🚗 NHTSA Vehicle Complaints Scraper

🚀 Pull every consumer vehicle complaint filed with NHTSA in seconds. Make, model, year, components, crash/fire/injury flags, dates, VIN, and full narratives, straight from the official US safety database.

🕒 Last updated: 2026-05-27 · 📊 15 fields per record · Millions of complaints · All US makes and models

NHTSA collects every consumer complaint filed about a US-registered vehicle and exposes it through a public tabular API. This scraper turns that API into a one-click data pull so you can analyse defect trends, monitor competitor recalls or feed an automotive intelligence pipeline.

Each record covers one ODI complaint, including the manufacturer's name, the component flagged, the incident date, whether it involved a crash, fire, injury or death, the full narrative the consumer submitted, and the affected products list. Pull by make, model and year - the actor handles the rest.

🎯 Target Audience	💡 Primary Use Cases
Automotive analysts	Track defect trends by component and model
Legal and insurance teams	Source complaint evidence for class-action research
OEM safety teams	Monitor competitor complaints for benchmarking
Consumer journalists	Investigate emerging vehicle safety issues
Data scientists	Train classifiers on complaint narratives

📋 What the NHTSA Vehicle Complaints Scraper does

• Hits the official api.nhtsa.gov/complaints/complaintsByVehicle endpoint
• Returns every complaint for a given make, model, modelYear
• Streams structured records: component, narrative, crash/fire/injury flags, dates, VIN
• No API key, no rate-limit headaches, no HTML parsing
• Stream-pull to tabular records

💡 Why it matters: NHTSA's consumer complaints database is the earliest signal of vehicle defects. Pulling it programmatically means you spot the trend before the recall.

🎬 Full Demo (🚧 Coming soon)

⚙️ Input

Field	Type	Description
make	string	Vehicle make (Honda, Ford, Tesla)
model	string	Vehicle model (Civic, F-150, Model 3)
modelYear	integer	Model year (1949-2030)
maxItems	integer	Cap on records returned (free plan: 10)

{ "make": "Honda", "model": "Civic", "modelYear": 2020, "maxItems": 25 }

{ "make": "Tesla", "model": "Model 3", "modelYear": 2023, "maxItems": 100 }

⚠️ Good to Know: NHTSA returns the complete complaint set per (make, model, year) tuple in one response. Loop your runs over multiple years to build a longitudinal dataset.

📊 Output

Field	Description
🆔 odiNumber	NHTSA ODI complaint number
🏭 manufacturer	Reported manufacturer
📅 modelYear / make / model	Vehicle identification
🔧 components	Affected component category
💥 crash / 🔥 fire	Boolean incident flags
🚑 numberOfInjuries / numberOfDeaths	Counts
🗓 dateOfIncident / dateComplaintFiled	Dates
📝 summary	Full complaint narrative
🔢 vin	Reported VIN if provided
📦 products	List of affected products
🔗 sourceUrl	NHTSA public page
🕒 scrapedAt	ISO timestamp

✨ Why choose this Actor

• 🆓 Public US government data, no auth required
• 📡 Direct hit on the official NHTSA tabular API
• 🧭 Single call returns the entire vehicle complaint set
• 🧰 Clean field names, no HTML parsing
• 📦 Pull as tabular records

📈 How it compares to alternatives

Approach	Cost	Coverage	Setup time
Manual tabular open from NHTSA	Free	Bulk only	Hours
Direct NHTSA API integration	Free	Full	Code required
ParseForge NHTSA Vehicle Complaints Scraper	Pay-per-result	Full + structured	Minutes

🚀 How to use

1. Create a free Apify account (includes $5 credit).
2. Open the NHTSA Vehicle Complaints Scraper.
3. Set make, model, modelYear.
4. Click Start and open tabular / spreadsheet / tabular / tabular.
5. Schedule daily, weekly or trigger from Make / Zapier.

💼 Business use cases

Defect monitoring - alert when complaint volume spikes for a make/model.

Legal research - pull every complaint citing a component for a class-action filing.

OEM benchmarking - compare your fleet against competitor complaint trends.

Consumer advisory journalism - investigate emerging safety issues.

🔌 Automating NHTSA Vehicle Complaints Scraper

Hook into Make, Zapier, n8n, Airbyte, Pipedream, Slack, Google Drive, GitHub Actions or any HTTP webhook for scheduled pulls.

🌟 Beyond business use cases

• Research: model defect propagation across years.
• Personal: check the complaint history of a used car before buying.
• Non-profit: support consumer protection investigations.
• Experimentation: train NLP classifiers on complaint narratives.

🤖 Ask an AI assistant about this scraper

Ask ChatGPT, Claude, Perplexity or Copilot: "How do I pull every NHTSA complaint about Tesla Model 3 brakes using the ParseForge Apify actor?"

❓ Frequently Asked Questions

Is NHTSA data public? Yes. All consumer complaints are public records under the NHTSA's open data policy.

How fresh is the data? NHTSA updates the complaints database continuously. The actor returns whatever the API serves at run time.

Can I search by VIN? The API filters by make/model/year. Filter the results client-side by VIN.

Are recalls included? This actor focuses on complaints. Recalls are a separate dataset.

Do I need an API key? No. NHTSA is fully open.

What about commercial vehicles? Heavy trucks and buses are indexed under their own makes and models.

Can I get European or Japanese complaints? NHTSA covers the US market. For EU, see EU vehicle safety registries.

Does the actor decode VINs? VINs are returned as-is. Pair with NHTSA's VIN decoder API to enrich.

How many records per run? The API returns the complete set per vehicle, often hundreds.

Is there pagination? The API returns the full set in one call. The actor caps via maxItems.

🔌 Integrate with any app

Apify, Make, Zapier, n8n, Pipedream, Slack, Airbyte, GitHub, Google Drive, Power Automate, AWS Lambda, REST webhook.

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💡 Pro Tip: browse the complete ParseForge collection for more US government data scrapers.

🆘 Need Help? Open our contact form

⚠️ Disclaimer: independent tool, not affiliated with NHTSA. Only publicly available US government data is collected.