Are you looking to boost your company’s online retail sales, or are you just a consumer who wants to know what makes a good online customer experience in 2024? Then you’ve come to the right place!
The rise of digital technology has had a profound impact on the customer experience in the online retail sector. Consumers are more and more demanding, looking for an immersive, visual and personalized experience, while prioritizing simplicity and fluidity in the purchasing process. Against this backdrop, we might ask how advances in artificial intelligence (AI) have played a decisive role, transforming every stage of the customer journey.
In this article, we explore how artificial intelligence, notably via predictive AI on the one hand, and generative AI on the other, is revolutionizing the customer experience across different phases of the online shopping process.
But before delving into the article, it’s important to understand the nuances between the two types of AI mentioned above. By focusing on the use of algorithms to solve specific problems, predictive AI helps to optimize the processes of recommendation, personalization and prediction of purchasing trends. On the other hand, generative AI, by mimicking existing models to create new data, images, or videos, opens the door to more immersive experiences for customers (Hermann & Puntoni, 2024).
1. Awareness & consideration
In this initial phase, the objective, from a company’s point of view, is to create the need in the customer’s mind. This is where customers discover the different products and services available. In this context, generative AI can prove effective. It has recently become possible to create visually appealing content, such as dynamic images and videos, capturing customers’ attention and encouraging them to explore further. This can be done in a larger-scale advertising context, but also in the showcase site by generating product descriptions and images. What’s more, in the context of Search Engine Optimization (or SEO), although AI-based search engines are likely to endanger certain sites reporting historical facts, guide articles, or reviews for example (Villecourt, 2023), it will probably be an excellent opportunity for commercial sites. These new search engines make it possible to highlight products in AI responses.
At the same time, predictive AI can analyze purchase histories, search histories and browsing behavior data to provide personalized recommendations, directing customers to products that are likely to be of interest to them.
2. Online shopping
As customers move on to the purchasing act, generative AI can simplify and optimize the process by offering smooth, intuitive customer journeys via functionalities. These features include guided navigation, which uses virtual assistants to ask questions about the user’s preferences and then suggest products based on the answers given. There’s also virtual search, which lets users search by loading images rather than words. For example, a user can upload a photo of a product they’ve seen somewhere, and the visual search system will identify the product or similar products available on the site; this is known as “computer vision”. This makes product searches more intuitive, especially when a user doesn’t know the exact name or features of the product they’re looking for.
Another aspect of AI, this time predictive, enables us to increase a consumer’s average basket by suggesting, at the end of the customer journey, complementary goods to those initially added to the basket. This encourages additional purchases and increases the average customer basket.
3. After-sales service
In the after-sales service phase, AI ensures continuous assistance to customers thanks to intelligent chatbots. These chatbots, with built-in generative capabilities, provide instant, personalized assistance, answering customer questions accurately and efficiently. Today, AI acts as a support system, helping users to resolve faults or incidents encountered during their digital experience. So, for the time being, it’s just level 1 support out of 3 on the IT support scale. Level 2 refers to the treatment of the problem at the root of the incident, and level 3 to expertise in specific areas of competence.
At the same time, predictive AI qualitatively analyzes customer interactions using natural language processing (NLP), enabling companies to understand customer needs and concerns in order to offer quality after-sales service.
4. Loyalty
In the customer loyalty phase, AI combines its generative and predictive capabilities to strengthen the customer-brand relationship. Thanks to predictive algorithms, companies can propose personalized, targeted offers by analyzing customer behavior and preferences. These algorithms also identify churn factors, making it possible to anticipate and intervene before the customer turns away.
At the same time, generative AI automates the creation of personalized communications, such as emails with specific offers based on customer characteristics and searches, or even in response to detected unsubscribe signals.
Together, these technologies enable advanced personalization and proactive interaction, making each customer unique and valued, while strengthening their loyalty over the long term.
In conclusion
Throughout every phase of the customer journey, artificial intelligence reinvents the customer experience, offering fluid, personalized and relevant interactions. By combining the generative and predictive capabilities of AI, companies can improve their knowledge of their customers or potential future customers, to better meet their expectations by anticipating their needs, strengthen their long-term loyalty, and thus increase their growth. (Vijayakumar, 2023)
Bibliography
Hermann, Erik, and Stefano Puntoni. “Artificial intelligence and consumer behavior: From predictive to generative AI.” Journal of Business Research, July 2024, https://www.sciencedirect.com/science/article/abs/pii/S0148296324002248. Accessed June 2024.
Vijayakumar, Harsha. “Revolutionizing Customer Experience with AI: A Path to Increase Revenue Growth Rate.” 15th International Conference on Electronics, Computers and Artificial Intelligence (ECAI) [Bucharest], 2023. Accessed June 2024.
Villecourt, Arthur. Youtube, May 2023, https://www.youtube.com/watch?v=Uy7ILn-48J8. Accessed June 2024.
