Introduction
From smartphones to in-store kiosks, visual search powered by artificial intelligence has revolutionized the way we discover, research, and buy products. By leveraging computer vision and machine learning algorithms, visual search allows consumers to get information about items simply by snapping photos or taking screenshots. This emerging technology is creating more personalized, streamlined shopping experiences while also providing brands with new opportunities to engage customers.
According to a 2024 Forrester Research report, over half of retailers are currently investing in visual search and computer vision capabilities. As these innovations continue to evolve, visual engagement will become a key component of retail and ecommerce.
TL;DR
Visual search uses computer vision and AI to identify objects, products, logos, etc. in images and video. This allows for better product discovery, personalized recommendations, and frictionless shopping experiences.
How Visual Search Works
Visual search relies on advanced computer vision algorithms that can analyze the contents of images and videos. The AI models detect and recognize various elements like objects, products, scenes, text, logos and more. The visual data is then matched against a company's product catalogs and databases to return the most relevant results and recommendations.
For example, if a user takes a picture of a dress they like, the algorithm may identify the garment's colors, pattern, and style. It then suggests similar dresses from affiliated brands. If a logo is detected, the technology can link to that brand's online store or product information.
Key Benefits of Visual Search
For consumers, visual search makes finding products easier and more engaging. Instead of typing keyword searches, shoppers can simply snap a picture or screenshot of an item to find where to buy it. Visual search also enables more personalized recommendations based on individual tastes.
For brands, visual search provides a new channel for consumers to discover and engage with their products through images and videos. According to a 2023 Business Insider article, 90% of all online engagement is now visual. Visual search allows brands to tap into this demand for visual content while collecting valuable data on customer preferences.
In-store, visual search powers next-generation shopping experiences. Retailers like Home Depot now use computer vision kiosks to help customers identify products by sight. Visual search also enables mobile features like shoppable Instagram posts.
Use Cases and Applications
Here are some of the most common visual search applications:
- Logo Detection: Computer vision can instantly recognize logos in social media posts, videos, and other visual content. This helps promote brand awareness and connections.
- Ecommerce: Online retailers use visual search with product image databases to enable frictionless browsing and checkout.
- Social Media & Influencer Marketing: Shoppable image posts and stories leverage visual search to make influencer content more interactive.
- In-Store Product Recognition: Retailers are rolling out computer vision kiosks and mobile apps that ID products visually to assist customers.
Conclusion
Visual search stands to revolutionize retail, ecommerce, marketing, and more by tapping into the power of images. As computer vision and AI advance, visual engagement will become more important for brands looking to connect with consumers. For shoppers, visual search means better product discovery, recommendations, and mobile shopping experiences. As this technology continues to evolve over the coming years, visual search will cement itself as a key component of the future of retail and ecommerce.
