Location-Based Data Mining for Cataloging

Client’s Challenge

A leading e-commerce company provided us with entire product and pricing information from its outlet across the United States. The client used to extract necessary data manually to do the study before switching to web scraping services.

The criteria’s included scraping product information from their e-commerce platform and retail store outlets across the country, sorted by zip codes of store locations. To scrape the price and product information from e-commerce websites, a comparable method of collecting data has been followed.

For a complete product catalog, this data is being used for additional study in the marketing plan and price comparison. iWeb scraping service was chosen by the client to streamline the complete web extraction process based on nationality, namely zip codes.

Solutions

In this scenario, site-specific crawls were used to focus on the client's website. The solution scraped before the data fields from the website, including the product's unique serial identity, name, category, URL link, crawling timestamp, store location, price, and stock control accessibility.

The client used the acquired data from the above two operations to classify it by zip codes for location and use it for further research. iWeb Scraping’s API was used to transmit the dataset to the client in JSON format.

Web Scraping Benefits

Delivery of unstructured data is made possible depending on the requirement of the client.
Redundancy was reduced because the customer specified which databases, they preferred to adjust web scrapers for scraping information.
The location-based data analysis did not necessitate any client involvement.
The client saved money and time since clean data was given for analysis.
The structure was altered about the client’s requirement.
Periodic updates depending on scrape intensity were also added.

Conclusion

All they had to do now was take the data which we provided according to their requirements.

Conclusion

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