Competitor Pricing Intelligence Case Study

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Competitor Pricing Intelligence

Web Data Automation for Automotive Industry Case Study

Problem Statement

An automotive giant aims to gain a competitive edge by analyzing competitor pricing details, car models, vehicle availability in specific regions, and customer ratings and reviews. To achieve this, Mobius has been tasked with extracting comprehensive data from leading car sharing platforms in the US.

Our solution

We have implemented a robust and automated data aggregation solution utilizing Python scripts. Including,

Automated Data Extraction: Python-based scripts have been developed to extract over 60 attributes from diverse sources, ensuring a thorough analysis of competitor pricing, car models, and customer sentiments
Normalization and Validation: The extracted data is processed using a normalized database structure, ensuring consistency and accuracy. Automated validations have been enabled to address coverage and attribute-related issues, enhancing the reliability of the extracted information
Automated Reporting: Mobius has implemented automated alerts, reports, and validations to monitor the entire data pipeline. This ensures the crawl and subsequent processes progress seamlessly, enhancing efficiency and reliability.
Geospatial Data Handling: Overcoming challenges related to latitude and longitude, Mobius has successfully managed geographical intricacies. Captured IDs are intelligently passed to different URLs, allowing precise data extraction from diverse sources.

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Benefits

Automation has resulted in significant time savings, reducing manual efforts by 70%, and allowing the client to focus on strategic decision-making.
By providing detailed competitor analysis, our client has gained a competitive advantage, allowing them to make informed decisions and set optimal pricing strategies.
Utilizing customer ratings and reviews, our client has tailored their services, enhancing customer satisfaction and loyalty, leading to a 13% increase in customer retention.