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How Machine Learning Is Transforming Shopping

Sellers want to create best possible customer experience

In this digital age, we are starting to see great practical ways in which artificial intelligenceArtificial Intelligence knows many different definitions, but in general it can be defined as a machine completing complex tasks intelligently, meaning that it mirrors human intelligence and evolves with time. () can shake up the status quo. Take the recently launched ‘ lawyer’ DoNotPay for example – an powered chatbotChatbots are computer programs which were engineered to converse in spoken or written form with humans. They are usually used in dialogue systems with a limited topic range. For example, they can answer basic customer questions or help you buy the correct train ticket. that gives free legal and immigration advice. Then there is the marketers’ mission to create a utopian, near-perfect experience for customers, with the likes of the O2 announcing that is set to handle its customer services from 2017 with a voice recognitionIn voice recognition an algorithm is able to listen to what a human or machine says and write it down and understand its meaning. Image Recognition describes the process of a machine knowing that you are currently looking at cat pictures. Consequently, video recognition denotes the act of a machine watching a video, and being able to understand what it 'sees'. system called Aura.

Personalize the shopping experience

, machine and predictive intelligence are terms that are frequently thrown around in the marketing space, and we’ve known for a while now how these emerging technologies are going to transform businesses and the customer journey, but how will the everyday man or woman on the street feel about the experience in reality? There is still a level of apprehension from customers about talking to an automated so-called instead of real people, but in fact, and machine can help humanise the customer experience by making it more personal for each user. Studies have shown that 78% of customers start the buying process with a web search, while 50% of us turn to social media to see what others have reviewed, before we even think of clicking that buy button. Wouldn’t it be great if businesses took this a step further, and right at the time when you were looking up attractions in a city you’re going to visit, a hotel decided to offer you a discount, or for instance, a restaurant tempted you with a dinner voucher just as you were about to book a table for a date? Machine is starting to make this happen and it’s the reason behind the success of services like Netflix, which make life easier for customers by tailoring to their needs.

Marketing needs to be about more than selling

As customers, we get tired of businesses and brands engaging with us only if they want something from us, and when you purchase that thing, you get radio silence. Ultimately as human beings we don’t like stereotypes, and the tools that marketers have today often treat customers as stereotypes. With more channels, social platforms and websites than ever before, our expectations as customers have shifted; we don’t want businesses to create persona and tracks, we want them to personalise their approach to us, make it unique, and be there for us to deliver us helpful information even after we purchase and become a customer. The humble beginnings of Google Maps is a good example of how a product has evolved by using elements to benefit the customer experience. It started with a simple cloud based map and, after having incorporated data such as streets, traffic signals and finally, real-time traffic updates, provides a platform that travellers now almost can’t live without. Automated navigation software, such as Google Maps and Waze, have essentially become “co-pilots” for many drivers – collecting real-time information, understanding where drivers are at in their journey and continuously their frequent destinations, commuting hours, and preferred routes. And ultimately, applying all of this in an personalised and actionable way — to essentially make sure we don’t end up in the middle of a lake when driving from A to B […]

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