How AI’s Machine Learning Algorithms are Personalizing Product Recommendation
Artificial intelligence (AI) has the potential to revolutionize the way e-commerce websites approach searchandizing. With the help of machine learning algorithms, AI systems can analyze vast amounts of data about customer behavior, preferences, and search patterns to optimize the presentation and ranking of products in search results.
One way that AI can be used for searchandizing is by predicting which products a customer is most likely to be interested in based on their past search and purchase history. By analyzing a customer’s past interactions with an e-commerce website, an AI system can learn to make recommendations for products that are tailored to the individual customer’s interests and needs. This can help to increase the chances that a customer will find and purchase a product on an e-commerce website, and can also help to improve the overall shopping experience for the customer.
Another potential application of AI in searchandizing is the ability to analyze and optimize the visual presentation of products in search results. AI systems can use image recognition and other techniques to analyze the appearance and features of products, and can then use this information to recommend the most effective way to present the products to customers. This could include recommending the use of certain images or video content, or suggesting the use of certain color schemes or layout elements to make the products more appealing to customers.
The potential of AI for searchandizing is vast, and it has the potential to significantly improve the way e-commerce websites present and rank products for customers. By analyzing customer behavior and preferences, and optimizing the visual presentation of products, AI can help e-commerce websites to attract and retain customers, and to increase sales and revenue.
Our products embed a powerful module dedicated to personnalization in which data are collected on real time during each customer journey on your website. You can boost your products with different formula :
- Low : high boost on low values (Logarithmic)
- Medium : less important boost on low values (Square root)
- High : linear boost, purely proportional to the chosen metric (Linear)