Reimagining Product Discovery Through Artificial Intelligence
Challenge
Finding the correct repair part is one of the most frustrating moments in the customer journey. Product names are often unfamiliar, visual differences can be subtle, and traditional search methods create friction that can lead to abandoned purchases and customer frustration.
Strategy
I identified an opportunity to simplify product discovery by allowing customers to search visually rather than relying on technical product knowledge.
The vision was straightforward:
Take a photo. Find the right part.
Execution
I led the ideation and development of the Danco AI Part Finder, an intelligent visual search tool trained on more than 30,000 product images.
The project required extensive model training, testing, refinement, and cross-functional collaboration to achieve 98% product retrieval accuracy.
Following development, the experience expanded beyond Danco’s digital ecosystem into customized interfaces supporting Lowe’s, The Home Depot, Ace Hardware and Menards, extending the technology across major national retail environments.
RESULTS
187K+
TOTAL USERS
847K+
PAGEVIEWS
98%
MATCH ACCURACY
5
DIGITAL INTERFACES
The AI-powered experience reached 187,000+ users and generated more than 847,000 pageviews across Danco and national retail partner interfaces, transforming a complex product search into a scalable digital customer experience.