This Car, How Much Should I Buy and Sell It For?
This is a question that used car dealers face every day. Even for the same model, the value can vary significantly depending on the year, mileage, and options, but often the judgment relies heavily on experience. To find out what price a competing dealer listed a car for yesterday, you have to browse through sites like Encar, KB Carrot, and K Car one by one.
- Setting the purchase price incorrectly can result in inventory sitting for a long time, or conversely, selling too cheaply and missing out on profit margins.
- Finding out later at what price a competing dealer listed the same item.
- With dozens of car models to manage, there is no one available to manually check all market prices.
New listings come up every day, and prices keep changing. It's difficult to keep up with this trend through manual checks.
Automatically Collect Listings and Bids Daily
By utilizing Hashscraper's used car platform crawler, you can regularly collect information on listings matching specified models and conditions. You can gather details such as the car's model, year, mileage, options, registration location, and the price offered by the seller all at once, allowing you to directly compare market trends.
Example of Crawling Data
{
"Platform": "엔카",
"Model": "○○ 세단 2.0 가솔린",
"Trim": "프레스티지",
"Year": 2021,
"Mileage": 43200,
"Price": 21500000,
"Fuel": "가솔린",
"Transmission": "자동",
"Region": "경기",
"Seller Type": "딜러",
"Options": ["파노라마선루프", "어라운드뷰", "통풍시트"],
"Accident": "무사고",
"Listing Date": "2026-07-24",
"Collected At": "2026-07-31 09:00"
}
By collecting information on the year, mileage, and options together, you can create price bands based on conditions rather than just a simple average price. Including seller types and registration locations allows you to see differences in dealer bids, private listings, and regional price variations.
Use Case: Price Monitoring for a Used Car Dealer
A domestic used car dealer in Korea handles around 30 main car models. Whenever inquiries about purchases came in, they had to open platforms to find similar listings to estimate values. Each staff member had different criteria for checks, leading to fluctuating estimates, and competing dealer prices were assessed visually each day.
Crawling Settings
- Platforms: Encar, KB Carrot, K Car, and other major used car platforms
- Data Collected: Car model, year, mileage, options, price, registration location, seller type, registration date
- Crawling Frequency: Once daily (regular morning collection)
- Collection Period: Ongoing operation (daily cumulative storage)
Analyzable Data from Crawling
| Analysis Item | Utilization |
|---|---|
| Price Bands by Conditions | Calculate the lowest to highest price range for combinations of year, mileage, and options |
| Identifying Undervalued Listings | Automatically identify listings that are significantly underpriced compared to similar conditions |
| Comparing Competing Dealers | Check the distribution of bids from dealers handling the same car models |
| Regional Price Discrepancies | Compare price differences based on registration locations such as metropolitan and rural areas |
| Inventory and Price Trends by Model | Track how the number of listings and average prices of specific car models change |
| Establishing Purchase Price Criteria | Establish a range for appropriate purchase prices by reverse calculating from selling prices |
Receiving daily summarized market data enabled them to provide well-founded values during purchase consultations. Being able to quickly identify undervalued listings on the same day also improved the speed of purchase decisions.
AI Analysis
By applying AI analysis to the collected listing texts, you can use it as a reference to filter out bait or suspicious listings. This method classifies cases where there are inducement phrases attached to prices that are excessively low compared to market prices.
{
"Model": "○○ 세단 2.0 가솔린",
"Price": 12900000,
"Bait Suspect": true,
"Reason": "동일 조건 시세 밴드 대비 40% 이상 낮음 + '전화문의' 유도 문구",
"Confidence": 0.82
}
Other Use Cases
Auction and Export Sourcing — Used to determine when to secure inventory based on the number of listings and price trends for specific car models.
Depreciation Analysis Compared to New Cars — Examines how used prices drop as the years go by compared to new car prices.
Financial and Insurance Reference Prices — Obtain reference values based on conditions for collateral evaluation or residual value calculation.
Conclusion
When decisions on purchase and sale prices are backed by data rather than just experience, the uncertainty decreases. By examining price bands based on conditions and competing dealer bids daily, you can be the first to catch undervalued listings and reduce the risk of inventory sitting for too long.
Hashscraper handles all crawler operations, maintenance, and monitoring. Even if platform structures change or collection errors occur, you can receive daily summarized market data without the need for direct intervention from the client.
Related Articles
- From Crawling Data to Decision Making
- Outsourcing Crawling Process — Step-by-step guide from inquiry to the first data
- Why Do Estimates Differ Among Companies for Crawling? — Breakdown of costs and hidden expenses
Start Now
With Hashscraper, you can automatically collect listings and market data from platforms like Encar, KB Carrot, and K Car on a regular basis.
