How AI Finds Similar Tiles from a Photo: Complete Guide

Introduction

Customers often arrive with inspiration photos and expect instant matches. Traditional search fails because design is visual, not textual.

Artificial intelligence closes this gap by interpreting patterns, colors, and textures to deliver accurate tile recommendations within seconds.

Why Traditional Search Fails

Product metadata rarely captures the nuance of patterns or color variations, leading to poor search results and lost sales opportunities.

Customers struggle with terminology, while sales teams waste time navigating catalogs instead of providing consultative support.

How AxoVision Solves the Problem

AxoVision analyses each image using deep learning models trained on thousands of tile designs to understand complex pattern geometry and color palettes.

With a simple photo upload, the system returns relevant results ranked by similarity, enabling customers to make confident purchase decisions quickly.

Implementation Checklist

Digitize your catalog with high-quality imagery and consistent metadata.

Connect AxoVision via API to your e-commerce platform or internal inventory tools.

Train sales teams to incorporate visual search into their showroom workflows.

Key Takeaways

Visual search increases conversion rates by up to 40% for tile retailers embracing AI-driven discovery.

Early adopters build defensible competitive advantages and gather rich data on customer design preferences.