domain
E-commerce
E-commerce solutions
E-commerce solutions
E-commerce solutions
Search
The search tools we develop help customers find what they need quickly and easily. By using advanced technology like natural language processing, we ensure that search results are relevant and personalised for each shopper. Make sure users can effortlessly discover products that meet their needs.
Cold start search engine
In the early stages of launching a search engine, there is a challenge known as the cold start problem. This happens when there isn't much historical data available. To tackle this, we employ different algorithms to help the system get started. We use techniques like content-based filtering and tools such as Elasticsearch, visual search, and Solr to understand what users prefer and how relevant the products are.
Cold start search engine
In the early stages of launching a search engine, there is a challenge known as the cold start problem. This happens when there isn't much historical data available. To tackle this, we employ different algorithms to help the system get started. We use techniques like content-based filtering and tools such as Elasticsearch, visual search, and Solr to understand what users prefer and how relevant the products are.
Cold start search engine
In the early stages of launching a search engine, there is a challenge known as the cold start problem. This happens when there isn't much historical data available. To tackle this, we employ different algorithms to help the system get started. We use techniques like content-based filtering and tools such as Elasticsearch, visual search, and Solr to understand what users prefer and how relevant the products are.
Search services
We develop services that improve user experience by making search results more accurate and relevant. By using natural language processing and machine learning models, we evaluate what users intend and the context of their searches. This helps the search engine to improve queries and provide smart autocomplete suggestions. We also offer advanced filtering options, making it easier for customers to browse products.
Search services
We develop services that improve user experience by making search results more accurate and relevant. By using natural language processing and machine learning models, we evaluate what users intend and the context of their searches. This helps the search engine to improve queries and provide smart autocomplete suggestions. We also offer advanced filtering options, making it easier for customers to browse products.
Search services
We develop services that improve user experience by making search results more accurate and relevant. By using natural language processing and machine learning models, we evaluate what users intend and the context of their searches. This helps the search engine to improve queries and provide smart autocomplete suggestions. We also offer advanced filtering options, making it easier for customers to browse products.
Content categorisation and labelling
Proper content categorisation and labelling are essential for improving search functionality and helping customers find products quickly. We develop machine learning solutions to automatically classify and tag products based on their features. By analysing product descriptions, images, and user-generated content, we ensure accurate categorisation.
Content categorisation and labelling
Proper content categorisation and labelling are essential for improving search functionality and helping customers find products quickly. We develop machine learning solutions to automatically classify and tag products based on their features. By analysing product descriptions, images, and user-generated content, we ensure accurate categorisation.
Content categorisation and labelling
Proper content categorisation and labelling are essential for improving search functionality and helping customers find products quickly. We develop machine learning solutions to automatically classify and tag products based on their features. By analysing product descriptions, images, and user-generated content, we ensure accurate categorisation.
E-commerce solutions
E-commerce solutions
E-commerce solutions
Ranking
Enhance your product visibility with our effective ranking solutions. We analyse customer behaviour, purchasing patterns, and product performance to display the most relevant items first in your search results. Our system adapts in real time, ensuring your products remain prominent and aligned with shopper preferences.
Clickstream recommendation
Clickstream recommendation systems use real-time data on user behaviour to provide personalised product suggestions. By analysing browsing patterns, click paths, and interaction history, we create dynamic recommendations that fit individual preferences. We use machine learning techniques like FlashRank to help the system adapt to changes in user behaviour, ensuring customers receive relevant suggestions.
Clickstream recommendation
Clickstream recommendation systems use real-time data on user behaviour to provide personalised product suggestions. By analysing browsing patterns, click paths, and interaction history, we create dynamic recommendations that fit individual preferences. We use machine learning techniques like FlashRank to help the system adapt to changes in user behaviour, ensuring customers receive relevant suggestions.
Clickstream recommendation
Clickstream recommendation systems use real-time data on user behaviour to provide personalised product suggestions. By analysing browsing patterns, click paths, and interaction history, we create dynamic recommendations that fit individual preferences. We use machine learning techniques like FlashRank to help the system adapt to changes in user behaviour, ensuring customers receive relevant suggestions.
