Project Overview
- User: Bilal Rajput
- Profile: Computer Science Student and Freelancer
- Use Case: Product Data for an Online Shop
- Project Scope: More than 50,000 Products
- Data Format: Excel
Bilal Rajput is a Computer Science student and freelancer specializing in web scraping and data collection. Since 2022, he has been using Octoparse to collect and structure publicly available web data for businesses, ranging from lead lists and competitor analysis to large-scale product datasets.
For Bilal, web scraping is more than a technical task. It is a service that helps businesses make data usable faster and complete projects that would be difficult to scale manually when dealing with large volumes of information.
From Manual Data Collection to a Data Service
Before using Octoparse, Bilal often transferred information from websites into spreadsheets manually. This process was time-consuming, repetitive, and difficult to scale when working with larger datasets.
With Octoparse, Bilal began his web scraping journey. Although the platform initially seemed complex, tutorials and blog articles helped him become confident quickly. Step by step, he developed his skills into a professional freelancer service.
The Challenge: Reliably Extracting More Than 50,000 Product Pages
One of Bilal’s most memorable projects involved a customer who needed to collect product data from an Australian website and import it into their own online store. The customer did not have the technical knowledge required to collect the data themselves.
The required information included product names, descriptions, technical specifications, prices, categories, images, and other relevant product details.
The challenge was not only the size of the project. With more than 50,000 product pages, the extraction logic needed to deliver reliable and consistent results. Bilal therefore needed a workflow that could be tested and optimized before processing the complete dataset.
The Solution: Custom Task, XPath, and a Structured Testing Process
Bilal built the project as a Custom Task in Octoparse and customized the extraction logic using XPath expressions to match the required product fields.
Instead of processing the entire product catalog immediately, he first tested the task with smaller samples in Local Mode. In Data Preview, he checked whether the content was correctly identified and assigned to the right fields.
He then optimized XPath expressions, workflow logic, and execution settings step by step. To ensure a stable data process, he adjusted the request frequency, execution approach, and relevant task settings based on the website’s technical requirements.
After the workflow was reliable, he scaled the extraction to the full product catalog.
“Testing and refining the task step by step helped the most.”
— Bilal Rajput
AI Support for More Efficient Workflows
Bilal sees great potential in AI helping simplify more steps in the process of building scraping workflows. Future AI features, such as support for creating data fields, can help users build workflows faster and focus more on data quality and customer requirements.
The Result: Product Data Ready for Business Use
The final dataset contained more than 50,000 products. Bilal delivered the data in Excel format, allowing the customer to use it directly for maintaining and expanding their e-commerce website.
From a large number of individual product pages, Bilal created a structured data foundation that the customer could integrate directly into their business processes. This allowed the customer to manage product information more efficiently, maintain store content in a more structured way, and continue expanding their online product catalog.
Why Octoparse?
For Bilal, the strength of Octoparse lies in the combination of visual workflows and technical flexibility. Many scraping tools require programming knowledge, while Octoparse makes advanced data extraction more accessible through visual workflows.
This combination allows him to translate individual customer requirements into reliable workflows faster, build data processes efficiently, and handle larger datasets in a controlled way.
Data Skills as an Opportunity for Freelancers
Bilal’s story shows how data automation can create new professional opportunities. As a student and freelancer, he built practical skills with Octoparse that can be directly applied to customer projects.
His advice to businesses is clear:
“Do not simply copy everything your competitors are doing. Use the collected data to understand market trends, identify gaps, and build something unique that adds value to your own business.”
— Bilal Rajput
For Bilal, a project does not end with collecting data. What matters is whether the data helps customers make better decisions, discover new opportunities, or improve their own processes.
Conclusion
More than 50,000 product records were the visible result of this project. The bigger story behind it is Bilal’s development: from manually collecting web data to becoming a freelancer who delivers scalable data projects for customers.
With Octoparse, he was able to build customized workflows and process large datasets in a controlled way. Web scraping is no longer just a technical solution, but a valuable skill that enables freelancers to solve real business challenges.
