Welcome to a quick overview of Coveo’s Automatic Relevance Tuning AI model ART. In this video, we'll see ART in action and learn how to quickly implement it. In this short demo, I'll show you the power of Coveo's Automatic Relevance Tuning (ART) AI model. ART is a powerful AI that automatically ranks search results when users ask questions or seek information. For example, on our demo site, if we search for how to download maps, ART retrieves the most relevant results from various sources like knowledge bases, websites, and discussions. These results are gathered from different siloed repositories. Coveo's AI scours these repositories to bring the most relevant content to the top, This is where ART excels. ART ranks results so the most relevant content appears at the top. Here we see a knowledge article, download information, a CRM case, several discussions, and support videos. It's a mix of different content types. ART learns from user interactions to automatically rank and boost the most relevant content. The AI model looks at user signals, like clicks on documents, to determine relevance and boost important documents to the top. ART continuously learns from these signals to refine search results. All of Coveo's purpose-built AI models, including ART, are easily configured in the admin interface by business users. Simply go to the machine learning tab, select model, and click on ad. Here you will find the twelve purposely built AI machine learning models that Coveo supports. Let's select the ART model and enable it through Coveo's guided steps. This model learns from user interaction signals. You can specify the time frame for these events to optimize the model. Coveo offers best practice recommendations for this, which we will select. Next, you can filter signals by criteria such as country or device, offering flexibility in training the model. After naming your model, it's ready to go. The model is now building, and can power a robust search experience in your UI. Enhance your knowledge discovery with Coveo’s ART model. Schedule a call with our AI experts today!

Refine Search Result Relevance with Coveo’s Automatic Relevance Tuning Model

Overview

Chapters

Transcript

Watch and learn how the Automatic Relevance Tuning (ART) AI model can improve search experiences, ensuring users find the most relevant information quickly and effortlessly.

Watch now to discover:

The importance of Automatic Relevance Tuning in search functionality: Coveo’s ART model automatically adjusts search results, ensuring the most relevant content is prioritized.
How to quickly set up and refine your ART model: Learn how to configure the ART model within Coveo’s admin interface and fine-tune it based on real-time user interactions.
The benefits of contextual and relevant recommendations: ART continuously learns from user signals like clicks and searches, refining its algorithms to deliver more accurate results over time.

Why You Need Automatic Relevance Tuning

Coveo’s Automatic Relevance Tuning (ART) is a game-changer for search functionality and user experience. Unlike traditional search engines that merely pull up results, ART continuously learns from user interactions to refine and prioritize content that truly matters.

Key benefits of Coveo’s ART model:

Superior Search Relevance: ART dynamically ranks search results by analyzing user signals, ensuring that the most pertinent information is always at the top, reducing time spent searching and boosting user satisfaction.
Boosted Efficiency: By intuitively guiding users to the exact information they need, ART streamlines workflows, significantly improving overall productivity and operational efficiency.
Improved User Satisfaction: With ART’s ability to refine and prioritize search results based on user behavior, your business can better anticipate user needs and guide them toward relevant products, content, or services, boosting conversion rates and driving revenue growth.