in a hyper-connected world. Demographics, page views, page clicks and hashtags are falling short in their exposure of true consumer learnings. Lifestyle, sentiment and engagement are the key elements to go after. Spotify has done this in innovative ways, marrying user habits like playlist creation with crowd-sourced behaviours to create personalised playlist suggestions.
Brands want to understand how people feel about their services, products and content. So far, though, it seems we only have a partial view of consumers, not the full picture we aspire to. This is exactly where a new wave of interfaces will move the industry forward, away from a straight broadcast out with frivolous two-way interactions towards a more natural dialogue between brands and people.
With the rise of new interfaces and interactions such as 1:1 messaging, voice-enabled services and natural language processing, we have a chance to reach a deeper understanding of consumers.
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