Artificial Intelligence: How AI Is Changing Retail in 2023

Nowadays, it is hard to imagine a successful retail business without AI. These technologies have long been an integral part of retail and e-commerce.

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Even if you don't know much about it, you have probably read or heard something about one of the retail/e-commerce-specific AI technologies below:

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• ?Virtual Shopping Assistants— AI voice-based assistance that can answer a consumer’s questions and make some personalized suggestions on the basis of analyzing data related to this customer.
• ?AI-driven AR – present goods in Augmented Reality, e.g., 3D models, and trying-on-apps (clothes, interior items).
• Smart Checkouts – customers can buy products in the shop and just go out. The AI-based solution makes all: scan products and make payments from the customer’s card.
• Personalized Recommendations – AI-based solutions gather customers' data and make personalized suggestions for purchases.
• AI-powered chatbots and messaging agents—these chatbots help reduce the time of response and increase customer satisfaction.
• Automated Service Interactions – AI-tools help automate the process of sending messages to a customer about the status of an order or service and the process of ordering or refunds.

Why is AI important in retail and e-commerce? The answer is in advantages, and the main ones are:

• increasing efficiency in the supply chain;
• increasing client satisfaction;
• improving product placement;
• personalization that leads to more sales;
• decreasing costs;
• optimized decisions based on data.

Let's take a closer look at the technologies of the 2023 trend: AI personalization shopping. This solution can help companies deliver personalized experiences, such as recommendations, search results, email campaigns and notifications.

At the base of such a tool can be some ready-made solution, for example, AWS personalization or can train its own AI model. The main technologies here are natural language processing (NLP), collaborative filters, XGBoost, K-means and user-based recommendation.

AI solutions can gather interaction data from users and after that build a collaborative-based filter - how do users' wishes intersect and after create some segments/clusters with multiple users. These segments are created based on the customer experience, taking into account business requirements (e.g., age, gender, price, etc) and then making a personalized recommendation.

If we talk about new clients here you can also apply AI tools to recommend the most popular goods based on sales analysis of gathered data or by using the filter of what the person is looking for right now. One more great option for collecting data about the customer, especially the new one, is the use of a quiz, which will help make your recommendations more personalized.

Also, we can rank goods by the likeliness of users based on analyzed data and make recommendations to the right customer, even for new products, and predict sales for some new campaigns that can efficiently increase sales.

Our solution is supported by AWS services including Amazon Pinpoint, Amazon Personalize. Amazon Personalize to provide similar item recommendations, search re-ranking based on user preferences, and product recommendations based on user item interactions. Amazon Pinpoint sends messages with personalized product recommendations to the customers. Also, we use FAISS to efficiently search for similar goods description and images.

How can our AI solutions be useful for your business? These solutions help to:

• attract new customers based on a unique customer personalization offer using a 3d avatar for more accurate sizing and product fitting demonstration;
• retain the customer by increasing the usefulness of recommendations and reducing purchasing time;
• increase the average sales receipt by understanding the needs of the client and recommending a set of products (related products);
• reduce the cost of supporting the flow of the client by using a smart assistant based on chatgpt;
• reduce errors in product and service descriptions, eliminate duplications and outliers in primary data based on our ML & NLP models;
• Provide fast integration with supplier data based on our ETL pipeline;
• find personal sales strategies for each client based on an analysis of their psychological, behavioral and anthropometric characteristics.

If you want to get AI-driven solutions to renovate your retail business, please contact us!

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