For whom
Online retailers, trading platforms, B2B and B2C platforms, startups.
Technologies used
OpenCart, Magento, PHP, JavaScript, Python, React, React Native, AI/ML, Big Data, API integration.
Challenges
Creation of convenient and functional online stores, automation of sales processes, improving user experience, increasing conversions and optimizing assortment.
Application examples
A feature-rich online store for a large retailer
Problem Description: A large online retailer approached us with a request to develop a multifunctional online store. The main problems were inefficient inventory management, difficulties in automating the distribution of availability notifications and low conversion rate.
Solution: We conducted a detailed analysis of the client’s business processes and developed a Magento-based solution with integration of stock control system and automatic notifications. Using AI/ML, we implemented a recommendation system that analyzes user behavior and offers personalized products.
Result: The implementation took 6 months. As a result, the client improved inventory management and automated sales processes, resulting in a 25% increase in revenue. Personalized recommendations increased conversion by 20% and increased average check by 15%. Warehouse management costs also decreased by 20%.
Building a platform for an e-commerce startup
Problem Description: An e-commerce startup approached us with a request to build a platform to sell niche products. Key challenges included the lack of a sales platform and the need to create a unique user experience to attract customers.
Solution: We developed a custom OpenCart-based solution optimized for the startup’s needs. We implemented a system of personalized product recommendations using AI/ML, as well as Big Data analysis for demand forecasting and assortment optimization. Social media integration increased user engagement.
Result: The implementation took 4 months. As a result, the startup successfully launched its platform and increased its user base by 150% in the first three months. Personalized product recommendations led to a 30% increase in average check, and big data analytics allowed for assortment optimization, which reduced costs by 20%.
B2B commerce platform
Problem Description: A B2B company approached us to develop a platform to automate trade processes between businesses. Key challenges included complex and inefficient order management processes and lack of integration with existing ERP systems.
Solution: We developed a PHP and React-based platform that integrated with the client’s existing ERP systems. The platform included automation of the ordering process, inventory management, and invoicing. Using AI/ML, we implemented a demand forecasting system that allowed for more accurate inventory management and reduced the risk of shortages or surpluses.
Result: The implementation took 5 months. As a result, the company reduced order processing time by 40%, reduced operating costs by 25%, and improved the overall efficiency of sales processes. AI/ML demand forecasting reduced costs by 15% and increased customer satisfaction through consistent product availability.