Inspired by Coveo’s AI-powered search & recommendation platform

Disclaimer: This is a hypothetical case study created for portfolio purposes. It demonstrates product thinking, user empathy, and solution design inspired by real-world UX patterns. It is not affiliated with or an evaluation of Coveo's current strategy.

🏢 Company Overview: Coveo

Coveo is a leading Canadian company that provides an AI-powered search and recommendation platform. It serves enterprise e-commerce, customer service, and knowledge management teams, offering personalized, intent-driven digital experiences through real-time data and machine learning.

👤 User Persona

Emily, 34, is a skincare enthusiast who frequently shops online for specific products. She expects fast, accurate results when using search terms like:

"fragrance-free moisturizer for sensitive skin"

❗ Problem

When users like Emily search using specific, long-tail queries, they often receive irrelevant or overly broad results — leading to:

• Increased friction in the purchase journey
• Erosion of trust in the platform
• Increased bounce and drop-off rates

Why this happens:

• Search systems don’t always recognize natural language or synonyms
• Product tags are not aligned with how users describe their needs
• Search AI lacks real-time adaptation to query trends