My main use case for Coveo is on one of my e-commerce websites where I have used it as a search platform that allows users to search for products, filter results, and view metadata and details. I have integrated Coveo into my web application. A specific example of how Coveo helps users on my e-commerce site is that it has streamlined website searches significantly. We have a large catalog of products, and each customer is categorized by certain preferences. Coveo has helped us identify those preferences and show specific products to specific users. It is AI-powered, and it is remarkable how it works behind the scenes.
Sitecore Developer at a university with 201-500 employees
Real User
Top 20
Apr 6, 2026
My main use case for Coveo is that I use it as a search engine for my websites. A quick specific example of how I use Coveo as a search engine for my websites is that we mostly used it for article pages; for example, if we need to sort a latest article, we send the entire article data to Coveo, which filters it for us and gives the exact result based on the rules we provided for Coveo. We have N number of customizations and rules for Coveo, so based on these rules, Coveo sorts out the data. Coveo provides a search engine experience that is superior when compared to the other search engines available in the market as of now.
Senior Staff Engineer at a tech vendor with 10,001+ employees
MSP
Top 10
Apr 3, 2026
My main use case for Coveo involves working on SAP Commerce technology where we built an e-commerce solution for one of our clients who faced issues while performing smart product searches on the site. Coveo provides AI-driven search results and proper recommendations based on customer interaction and context, which is very beneficial for us because it improves our order conversion rate, allowing customers to find the exact products they want and see similar products, greatly increasing upselling. A specific example of how Coveo helped solve the smart search issue for our client is that it offers personalized recommendations based on customer interaction rather than global recommendations. We send an event to Coveo, and based on that event for a particular user, Coveo sends personalized recommendations, which is crucial as customers searching for products receive recommendations based on what other similar users have purchased. Coveo's flexibility allows us to create recommendations based on strategies like recently viewed or most purchased products, and it integrates easily with SAP Commerce, making it straightforward for us to index all products in Coveo, which uses a machine learning model. We can configure a search result via a query configuration pipeline, which adds to the flexibility and intuitiveness of using Coveo as it continually updates with new features like real-time facet management that requires no technical knowledge to implement. Coveo greatly helps our customers, as we use it not only for product search but also for content search. Its indexing capabilities are versatile, utilizing various approaches like pull or push methods, and its AI model effectively responds to user interactions. Coveo enables us to configure all aspects of the search page, from facet ordering and priorities to sorting criteria, which can be done easily through the customer merchandising hub, enhancing workflow efficiency and increasing customer satisfaction as users receive relevant search results effortlessly.
Senior Software Engineer at a recreational facilities/services company with 501-1,000 employees
Real User
Top 10
Apr 3, 2026
My main use case for Coveo is that we are using it for search as well as recommendation perspective. We are trying to index our content pages, products, and then we are utilizing that on our product listing pages for recommendation, search, and then auto-suggest, everything that we have in our e-commerce site. A specific example of how Coveo is used on one of our product listing pages is that we have products that we are currently indexing in Coveo. After indexing, we are trying to display those product attributes and everything in our search box. We put some search text over there and then it is returning a full list of products that we have. Apart from that for our content pages as well, we are trying to search some newsletter or something and then it is returning those results in our listing pages. Coveo is currently offering exceptional flexibility, integrating easily with any enterprise stack. Its user-friendly interface ensures a low learning curve for functional teams, while its native AI/ML engine delivers superior search and recommendations. With Coveo, business users can independently manage search rules to drive better customer outcomes with minimum manual effort.
Coveo delivers AI-powered search and relevance solutions, enhancing information retrieval and personalization across digital experiences. It leverages AI to ensure businesses provide highly relevant content efficiently.Coveo integrates advanced AI algorithms to improve search capabilities, driving user engagement and customer satisfaction through personalized digital interactions. With its machine learning models, Coveo can dynamically tailor content suggestions, optimizing the user journey...
My main use case for Coveo is on one of my e-commerce websites where I have used it as a search platform that allows users to search for products, filter results, and view metadata and details. I have integrated Coveo into my web application. A specific example of how Coveo helps users on my e-commerce site is that it has streamlined website searches significantly. We have a large catalog of products, and each customer is categorized by certain preferences. Coveo has helped us identify those preferences and show specific products to specific users. It is AI-powered, and it is remarkable how it works behind the scenes.
My main use case for Coveo is that I use it as a search engine for my websites. A quick specific example of how I use Coveo as a search engine for my websites is that we mostly used it for article pages; for example, if we need to sort a latest article, we send the entire article data to Coveo, which filters it for us and gives the exact result based on the rules we provided for Coveo. We have N number of customizations and rules for Coveo, so based on these rules, Coveo sorts out the data. Coveo provides a search engine experience that is superior when compared to the other search engines available in the market as of now.
My main use case for Coveo involves working on SAP Commerce technology where we built an e-commerce solution for one of our clients who faced issues while performing smart product searches on the site. Coveo provides AI-driven search results and proper recommendations based on customer interaction and context, which is very beneficial for us because it improves our order conversion rate, allowing customers to find the exact products they want and see similar products, greatly increasing upselling. A specific example of how Coveo helped solve the smart search issue for our client is that it offers personalized recommendations based on customer interaction rather than global recommendations. We send an event to Coveo, and based on that event for a particular user, Coveo sends personalized recommendations, which is crucial as customers searching for products receive recommendations based on what other similar users have purchased. Coveo's flexibility allows us to create recommendations based on strategies like recently viewed or most purchased products, and it integrates easily with SAP Commerce, making it straightforward for us to index all products in Coveo, which uses a machine learning model. We can configure a search result via a query configuration pipeline, which adds to the flexibility and intuitiveness of using Coveo as it continually updates with new features like real-time facet management that requires no technical knowledge to implement. Coveo greatly helps our customers, as we use it not only for product search but also for content search. Its indexing capabilities are versatile, utilizing various approaches like pull or push methods, and its AI model effectively responds to user interactions. Coveo enables us to configure all aspects of the search page, from facet ordering and priorities to sorting criteria, which can be done easily through the customer merchandising hub, enhancing workflow efficiency and increasing customer satisfaction as users receive relevant search results effortlessly.
My main use case for Coveo is that we are using it for search as well as recommendation perspective. We are trying to index our content pages, products, and then we are utilizing that on our product listing pages for recommendation, search, and then auto-suggest, everything that we have in our e-commerce site. A specific example of how Coveo is used on one of our product listing pages is that we have products that we are currently indexing in Coveo. After indexing, we are trying to display those product attributes and everything in our search box. We put some search text over there and then it is returning a full list of products that we have. Apart from that for our content pages as well, we are trying to search some newsletter or something and then it is returning those results in our listing pages. Coveo is currently offering exceptional flexibility, integrating easily with any enterprise stack. Its user-friendly interface ensures a low learning curve for functional teams, while its native AI/ML engine delivers superior search and recommendations. With Coveo, business users can independently manage search rules to drive better customer outcomes with minimum manual effort.