Automotive Industry Data Scraping: How's It Changing this Market?

Use cases 

Here are only a few already proven web scraping use cases within the automotive industry:

• Market trends and pricing intelligence knowledge is primarily obtained via web scraping practice, e.g. monitoring consumers’ purchasing behavior, global sales information, or competitions’ pricing tactics. This kind of analyzed A shapes switched-on companies’ policies. Instead of thinking how to collect data, companies can focus on data analysis and tracking trends in their markets. 

• Aggregated car listings websites rely on the web scraping practice to pull a vast amount of real-time data from the entire web and display it on their one-stop-shop sites for consumers’ convenience.

• Auto parts sites utilize the web scraping practice to monitor the demand and supply for auto parts by exploring competition’s product catalogs, sales figures, auto part reviews, warranty repairs information, to name a few.

• Consumer sentiment analysis by web scraping practice allows automotive manufacturers and auto traders to gather powerful insights from drivers. This analysis insights aids in optimizing existing procedures, as well as generating designs of future vehicles.

Of course, we only scratched the surface here. The automotive industry generates a massive amount of data on the web that holds immense value for the used car and auto parts market participants, car manufacturers, or even start-ups hoping to become the next Tesla. 

However, before the automotive industry data analysis phase, the first step for all data-driven market players is to have a robust external data gathering process in place.

Data extraction tools and solutions

Some companies choose to build their in-house web data mechanisms. As mentioned earlier, it requires automation, i.e., software scripts, also known as web scrapers. Usually, these web scrapers are built and continuously maintained by developers. Furthermore, the web scrapers need to be supported by a proxy network to gather the data successfully. Why so?

Typically, the websites that hold the desired public knowledge implement data requests limits. Once these sites receive a significantly larger volume of requests, they start to block the data collection process by blacklisting the client’s (web scraper’s) IP address. 

Hence, for the web scraper to successfully collect the necessary data on a scale, it is paramount to use proxies (that carry their own IP address). By using a vast amount of proxies, the web scraper can distribute the requests evenly via the IP address pool without reaching the website’s implemented data request limit.

For web data collection in the automotive industry, datacenter proxies are among the top picks.

Datacenter Proxies are private proxies that are unattached with an ISP (Internet Service Provider). Datacenter Proxy is a fast, cheap, and reliable web monitoring solution. Also, datacenter proxies come from a secondary corporation and provide a completely private IP authentication. It guarantees a high level of anonymity and response time.

It’s a wrap

Hopefully, by now, you have a decent understanding of how the automotive industry is already benefiting from the web scraping practice and what resources are needed to gather the data successfully. 

It is safe to state that with the upcoming further technological advancements within the sector, data-backed insights will shape the foreseeable automotive industry companies’ policies. 

Want to find out more ways to use proxies, or you don’t know how to start your own web scraping project, we have many more blog posts that will answer all of your questions!