Automating Data Extraction and Demand Forecasting for Retail Efficiency
A leading global retailer struggled with accurate demand forecasting and efficient order management across hundreds of stores and multiple e-commerce platforms. They faced challenges with manual data collection, slow order processing, and price tracking.
INTECH implemented a Robotic Process Automation (RPA) solution using UiPath to automate data extraction from shopping portals like Amazon and Alibaba. This helped the retailer forecast demand more accurately, cut costs, and increase revenue by streamlining operations.
The client is a mid-sized retail company with both online and offline sales channels, offering consumer electronics, home goods, and lifestyle products. As their product catalog grew and regional operations expanded, tracking competitor pricing and forecasting demand across hundreds of SKUs became increasingly difficult.
The team relied heavily on manual research to monitor pricing and product availability on shopping portals. This led to missed opportunities, overstocking, and pricing mismatches.
As competition intensified in the online retail market, the client struggled to keep pace with market dynamics.
Core challenges included:
Limited Market Visibility
The client had no reliable method to monitor pricing or product positioning across shopping portals. Manually gathering this information was time-consuming and often outdated by the time it reached decision-makers.
Inefficient Forecasting Models
Demand forecasting relied heavily on internal sales history, ignoring external factors such as competitor pricing, seasonal shifts, or emerging product trends. This led to frequent stock imbalances.
High Operational Overhead
Teams manually extracted product data from multiple websites for analysis. These repetitive tasks drained time and resources, introduced human error, and slowed down strategic planning cycles.
Scalability Concerns
With expansion plans underway, the client knew that manual monitoring wouldn’t scale.
They needed a solution that could adapt to growing product volumes, multiple geographies, and evolving competitive dynamics. Thus, INTECH presented the solution.
To address the client’s operational and visibility gaps, INTECH deployed a Robotic Process Automation (RPA) solution using UiPath. The system automated the extraction of key product data, including descriptions, pricing, availability, and vendor details from shopping portals.
This solution replaced time-consuming manual tracking with real-time, accurate insights.
Here are the key features:
Real-Time Market Insights
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Our automated solution provided continuous access to live product and pricing data across multiple marketplaces. This gave the client a clear view of how products are positioned and priced in real-time. With this data feeding directly into planning systems, demand forecasting became more accurate, timely, and responsive to market changes.
Smarter Forecasting
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The client’s forecasting was previously based only on internal sales data. With INTECH’s solution, real-time market data became accessible. This gave them a more complete view, helping predict demand more accurately and avoid stock issues.
Reduced Manual Workload
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The solution eliminated repetitive manual tasks by running unattended bots that required no human input. Teams no longer had to extract and clean data by hand, which reduced errors and saved valuable time for strategic analysis.
Scalable Automation Architecture
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As the client expanded, manual monitoring couldn’t keep up with the volume of data needed. The RPA solution was built with scalability in mind. Bots could run on multiple machines at once and integrate with additional shopping platforms without rework. This allowed the client to handle more products without adding to their operational workload.
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With the solution framework defined, INTECH moved forward with the implementation.
INTECH built a system that could run reliably, scale easily, and integrate smoothly with the client’s existing operations. The process began with a proof of concept and continued through bot development, testing, and automation scheduling.
Here are the steps involved in the implementation process:
Initial PoC Development
The implementation began with a Proof of Concept (PoC) using UiPath to validate the feasibility of automating data extraction from e-commerce websites. The PoC focused on building bots that could reliably navigate product listings, extract relevant fields, and store them in structured formats.
Bot Design and Workflow Configuration
Based on the PoC results, UiPath workflows were developed to automate the end-to-end process. Each bot was configured to perform browser-based interactions required to extract product details from multiple vendor pages. The automation logic was modular to support easy updates and platform-specific adjustments.
Environment Setup and Multi-Machine Deployment
To scale performance, the bots were deployed across multiple virtual machines. This setup enabled parallel execution, allowing faster data processing and support for larger data volumes as the system scaled.
Platform Integration
The bots were integrated with specific shopping portals, beginning with high-priority platforms like Amazon and Alibaba. The modular structure allowed additional platforms to be added with minimal development effort.
Scheduling, Orchestration, and Data Handling
Using UiPath Orchestrator, bots were scheduled to run at defined intervals without human intervention, ensuring 24/7 operation. The extracted data was automatically exported in structured formats for analytics and inventory systems. Logs and alerts were set up to monitor bot performance and flag any issues during data extraction.
INTECH’s RPA solution transforms the client’s operations by improving market insights, forecasting accuracy, and operational efficiency. The automation of data extraction enhances decision-making and supports scalable growth.
Here's the business impact:
To achieve these business impacts, we leveraged the right tools and technologies.
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UiPath: Used to automate the data extraction process through intelligent bots. It enables the creation of workflows to collect and process product data from e-commerce platforms in real time.
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UiPath Orchestrator: UiPath Orchestrator schedules and manages bot operations. It ensures continuous, unattended automation while providing real-time monitoring, performance tracking, and exception handling.
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Amazon & Alibaba APIs: Custom API integrations with portals allow for seamless and accurate extraction of product data. These help access real-time information on pricing, availability, and product details directly from these platforms.
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Cloud Infrastructure: The solution is hosted on cloud infrastructure to ensure scalability and flexibility. This setup supports large data volumes, offers high availability, and allows for easy expansion as the client’s needs grow.
