Visual Search

Visual Search is a technology that allows users to search for visual content by simply uploading an image or taking a photo. The Visual Search application will provide visually similar or related results. Therefore, it has the potential to revolutionize e-commerce. Visual Search has gained significant attention in recent years due to its ability to improve user experience and increase revenue for e-commerce companies.

How it works?

This technology helps users find clothing that matches their style and preferences by recommending similar items. Not only one thing but many recognized in the picture. The system returns similar products based on visual similarity. Thanks to that, it allows users to find similar products to the ones they are interested in, even if they don’t know the product name or brand.

Benefits of visual search for your business

User Experience

Visual Search allows users to easily and quickly find the products they are looking for. The user receives similar items that a given store has in its assortment. This functionality improves their overall experience on the website or app. Moreover, it provides a more intuitive search experience that can increase engagement and conversion rates.

Personalization

Visual Search technology can provide customized search results based on the user’s search history and preferences. Users are likely to use tools that immediately provide personalized and filtered search results. Visual Search can help businesses to offer more targeted and customized products. It improves the shopping experience.

Search efficiency and relevance

Visual Search can improve search accuracy and efficiency. It reduces search time and increases the chances of finding the desired product or service. In addition, Visual Search provides more relevant results because the algorithms can recognize product details and features, such as color and shape, which allows you to match the results to the user’s preferences precisely.

Increased conversions

Users who receive immediate results, as expected, are more likely to make a purchase faster than other product search methods. This helps to build customer satisfaction and loyalty. In addition, increasing the time spent on the site positively affects the site’s position in search engine results, which can help businesses reduce bounce rates.

Implementation

Our Visual Search solution consists of two sequential models: object detection and visual search models. First, object detection finds the objects in the shop’s catalog on the provided image (e.g., shoes, bags). Then, the visual search model returns the most similar products to the selected object. Finally, the results can be presented in a carousel of the most similar items that may be shown on the product’s site. This way, users can easily find personalized items in the shop product catalog.

Implementing Visual Search requires several components to create an efficient and effective system. The key features required for Visual Search implementation are:

Products catalog 

The database that stores images of products and information about products, ex. ids, image URLs, site URLs, product types, descriptions, metadata, etc.

Indexer

The component processes data, writes information to the database and updates the product set every few hours.

Image recognition algorithm

The model detects objects on the queried image and finds the most similar item to the selected crop across the product set.

Conclusion 

In conclusion, our Visual Search technology has many benefits. It can improve search accuracy and efficiency, reduce search time, and provide personalized search results. Enhancing the user experience, personalization, and improving search results’ accuracy helps increase customer engagement and conversion rates. In addition, modern e-commerce solutions allow you to stand out from the competition and build a positive image of a contemporary company that focuses on quality and customer satisfaction.

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