- Artificial intelligence. AI involves the ability to receive inputs from the environment, interpret and learn from such inputs, and react and behave in ways that absorb this intelligence to achieve a goal.
AI already has many real-world uses, including helping drivers navigate, as with the ride-sharing Lyft service as well as GPS assistance apps like Waze; online sites like Amazon that make recommendations based on your previous behavior, and applications like Snapchat and Instagram that can find meaning from facial expressions or emojis, as well as language translators or book readers that can read Tolstoy’s War and Peace in less than two seconds.
- IoT-connected devices. The billions of devices, which are connected to the Internet, have been installed in various items to gather data for customer service, environmental safety and improvement and product maintenance. IoT devices have been installed in home security systems, refrigerators, cars, oil rigs, traffic lights and surveillance cameras to gather data on the environment as well as human interaction with these items.
- Conversational interfaces. These user interfaces mimic human interaction. Recently, voice-activated conversational interfaces have matured. Examples include virtual assistants like Siri, Cortana and Amazon Echo, but also chatbots, and virtual assistants to help you schedule meetings
Together, these technologies can provide critical data about customers’ experience with products, provide information for customers to take action on, and more. As companies gather and use this data, they can provide better customer experience but also help to develop new products or features in next-generation products. Ultimately, Leary said, this new influx of product, usage and customer data is about creating a new customer experience.
Leary used the example of a smart refrigerator whose temperature and be adjusted automatically, or have a broken part sent out to the customer, even before he is aware that the part is malfunctioning. It also enables companies to gather new information about product usage that can enhance customer relationships or product development.
It can give “real detailed, data-driven uses [of products]” he said. “Being able to have that data flow back to the home office, run machine learning, find patterns, find things you probably wouldn’t have found any other way by taking huge amounts of data and analyzing it, that should provide understanding as to what kinds of ways can improve the experience based on hard data.“
Companies that embrace this three-legged stool of technology are likely to be the most successful in their respective markets. They will be able to get customer feedback and product information more quickly.
Leary predicted these trends will gather major steam in 2018, not just because of this competitive pressure but also because of customer expectations.
“Customers are ramping up their expectations dramatically as they get more comfortable with technology, so companies have to be ahead of customers if they want to keep them happy,” Leary said.
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