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Visual Recommendation System

Image-based recommendation system which recommends products based on their visual similarity

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OUR TRUSTED PARTNERS
Magento An Adobe Company Adobe AWS Big Commerce Google Cloud Hyva Amasty Centuria Ergonode Voucherify

How does it work?

We are using transfer learning from the field of image classification to extract features from new data.

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15
+
YEARS ON THE MARKET
100
k+
TASKS COMPLETED
100
+
PROJECTS DELIVERED

What is transfer learning?

Transfer learning involves applying knowledge from one field in another field. In our recommendation system, we are using an already trained model and training only the top layers to adapt to new cases.
Skip to the main content. Snowdog logo Services Platforms Our Work BlogAbout Us Let's Talk Development eCommerce Development Mobile App Development Custom Functionality System Integrations Headless/Composable Hyvä/Sparq Design Information Architecture UX/UI Accessibility Service Category eCommerce Strategy Consulting DevOps Consulting Replace this text Tech Stack Consulting Magento Open Source Adobe Commerce Hyvä commercetools BigCommerce B2B ClearBags Sanpol Mago Group Packaging Price Tacony B2C Focus Camera N69 Eobuwie Biuro Paczka Time Trend High Point Scientific Government & NGO UAM GO Marketplace Social Native Visual Recommendation System Image-based recommendation system which recommends products based on their visual similarity Let's Talk OUR TRUSTED PARTNERS How does it work? We are using transfer learning from the field of image classification to extract features from new data. Let's Talk sd ai page pic What is transfer learning? Transfer learning involves applying knowledge from one field in another field. In our recommendation system, we are using an already trained model and training only the top layers to adapt to new cases. Advantages There is no need for a priori data thanks to transfer learning. The only required component from stores is a database of the product images to feed the model, so it's possible to build a working demo of this recommendation system for your store within a day. Development Opportunities Adding filtering based on attributes would enhance the performance of the system. A product could be improved in the future, given feedback that is collected based on user clicks on the website. Items clicked from recommendations would be considered successfully recommended items — therefore, the system could learn from user engagement with the given recommendations. Applications This system can be used to recommend visually similar products when looking for alternatives to the currently viewed item. It's perfect for a starting point in behavioral recommendations when there is not sufficient data gathered yet to suggest items based on a user's search history. Let's Talk Let's work together Tell us more about your project and find out how we can help you. Let's Talk Graphic. of a businesswoman Snowdog logo hello@snow.dog Mostowa 11, 61-854 Poznań, Poland SERVICES eCommerce Development Customer Experience Mobile App Development DevOps Consulting COMPANY About Us Blog Career Accessibility StatementPrivacy Policy & Cookies © 2025 Snowdog Facebook X Instagram LinkedinYouTube VAT-ID: PL7831703995 KRS: 0000480529 REGON: 302537491 Logo Funduszy Europejskich oraz Programu RegionalnegoLogo Samorządu Województwa WielkopolskiegoLogo Unii Europejskiej oraz Europejskiego Funduszu Rozwoju Regionalnego Return to top
Advantages
There is no need for a priori data thanks to transfer learning. The only required component from stores is a database of the product images to feed the model, so it's possible to build a working demo of this recommendation system for your store within a day.
Development Opportunities icon
Development Opportunities
Adding filtering based on attributes would enhance the performance of the system. A product could be improved in the future, given feedback that is collected based on user clicks on the website. Items clicked from recommendations would be considered successfully recommended items — therefore, the system could learn from user engagement with the given recommendations.
Applications
Applications
This system can be used to recommend visually similar products when looking for alternatives to the currently viewed item. It's perfect for a starting point in behavioral recommendations when there is not sufficient data gathered yet to suggest items based on a user's search history.

Let's work together

Tell us more about your project and find out how we can help you.

Let's Talk
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