6 min

August 15, 2023

Visual Search - a revolution in e-commerce

E-commerce has become an integral part of life in modern society, and online shopping is becoming increasingly popular. However, although many e-commerce platforms offer advanced text search options, traditional methods can still be challenging for some customers. This is where "Visual Search" (visual search) - an innovative, promising technology that has the potential to transform the way people browse and buy products online - enters the scene.

What is Visual Search?

Visual Search is an advanced tool based on artificial intelligence ( AI) and deep learning that allows customers to search online stores using images rather than traditional keywords. Visual Search allows users to upload an image of a product or a portion of a product, and then automatically finds similar or identical products available in the store.

How does Visual Search work?

Visual Search - uses advanced algorithms and technologies based on artificial intelligence and machine learning to enable computers to "understand" and analyze visual content.

The main steps and principles by which the Visual Search mechanism works:

Extraction and analysis of visual features:

First, an image is divided into multiple areas, and each area is analyzed to extract visual features such as colors, shapes, textures, contours, patterns and other characteristic elements. These features form a unique "fingerprint" or "vector" for each pattern.

Creating a database:

The extracted feature vectors are stored in a database, allowing new images to be compared with existing ones to determine the degree of similarity.

Machine learning:

The Visual Search engine uses machine learning techniques such as neural networks, deep learning and other algorithms to learn from large amounts of data to improve search accuracy and efficiency.

Comparison and ranking:

when a user uploads an image to Visual Search, its feature vector is compared with vectors of other images in the database. Using various metrics and similarity algorithms, the system determines how similar the corresponding vectors are to each other and ranks the search results.

Presentation of results:

Based on the rankings, the system presents search results to the user, including similar or identical images, information about recognized objects, products or places, and other related queries.

Feedback and improvement:

The Visual Search engine can also learn from user feedback, allowing it to improve results and become more precise and functional over time.

Google Lens

One such technology is Google Lens. It's a technology developed by Google that uses artificial intelligence and computer vision to recognize objects and information in images, both in real time and in pictures stored in the device's memory. Google Lens was unveiled in 2017 and is available as part of the Google Photos app on mobile devices, and is also integrated with Google Assistant and Google Search.

Google Lens' main features include:

Object recognition

Google Lens can identify a variety of objects, such as animals, plants, places, logos, products and more, simply by pointing the device's camera at the object.

Text recognition

One of the most useful features of Google Lens is the ability to scan text in photos and translate it into another language or copy it for further use.

Recognition of QR codes and barcodes

Lens can read QR codes and barcodes, providing information about products, coupon offers, contact information, social media referrals, etc.

Style and product recognition

If you like a trendy piece of clothing or furniture, but don't know how to find it, Google Lens can help identify a style, brand or similar product and display product recommendations.

Search for information about objects and places

You can learn more about landmarks, buildings, monuments and other places of interest by simply pointing your camera at the desired location.

Recognizing works of art

If you are standing in front of a painting or other work of art and would like information about it, Google Lens can help identify the author and title of the work.

Advantages of Visual Search in e-commerce

Speed and convenience

Visual search provides users with a quick and easy way to find the products they are interested in. Instead of spending time entering text queries, customers can simply upload a picture of a product they found somewhere on a website or in real life, greatly speeding up the search process. This is especially beneficial for customers who aren't sure how to accurately describe a product, or for those who want to find exact patterns or styles but have difficulty with verbal descriptions.

Improving the customer experience

Traditional keyword-based search methods can be frustrating and limiting for customers. Inappropriate keywords or insufficiently accurate product descriptions can lead to missing relevant results or inappropriate suggestions. Visual Search eliminates these barriers by allowing customers to find products based on what they have seen or what they like. This personalized approach to shopping can significantly increase customer satisfaction.

Increased conversion

The ability to use Visual Search can significantly affect the Conversion Rate of online stores. Customers who can quickly and easily find what they are looking for are more likely to purchase. With a more intuitive and interactive search process, customers can more easily find the right products, leading to more transactions.


Today's e-commerce market is extremely competitive, and providing an exceptional customer experience can be a key asset. Stores that implement modern technologies, such as visual search, can stand out from the competition, gain a significant advantage and attract more customers thereby increasing revenue. These are investments that can attract new users and increase loyalty and trust among existing customers.

Discovering new products

Visual search allows customers to discover new products based on images that may interest them. If a customer likes a particular product feature, he or she can search online for similar options that he or she may have previously missed. This allows more discovery of a store's assortment and can lead to more spontaneous purchases.


Developments in artificial intelligence and image processing technologies are opening up new prospects for Visual Search. The more advanced these technologies become, the more accurate and effective search mechanisms become. Introducing such a feature into mobile apps allows users to instantly scan products they see in the real world and find them in an online store. This makes it possible to create a more personalized shopping experience. Visual Search capabilities are also being widely used in fashion, interior design and other industries that benefit from identifying and searching patterns and shapes.

In summary, the emerging Visual Search technology has the potential to revolutionize e-commerce and the way consumers interact with products online. By facilitating the process of searching and identifying products, it can help increase sales, customer satisfaction and customization of offerings.

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