Daily Vehicle Market Monitor
A scheduled agent captures vehicle-market listings every day and stores a dated snapshot for analysis.
- Status
- Demo
- Task & input
- Public vehicle-market listings, collected every day on a cron schedule.
- QMerse performs
- Collects and flattens the listings in Python, writes them to PostgreSQL without duplicating rows, and maps activity by dealer ZIP.
- You review
- The run history, the dated snapshots and the ZIP map.
- Output
- A daily snapshot appended to a growing time series, with a map from the same run.
A scheduled QMerse agent captures public vehicle-market listings, structures vehicle and dealer data, maps market activity by ZIP code, and stores a daily snapshot for ongoing analysis. It runs on the server on a cron schedule — nobody opens the canvas to trigger it.
Track new inventory, regional pricing, price reductions and days-on-market — down to individual VINs.
How it is built. A Python script node handles collection and flattening, then writes straight into PostgreSQL. The write is configured to skip on conflict, so a re-run never duplicates rows and the table stays clean whether the flow fires once or fires again after a failure. The schedule is a standard cron expression, so the flow runs unattended and reports its own run history.
Why the schedule is the point. A single scrape is a snapshot; the value is in the accumulation. Because every run appends another dated snapshot, the dataset becomes a time series — and questions that are impossible against one download become straightforward: which ZIPs are discounting fastest, how long a given trim sits before it moves, where a specific VIN has been repriced.
The map shows listings by dealer ZIP, with bubble size as listing count and colour as average price. It is generated from the same workflow that collects the data, so the visualisation stays in step with the table behind it.
