A few years ago, experts were trumpeting that the future is mobile, and they weren’t wrong. Some of the world’s most successful new apps and business models are mobile-based — just look at Uber, Instagram, and Snapchat.
Now, our machines and devices are beginning to understand us on an even deeper level. Machine learning and artificial intelligence are being used to improve user experience and transform the way that we interact with technology. The aim is to simplify processes using complex assistive technologies and seamlessly integrate them into our lives. Large datasets help to train algorithms and change user interfaces for products and services.
But does this mean that we’re creating more ways to strip tangible, human approaches from the way that we live, work and play? Isn’t it more important than ever that we prioritize personalized, human-centered moments?
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Gartner predicts that 100 million customers will shop in augmented reality by 2020. This is going to be a massive point of disruption for the way brands and customers interact with one other. AR is about using information manipulation to create more visual value, whether for professional or entertainment purposes. Take a look at the new iPhone X and its AR capabilities.
The intersection between AI and AR is exciting. There are currently a lot of AI assistive technologies on the market such as Amazon Echo and Google Home.
They use voice technology and conversational interfaces to provide information to a user and respond to commands. One analyst even estimates that Amazon’s voice technology could bring the company up to $10 billion in e-commerce sales by 2020. With more AR capabilities, an assistive tech could become even more assistive. Visual data, maps and more could be enhanced with AR.
As data sets get bigger and bigger, the opportunities for devices to utilize machine learning and adapt to surroundings increases.
Your device can know what’s in your fridge and tell you to pick up groceries or start using spatial awareness and Wi-Fi radar to learn its environment. The “internet of things” can create a connected home/office and will be able to anticipate needs and behaviors.
In rapid digital transformation, it’s vital that we don’t forget who we are. With the large customer data sets that brands are generating, they need to ensure that they use them in emotionally intelligent ways. Using social listening tools to combine data with customer intelligence will help brands engage with customers meaningfully, directly and consistently.
It’ll also help brands understand whether customers actually want some of these new and crazy products they’re proposing. Do customers want every item they own to be mobilized by the internet of things?
Listening to customers makes business sense, promotes a human-centric approach and prevents a brand from bringing irrelevant solutions to market. Product development, brand strategy, and marketing can all be better with a human-to-human method.
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Machine learning can create more relevant and targeted communication, too, that doesn’t feel invasive or full-on. According to a study by HubSpot, 91% of online users in the U.S. and Europe found that advertising and marketing have become more and more intrusive over the past two to three years. So, there’s an opportunity here to tailor advertising towards customer’s online habits and behaviors.
BACS took on a Current Account Switch Service campaign in the U.K. and deployed machine learning with programmatic ad buying. They were able to build more comprehensive user profiles and “track on-site engagement and customer journeys on an individual level.”
BACS could then match likely switchers’ browsing behavior with targeted video content and increased acquisition click-through rates by 870%. This highly personalized approach, which took unique customer-centric behaviors into account, meant that BACS could prevent customers being bombarded with content.
Having so much technology at our fingertips can sometimes feel a bit alienating. An important aspect that can help to bridge that gap and differentiate the ways brands use AI, ML and AR is with conversational, personality-driven approaches.
Conversational interfaces can utilize linguistic data so that they can respond in an emotive way. And data can be used for creating engaging content for any digital channel.
Relative Insight is an example of a company that has recognized the need to create products and services that bring customers closer to brands, using language and tone that appeals to the customer.
They analyze language and turn it into large datasets that enable brands to create emotive marketing that connects with consumers.
Talking to people in a comforting way creates more brand affinity. Learning to communicate in a way that doesn’t patronize customers and speaks to them on a human level can help to position your brand in a positive way.
Good conversational interfaces and meaningful engagement help to keep developing technology moving in an understandable direction.
If it’s grounded in human, personality-driven approaches and uses data in emotionally intelligent ways, new technology doesn’t seem as alienating or daunting.
Tech can help to make customers’ lives easier and simpler, but not in an invasive way that crosses the intrusive human lines.
This originally appeared on Forbes here