Imagine that a retailer could promote a product as personal as a perfume and match our preferences before we have smelled it. It is a very tempting possibility for them and one that could be a reality in the coming decades, as computer science experts believe that these lines are getting thinner and that the day these marketing techniques can be applied to attract consumers, it’s closer.Marketers and advertisers are developing a number of artificial intelligence applications that can understand consumer wishes, determine which sales pitches work best, and broaden a company’s base in the marketplace using targeted ads, rationalization.
But they are a long way from the capitalization of AI-based applications. Some may be wary of the technology they do not understand, while others may not see in turn the attractive results that marketing programs might leave behind. At the same time, artificial intelligence applications will have to go a long way to be implemented at the retail level.AI, the field of computing dedicated to making smart machines, has been used by Internet companies to make search engines more and more precise. The military uses it to carry out surveillance and financial institutions to prevent fraud. Computers use complex algorithms, a detailed list of instructions, to make decisions or reach conclusions that give the impression that they are thinking or learning.
The AI go-to-market request Japan Phone Number List will depend, to a large extent, on one of the most basic principles in the industry: knowing your customer. By focusing on their profiles, preferences, wants, and dislikes, marketers can try to attract them.The problem is that with the use of traditional methods, customer profiles are either incomplete or difficult to convert into strategies that really work. For example, the purchases we usually do in a supermarket. The data can tell retailers what they recently bought, but the store has no way of knowing why it responded to a certain promotion or didn’t show up last.
With AI however, the problems are becoming less burdensome. Powerful computer systems can collect information about customers and their habits through a loyalty card, to cite one example. Algorithms can identify patterns or trends in shopping behavior that can help managers determine which products might attract customers or when an in-store promotion would be most effective.
But it is not a perfect science, as many consumers may simply ignore or stop receiving emails from the loyalty card program, for example. But it can also help many clients, such as a person who does a lot of web searches about travel in Europe. You can only give ads from travel agencies, something that we can see on a daily basis with Google because it is the system it uses.
Experts say that these targeted ads will be increasingly sophisticated, to the point that we can imagine walking and passing by a clothing store, at which point we receive an alert on our Smartphone about a specific offer of jeans if we buy them in this moment. Jeans that we bought in the past and the system retains and remembers it every time we pass by. “Things like this are totally possible,” said Stan Matwin, an Ottawa computer science professor.
Another innovative development is what is known as customer segmentation. Traditionally, retailers can divide their customers into different groups, but now complex AI applications are being created to capture details. Professor Monica Casaba yo, from EASED Barcelona, commented that it is achieved by applying “fuzzy logic”, what we can classify as gray terms and not just black or white.
It shifts away from statistics and instead uses large amounts of customer information obtained through point-of-sale data, loyalty card information, surveys, and social media activity. The degree to which consumers feel loyal to a particular brand or if they are obsessed with buying low-cost is determined.