Hyper-personalization: Experiences Consumers Want Now

Is the hyper-personalization the next stage in the evolution of customer engagement?

Customers are ever more demanding, tech-savvy and have almost unlimited access to information through the usage of different devices and platforms. In the Information Age, brands had to develop and improve their interfaces on each channel. Offer a more fancy, friendly and customized relation is unquestionably the key to success. As a consequence, these customers expect real-time responses with minimal effort and access to valuable rewards and customized experiences.

In retail customization is the key element, especially if we take into consideration that 50% of customers enjoy getting recommendations of products based on their interests while 49% are happy to share personal information with brands in order to improve their shopping experience. Amazon is an excellent example. If you’re a repeat customer you may be used to look at customized ads based on your purchase history. 35% of purchases in Amazon come from recommendations based on algorithms.

The purchase history can provide useful information about our likes and preferences, but also disrupt our recommendations. Not everything we buy on marketplaces like Amazon or any other eCommerce is for personal usage; there are products being purchased as a gift or for relatives.. Therefore, custom strategies to improve the customer engagement must be driven by the smart compilation and interpretation of information.

In this sense, the artificial intelligence revolution is facilitating smart data management, thanks to technologies such as deep learning.

3 Ways of using Artificial Intelligence to customize (and boost) shopping experiences

Artificial Intelligence has the capacity to customize the “customer journey” and help to improve the purchase process, which makes it more effective, attractive and adapted to personal needs on each part in the decision making process.

Product search: visual image recognition

The visual image recognition based on AI allows a picture taken with a smartphone to become a direct access point to an article or product. This solution allows to shorten the product search process to a single click. Visual shopping on search by image: an easy and friendly way to connect street styles with product catalogues.

The API of computer vision of Wide Eyes Technologies makes it possible for brands and retailers to identify automatically and with no human interaction several pieces of clothing that are shown in an image and offer users results from a selected product catalog that are visually similar to the ones shown in the image.

Out-of-stock: practical options in real time

The AI can take into account out-of-stock information in real time, when offering  customers products that match their needs. Once again, image recognition proves to be useful. The computer vision APIs of Wide Eyes Technologies allow enterprises to offer customers the right product in the right moment; in other words, to set up a personalized way to discover fashion by showing visually similar in-stock items.

Purchase decision: ultra-precise recommendations

Retargeting campaigns with banners showing products that a customer looked at or put in the basket without finally purchasing them are common by now. The APIs of Wide Eyes Technologies can help adding visually similar items to retargeting banners. Another application of artificial intelligence that has a positive impact on the purchasing process, especially in the fashion industry, is the style advisor. Suggesting a customer which pieces and articles to combine does not only provide an additional value to the customer but is an influencing factor in the decision making process of that person. The APIs of Wide Eyes Technologies can complete perfect outfits automatically taking into account a brand’s style guide as well as out-of-stock information. The API acts like a personal shopper that is always available to the client, namely having a personal shopper always available to the client.

These three use cases are probably the main reason why fashion retailers are investing in  using artificial intelligence to increase sale conversion rates and improve customer engagement.

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