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Car Complaints Crawler

What does Car Complaints Crawler do?

Car Complaints Crawler scrapes vehicle complaint data from CarComplaints.com — one of the most comprehensive consumer-reported car problem databases on the web. For every make, model, year, and complaint category, it collects both user-submitted complaint counts and NHTSA (National Highway Traffic Safety Administration) complaint counts.

Run it once to get a full snapshot of the database, or schedule it weekly to track how complaint volumes change over time. Results are available for download as JSON, CSV, or Excel directly from the Apify Console.

Why use Car Complaints Crawler?

• Automotive research — identify which vehicles have the most reported problems before buying
• Legal and lemon law research — find patterns in complaints by make, model, year, and category
• Journalism and data analysis — track complaint trends across manufacturers
• Competitive intelligence — benchmark reliability data across brands
• Insurance and risk modeling — supplement actuarial data with real-world complaint volume

How to use Car Complaints Crawler

1. Click Try for free on this page
2. Optionally enter one or more makes to limit the crawl (leave blank to scrape everything)
3. Optionally filter by model, minimum year, or maximum year
4. Click Start and wait for the run to complete
5. Download your dataset as JSON, CSV, or Excel from the Output tab

A full crawl of all makes covers 70+ manufacturers, hundreds of models, and thousands of year/category combinations. It typically completes in a few hours. For a quick test, set Max requests per crawl to 50.

Input

Example input to scrape only Ford and Toyota from 2015 onward:

{
"makes":["Ford","Toyota"],
"minYear":2015
}

Output

Each record represents one complaint category for a specific make/model/year. You can download the dataset in various formats such as JSON, CSV, or Excel.

Example output records:

[
{
"make":"Ford",
"model":"F-150",
"year":"2018",
"year_complaints":"312",
"model_total_complaints":"4821",
"category":"engine problems",
"category_complaints":"87",
"nhtsa_complaints":"204",
"url":"https://www.carcomplaints.com/Ford/F-150/2018/"
},
{
"make":"Ford",
"model":"F-150",
"year":"2018",
"year_complaints":"312",
"model_total_complaints":"4821",
"category":"transmission problems",
"category_complaints":"43",
"nhtsa_complaints":"98",
"url":"https://www.carcomplaints.com/Ford/F-150/2018/"
}
]

Data fields

Pricing and cost

A full crawl of all 70+ makes costs approximately 5–15 compute units depending on the size of the database at run time. Using make/model/year filters dramatically reduces cost for targeted use cases.

Tips

• Use Filter by make(s) to run targeted, low-cost scrapes for specific brands
• Set Max requests per crawl to 50 to do a quick test run before committing to a full crawl
• Schedule a weekly run to track complaint trends over time — new complaints are submitted daily

FAQ and support

• Is this legal? This Actor scrapes publicly available data from CarComplaints.com. Always review a website's Terms of Service before using scraped data commercially.
• The data looks incomplete — some year/category combinations have no user complaints but do have NHTSA complaints. This is expected; category_complaints will be null in those cases.
• Found a bug or need a custom feature? Open an issue on the Actor's Issues tab.