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This article discusses the challenges of searching for auto parts online and how modern open source search platforms like Elasticsearch can overcome these challenges, providing better performance and scalability.
Replacements, Ltd., the world’s largest retailer of tableware, has launched a smart autocomplete feature on its website to improve the product discovery experience for customers. The new feature, developed by Grid Dynamics, uses a self-learning solution that learns new suggestions based on customer interactions with the search box, and has led to a 37% increase in autocomplete suggestion clicks and a 1.7% uplift in overall revenue.
In this blog post we describe the approach to extend the coverage of machine learned ranking to the whole result set, improving overall search results relevance and conversion rates
This article discusses the evolution of retail web search engines, from full text search algorithms to concept search and the current state-of-the-art deep learning-based semantic vector search.
The article discusses the evolution of retail search engines and the emergence of deep learning-based semantic vector search engines. It explains how semantic vectors can be used to represent and search for products and queries based on their meaning, and how deep learning models can be trained to produce these semantic vectors.
Replacements.com, the world’s largest retailer of tableware, has implemented a visual search solution using deep learning models to help customers identify patterns based on uploaded photos, improving the accuracy and convenience of the search process.
This article discusses the importance of relevance in online commerce and how automated merchandising tools can improve product discovery for retailers with large catalogs. It also highlights various strategies and tools that can be used to enhance product relevancy and improve the customer experience.
Art.com, an online retailer of art reproductions, has introduced a visual search feature that allows customers to find artwork based on style and content similarity. The feature, developed in partnership with Grid Dynamics, uses deep learning and image processing techniques to provide more relevant and visually similar search results.
Grid Dynamics Labs is developing an open omni-channel conversational commerce platform called Grid Genie, which aims to level the playing field for retailers in the AI market. The platform will treat different AI devices as end points and provide a seamless conversational experience across all channels.
This article discusses how online retailers can use computer vision and machine learning to build a visual similarity search engine. This engine can help customers discover similar products and improve product attribution in e-commerce catalogs.
