Coveo Cloud

Search, recommendation, & personalization AI cloud platform for intelligent shopping experiences.

Integration Type

Search Solutions

Developed By


Coveo is a cloud native platform providing search, recommendation, and personalization to power intelligent shopping & buying experiences.

Coveo unifies data from any source and learns from every interaction across channels to tailor experiences that increase conversion & average order value, lower costs to serve, and drive customer satisfaction.

Coveo also arms merchandisers with the automation and insight needed to reduce manual effort and optimize shopping experiences that bring the most value to the business.

Simply stated Coveo provides AI on-tap for every part of the ecommerce journey.

Capabilities Highlight

AI-powered search to help shoppers find what they need faster

Coveo is able to analyze and index complex Ecommerce catalogs creating a proxy catalog that is optimized for searching. Coveo brings together the product, the variance, and the availability so that your ecommerce search has no friction. The AI cloud platform then leverages data and shoppers’ behavior to deliver relevant search results across web, mobile, chat and beyond.

Intelligent Query Suggestions to improve catalog discoverability

Coveo proposes options to shoppers as they type in the search box, leveraging Machine Learning so that suggestions continuously evolve and adjust with trends and the language of your shoppers. 

Dynamic Navigation to optimize browsing experiences

Coveo’s dynamic navigation capability leverages Machine Learning to automatically propose or re-order relevant filters, values and categories. This means Coveo can automatically:

1) Select or boost categories based on a shoppers’ patterns and extracted catalog intelligence.

2) Show the most relevant facets/filters for each category selected and prioritize the order of those filters so that the most relevant ones appear first.

3) Reorder the values within each of the facets/filters shown so that the most relevant ones appear first.

Fast Personalization to show relevant products quickly even for anonymous shoppers

Personalization is hard to get right. Coveo leverages Machine Learning algorithms and product embeddings to understand a shopper's interactions with products over time, it can then determine their preferences and intent within a few clicks, even on anonymous shoppers. 

Recommendation Models to maximize the value of each shopping cart

Coveo machine learning models can be used to automatically recommend the most relevant product to shoppers based on their browsing and buying behavior, what’s already in their cart, or what’s often viewed and bought together.

Intelligent Merchandising to optimize for the business

Coveo enables you to boost specific products and content that are both relevant to the shopper and to the business. You can leverage boost-and-bury rules and sticky positions to promote products based on margin, arrival data, stock availability, or other relevant attributes.

Search Analytics to gain insight into the entire shopper journey and track revenue attribution

Collecting the right data about how shoppers discover, and buy is crucial to optimizing your digital storefront. Coveo offers a powerful set of analytics and dashboards to understand trends and directly measure how search impacts business goals, such as conversion, average order value, and revenues.

Description of the Integration

Tech-first companies have taught customers to demand best-in-class search experiences. Coveo empowers enterprises to thrive in the experience age through delivering unique experiences that are unified, relevant and valuable. This is done by leveraging Coveo’s proprietary Machine Learning and unlocking the value of products’ and customers’ data.

Coveo leverages different types of information from a catalog (i.e. products, variants and availability) to make products discoverable. This article serves as an introduction and high-level guide to indexing products from a catalog. Yet, Coveo can also index more than product data: structured product catalog data can blend with unstructured content (e.g. community reviews and YouTube videos).

Coveo also tracks different types of commerce events (e.g. page views, products clicked, products added to cart, purchases) to provide machine learning with inputs to learn from and to help predict user behavior. This article explains in detail how the script leveraging the syntax of the Google analytics.js script is being used.

Coveo maps product data with user behavior and leverages it in its out-of-the-box Machine Learning models. More precisely, Coveo uses AI to tailor every aspect of the customer experience across different touchpoints, from typo tolerant and predictive query suggestions to dynamic and intelligent facets, and from an optimized ranking of search results to tailored and individualized product recommendations. This short guide reviews the default setup of Coveo Machine Learning models.

It is possible to surface content either using the Coveo™ JavaScript Search Framework or the Coveo Search API.

The former option provides a simple way to implement our full-featured search interface that includes machine-learning-ready usage analytics. This article serves as an introduction to creating a search interface with the Javascript Search Framework. The Coveo JavaScript Search Framework offers a large collection of components (e.g., Searchbox, ResultList, Facet, etc.) and utilities to help you create, customize, and maintain end-user interfaces relying on the Coveo Cloud Platform. Among other things, JavaScript Search Framework end-user interfaces can automatically handle building and sending queries, displaying query results, and logging appropriate usage analytics events. For more in-depth implementation guidelines, see Leveraging the Coveo JavaScript Search Framework.

Alternatively, it is possible to use Coveo’s API-first approach to building search interfaces, thus decoupling the presentation layer from the component. This option offers more flexibility in design and enables developers to easily integrate and develop on the Coveo platform. More information can be found by consulting the documentation on Building a Search Interface Using the Coveo Search API

Coveo also leverages the same content and data to create recommendation models designed to support multiple use cases (e.g. cart recommendations, homepage recommendations). More information on the different use cases can be found in this article. Coveo’s Machine Learning takes advantage of usage analytics to suggest relevant products to end users based on their past and present interactions with a Coveo-powered commerce implementation. Relevant content will be surfaced with our Search API or our JavaScript framework.