According to Wikipedia, Artificial Intelligence, or AI, is the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
Translate this into increased content personalization for consumers, and data insights allow retailers to spot trends, tailor product recommendations, modify prices in real-time, and more.
But can B2C companies create a seamless and consistent user experience across multiple touch points using AI in order to maximize sales—while keeping consumers comfortable with the fact that their behaviors and preferences are being collected, utilized and presented back to them daily?
Alexa—the voice service that powers Amazon Echo and the all new Echo Dot—provides capabilities, or skills, that enable customers to interact with devices in a more intuitive way, using voice commands.
In late 2016, Google announced Google Home, a Wi-Fi speaker that also works as a smarthome control center. Powered by Google Assistant, it can be used to playback entertainment anywhere in your house, effortlessly manage every-day tasks, ask Google whatever what you want to know. Google Assistant is an adaption of Google Now and Ok Google, and it “basically improves the two-way conversation experience of those services thanks to AI and machine learning.”
The Future of AI Personalization
As Greg Ng, VP of Digital Engagement at PointSource writes in Website Magazine:
To better understand where AI is taking us, consider Amazon’s Alexa.
Currently, Alexa uses speech recognition and keywords to perform various tasks ranging from placing online orders to providing weather updates. For example, if a user asks Alexa for Chinese food recommendations, the technology combines geographic information with restaurants the user has engaged with in the past to offer a suggestion that is nearby, open and consistent with previous behaviors. This innovation certainly demonstrates the power of personalization, but it merely scratches the surface of what AI can do.
Let’s consider this scenario again. A user asks Alexa for Chinese food recommendations, and during the exchange there are voices in the background. Based on this context clue, Alexa may determine that this order is for more than one person and can suggest a restaurant with family deals or group specials. Or, Alexa may be able to monitor the user’s tone to deduce agitation. If this is the case, Alexa could encourage the user toward a restaurant that is known for speedy service, recognizing that agitation often indicates impatience.
These are just two examples of how AI can supercharge the digital user experience moving forward. The possibilities are endless, and marketers can apply them to any search function or transaction. Sentiment will dictate how AI informs future interactions, and when married with contextual information like environment and time of day, it seems as if companies can personalize UX down to the very moment it happens.
Investors are betting big on AI, and AI acquirers are in a race to meet demand.
While many people tell friends that they find it intrusive or disconcerting that their “private” online behaviors and offline transactions are being mined, it’s hard to find anyone who doesn’t secretly (or overtly) love the convenience of a simplified, positive experience when they need something.
For businesses across all industries, big data represents a goldmine—but only when harnessed, sliced and utilized strategically.