Using AI to create a personalized shopping experience in online retail
The future of e-commerce is being massively influenced by the use of artificial intelligence. AI in online retail is already contributing to a significantly improved user experience by offering personalized buying experiences.
More personalization and service as a result of AI in e-commerce
Personalized offers instead of endless product lists: especially in online retail, the challenge of meeting consumer expectations with regard to unique customer experiences is growing. Recommendations and products ideally need to be adapted to the preferences and needs of customers, even before they themselves really know what they want.
This is precisely where new technologies such as AI in online retail come in, offering authentic and tailored experiences that are relevant to each individual customer. The benefit to online retailers: such improved usability and personalization, where the exacting requirements of today’s consumers are also satisfied, strengthen customer retention and increase sales in the long term.
Machine learning algorithms for personalized offers and recommendations
Artificial intelligence in online retail is generally based on complex machine learning algorithms that are trained using behavioral and transactional data in order to develop an understanding of customer needs. E-commerce companies can utilize the collected and processed data to recommend personalized products to every customer in real time and thus design an individual, user-oriented shopping experience. In essence, professional AI solutions in online retail create a customer journey that is individually tailored to every consumer’s interests and needs and goes way beyond merely buying a product.
When AI in online retail plays on the “Diderot effect”
The Diderot effect is a term used in consumer research and describes a consumer’s potential compulsion to make additional purchases after buying an item in order to create a harmonious overall picture. For example, when someone buys a new jacket, it may trigger their dissatisfaction with other items of clothing or accessories, such as their shoes or handbag, and lead to subsequent impulse buying. In brick-and-mortar retail, the Diderot effect is a part of the standard repertoire of skilled sellers. In e-commerce, AI can play on this behavior through personalization and, by analyzing clicks, shopping baskets, purchasing history or search queries, can deliver suitable suggestions for additional purchases that make sense in the eyes of the user.
Personalization beyond mere product recommendations
Online retail personalization solutions that are based on AI are not limited to mere product recommendations; they are much more versatile. Whether menu navigation, newsletters, or editorial content, AI-driven systems can be used to optimize the personal shopping experience of customers on many levels, for example:
- Personalized addressing using different welcome texts or product descriptions
- An online shop navigation sequence that is adapted to demographic characteristics or visitor history
- Product categorization
- Analysis of customer reviews in order to better gear products and product suggestions to the target group
- Dialogue-oriented online retail through the use of smart chatbots and voice-controlled services
- Email marketing by tailoring relevant content to the respective customer
AI is gaining ground in online retail
The diverse possibilities offered by artificial intelligence in online retail are already being used today in the innovative solutions of numerous companies. For example, Amazon’s digital shopping assistant “AR View” utilizes augmented reality to let customers virtually place selected products in their own home before buying them. After starting the app, the user simply lines up the smartphone with the spot he or she has designated for the item. Via augmented reality, the product then appears on screen in a matter of seconds and can be turned, moved around, and viewed from different angles.
Visual search solutions are also incredibly popular with many e-commerce providers. For example, consumers can take a photo of a certain fashion to get similar product suggestions in an online shop. For several years now, industry giants including Zalando, Otto, and ASOS have been increasingly incorporating the principle of simplifying customers’ product searches through uploaded photos. And for good reason: according to OMD’s most recent study “The Retail Revolution”, 67 percent of Germans have already utilized visual search options – and the trend is growing. Visual search therefore presents promising opportunities and offers enormous marketing potential, especially in the fashion, food, and cosmetics industries.