Mid-sized retail company with both online and offline sales channels
Retail sector offering consumer electronics, home goods, and lifestyle products
Multi-channel product sales across growing regional operations with expanding product catalog
Replace manual research methods for monitoring pricing and product availability on shopping portals with automated system that improves demand forecasting and reduces operational overhead
No reliable method to monitor pricing or product positioning across shopping portals regularly
Information gathering was slow and often outdated by the time it reached decision-makers
Demand forecasting relied heavily on internal sales history, ignoring external factors like competitor pricing, seasonal shifts, or emerging product trends
Forecasting gaps led to frequent overstocking and missed opportunities from stockouts
Teams manually extracted product data from multiple websites for analysis, draining time and resources while introducing human error
Manual monitoring wouldn't scale with expansion plans for growing product volumes, multiple geographies, and evolving competitive dynamics
System extracted product descriptions, pricing, availability, and vendor details from shopping portals automatically
Provided continuous access to live product and pricing data across multiple marketplaces
Combined internal sales data with real-time market data for more complete view and accurate demand predictions
Ran without human input, eliminating repetitive manual tasks and reducing errors
Bots could run on multiple machines at once and integrate with additional shopping platforms without rework
Solution specifically targeted these high-priority shopping portals for data collection
Created workflows to automate data extraction process through intelligent bots that collect and process product data in real time
Scheduled and managed bot operations, ensuring continuous unattended automation with real-time monitoring, performance tracking, and exception handling
Custom API integrations enabled seamless and accurate extraction of product data for real-time pricing, availability, and product details
Hosted solution on cloud to ensure scalability and flexibility, supporting large data volumes with high availability
Enabled parallel execution for faster data processing and support for larger data volumes
Automated bots removed human errors in data entry and order management completely
Teams stopped spending time on repetitive data extraction tasks across multiple websites
Automation reduced the need for manual tasks, freeing up resources for strategic work
Real-time insights enabled better pricing and inventory strategy adjustments
Accurate product data and smoother workflows improved overall efficiency
RPA eliminated human errors in data entry and order management, ensuring accurate product data
Automation reduced the need for manual tasks, cutting operational costs and freeing resources for strategic activities
Real-time insights from automated data extraction allowed the client to adjust pricing and inventory strategies
Access to external market factors alongside internal sales history prevented stock imbalances
System handled growing product volumes and additional platforms as business expanded
Smoother experience kept customers returning for repeat business
You’re one step away from building great software. This case study will help you learn more about how Simform helps successful companies extend their tech teams.
Discover cutting-edge ideas and insights from the world of technology and business.
You’re one step away from building great software. This case study will help you learn more about how Simform helps successful companies extend their tech teams.