Visual search recommendations
With visual search recommendations, customers can find products using images, making the shopping experience more intuitive and engaging. Our system uses computer vision techniques to analyse images uploaded by users, helping to identify similar products in our inventory.
Visual search recommendations
With visual search recommendations, customers can find products using images, making the shopping experience more intuitive and engaging. Our system uses computer vision techniques to analyse images uploaded by users, helping to identify similar products in our inventory.
Visual search recommendations
With visual search recommendations, customers can find products using images, making the shopping experience more intuitive and engaging. Our system uses computer vision techniques to analyse images uploaded by users, helping to identify similar products in our inventory.
Text similarity search
Improve product findability by better machine understanding of language and context. We use natural language processing techniques, and modern cross-encoder systems to analyse product descriptions and user queries. This helps us identify and recommend items with similar attributes or themes.
Text similarity search
Improve product findability by better machine understanding of language and context. We use natural language processing techniques, and modern cross-encoder systems to analyse product descriptions and user queries. This helps us identify and recommend items with similar attributes or themes.
Text similarity search
Improve product findability by better machine understanding of language and context. We use natural language processing techniques, and modern cross-encoder systems to analyse product descriptions and user queries. This helps us identify and recommend items with similar attributes or themes.
Hybrid search
The hybrid search approach combines traditional keyword-based search with an understanding of visual product similarity and important data such as descriptions, prices, and clicks. By integrating structured and unstructured data, we create systems that process user queries from multiple angles, providing results that are both relevant and contextually appropriate.
Hybrid search
The hybrid search approach combines traditional keyword-based search with an understanding of visual product similarity and important data such as descriptions, prices, and clicks. By integrating structured and unstructured data, we create systems that process user queries from multiple angles, providing results that are both relevant and contextually appropriate.
Hybrid search
The hybrid search approach combines traditional keyword-based search with an understanding of visual product similarity and important data such as descriptions, prices, and clicks. By integrating structured and unstructured data, we create systems that process user queries from multiple angles, providing results that are both relevant and contextually appropriate.
E-commerce solutions
E-commerce solutions
E-commerce solutions
Recommendations
Boost customer engagement with personalised product recommendations. Analyse user preferences and interactions on your site to suggest products they are likely to love. By employing techniques that learn from both user behaviour and product features, we create a shopping experience that encourages exploration.
Recommendation systems
We create recommendation systems that analyse user behaviour, preferences, and purchase history to offer personalised product suggestions. Using collaborative filtering, content-based filtering, and other advanced machine learning methods, our recommendations adapt to users’ changing interests.
Recommendation systems
We create recommendation systems that analyse user behaviour, preferences, and purchase history to offer personalised product suggestions. Using collaborative filtering, content-based filtering, and other advanced machine learning methods, our recommendations adapt to users’ changing interests.
Recommendation systems
We create recommendation systems that analyse user behaviour, preferences, and purchase history to offer personalised product suggestions. Using collaborative filtering, content-based filtering, and other advanced machine learning methods, our recommendations adapt to users’ changing interests.
User preference analytics
By collecting data from various sources—such as browsing history, purchase patterns, and interaction metrics—we identify trends in user preferences. This enables better product recommendations and marketing strategies. Using machine learning models, we effectively segment users and predict future buying behaviour.
User preference analytics
By collecting data from various sources—such as browsing history, purchase patterns, and interaction metrics—we identify trends in user preferences. This enables better product recommendations and marketing strategies. Using machine learning models, we effectively segment users and predict future buying behaviour.
User preference analytics
By collecting data from various sources—such as browsing history, purchase patterns, and interaction metrics—we identify trends in user preferences. This enables better product recommendations and marketing strategies. Using machine learning models, we effectively segment users and predict future buying behaviour.
Let's talk with our CEO
Email: andrii.rohovyi@postdata.ai
Let's talk with our CEO
Email: andrii.rohovyi@postdata.ai
Let's talk with our CEO
Email: andrii.rohovyi@postdata.ai
Postdata. All right reserved. © 2024
Postdata. All right reserved. © 2024
Postdata. All right reserved. © 2024