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From generating realistic product previews and re-contextualizing products in various scenarios, to simplifying product attribution and crafting optimized SEO metadata, generative AI is leaving its mark across an array of domains.
Many retailers are adopting a composable approach to their e-commerce platforms, which allows them to select best-of-breed software components and combine them into a flexible and scalable solution that can easily adapt to changing business needs. This composable architecture, known as MACH (microservices, API-first, cloud-native, and headless), offers retailers the ability to quickly roll out new features and customer experiences, experiment with emerging technologies, and stay competitive in the market.
Knowde implemented a new search system that improved search relevance and customer engagement metrics on their digital marketplace for ingredients and chemistry.
Consumer demand for personalized digital shopping experiences has skyrocketed over the last few years, and constant change is to be expected. Accelerate migration to Google Cloud Retail Search with our Starter Kit.
The article discusses the concept of composable commerce and the integration of Google Cloud Retail Search into the commercetools platform, providing retailers with advanced product search capabilities and personalized product discovery experiences.
This white paper discusses the evolution of omnichannel digital commerce and highlights the trends that will shape its future in 2022. It emphasizes the importance of leveraging advanced technology, such as composable commerce platforms and AI-powered product discovery, to create exceptional customer experiences and stay competitive in the consumer-driven era.
Grid Dynamics helped a retailer of tableware and jewelry implement a visual search solution, reducing product search times from days to seconds.
We share our experience how the problem of coin recognition was solved with deep learning. The whole process is described in details: dataset collection and preparation, segmentation model training, embedder training and evaluation and finally vector search.
This article discusses the importance of query parsing in e-commerce search engines and introduces the concept of concept-oriented query parsing using a semantic graph. It explains how this approach can improve the accuracy and relevance of search results in e-commerce applications.
