Industry: Automobile
Region: USA
Technology: Data Science, Python, Generative AI Models, Web Scraping
About the Client
Our client, a leading technology provider company based in America to help RV, Marine, Powersports, and Equipment manufacturers and dealer find, win, and keep customers, sought innovative solutions to extract features from OEM website. Their objective was to reduce the manual intervention of getting the required features from OEM websites.
The Business Challenge
The client faced several significant challenges:
- Manual Feature Extraction:Rollick faces the challenge of dealing with hundreds of OEMs and brands, each launching new vehicle variants annually. The process of extracting features and specifications for these vehicles was entirely manual.
- Time-Consuming Process: The content team at Rollick spent significant hours manually browsing through each OEM website to gather the necessary features for the vehicles. This manual process was labour-intensive and time-consuming.
- Variability Across OEMs:Each OEM website may have different layouts, formats, and structures for presenting vehicle features. This variability added complexity to the manual extraction process, requiring the team to adapt to different website structures.
The Solution
Leveraging Generative AI expertise, we implemented an automated solution to overcome these challenges. The new system drastically reduced the time spent on feature extraction, providing Rollick with accurate and consistent data across all OEMs and brands. This automation not only streamlined the process but also freed up valuable resources within the content team, allowing them to focus on more strategic initiatives.
- Data Retrieval Library Integration:To streamline the process of accessing data from OEM websites, we integrated a powerful data retrieval library into Rollick's system. This library enabled us to efficiently gather information from various OEM websites in a structured and organized manner.
- Automated Data Retrieval: : Leveraging the data retrieval library, our system automatically accessed and retrieved the required features and specifications from each OEM website. This automated process eliminated the need for manual browsing and significantly reduced the time and effort previously spent on data collection
- Prompt Engineering for Feature Extraction:With the data in hand, we utilized prompt engineering techniques to extract the specific features and specifications required by Rollick. Customized prompts were designed to target and extract the relevant information from the retrieved data, ensuring accuracy and completeness.
The Benefits
- Time and Resource Savings: The automated feature extraction system saves significant time and resources previously spent on manual browsing and data collection from OEM websites. The content team can now allocate their valuable time to more strategic tasks, improving overall productivity and efficiency.
- Scalability and Adaptability: The automated system is scalable and adaptable to accommodate new OEMs, brands, and vehicle variants as Rollick's marketplace expands. As the company grows and onboard new partners, the system seamlessly handles increased data extraction tasks without compromising efficiency.
- Real-Time Updates:The system enables real-time updates of features and specifications, ensuring that Rollick always has the latest information available. This real-time data availability allows for quick adjustments to product listings, promotions, and marketplace offerings.
- Cost Efficiency: The automation of feature extraction reduces operational costs associated with manual data collection. Rollick can achieve cost savings in terms of labour hours, minimizing the need for a large content team dedicated to data retrieval tasks.
Key Technologies
- Python
- Generative AI Models
- Web scraping