The Vermont Real Estate Market A Deep Dive Into Zillows Data

Working With Zillow Data for Vermont Properties

Zillow isn't a primary data source for professionals. It's a consumer tool that happens to sit on a massive amount of listing information, and the data it surfaces is useful if you know how to read it and what to ignore. I've spent years pulling Zillow figures into comparative market analyses for Vermont properties, and the process is rarely as clean as the website makes it look. The first thing you need to understand is that Zillow relies on public records and MLS feeds that come with delays. In Vermont, where rural counties move slower than the cities, a property listed on the Chittenden County MLS might show up on Zillow within an hour, but a farm sale in Windsor County could take three days to propagate through whatever aggregator Zillow contracts with that region. That lag matters when you're trying to give a client real-time pricing guidance.

The Vermont Real Estate Market A Deep Dive Into Zillows Data

Getting the data itself is straightforward. You go to Zillow.com, search by town or zip code, and pull the sold listings from the past six to twelve months. Most people stop there. That's where you make your mistake. The sold price on Zillow is often the last list price, not necessarily the final contracted amount, and in Vermont's market where negotiation margins can swing five to eight percent depending on whether it's a winter off-season deal or a summer cabin rush, that distinction costs you real money if you're building an appraisal around it. What I do instead is export the raw data using browser-based scraping tools or scripts that hit Zillow's public API endpoints where they exist. The Zillow Group Web Services API used to be widely available, but they've restricted it considerably over the past few years. Now the practical approach is to use a combination of their public data feeds and manual verification. For about forty percent of Vermont properties, especially the older farmsteads and lakefront parcels, the Zestimate algorithm pulls square footage and room counts from county tax assessors, and those records are frequently wrong. I had a property in Bennington County last year where the assessor listed 1,200 square feet on the main house but the actual finished living space was 1,840 square feet because a 1998 addition was never properly permitted and filed. Zillow's data reflected the assessor's numbers exactly, which would have thrown off any price-per-square-foot calculation by nearly forty percent. The workaround I use is to cross-reference every Zillow figure against the town clerk's record and the most recent property tax assessment, then flag any discrepancies above ten percent. This adds about twenty minutes per property to my workflow, but it prevents me from building an entire CMA on bad baseline data. You can automate parts of this with a script that pulls the Zillow data and matches it against municipal property records by address, but Vermont's inconsistent numbering systems across towns make automated matching error-prone. I run the script first and then manually verify the flagged mismatches.

There's another layer most people miss entirely. Zillow's "days on market" metric doesn't account for listings that were pulled and re-listed, which happens more often than you'd think in Vermont's smaller towns where sellers test the water before committing to a price. A cabin in Stowe that sat for 120 days on Zillow might have actually been on and off the market three separate times, meaning the true market time was closer to sixty days with two price reductions along the way. That changes your analysis of pricing velocity significantly. For rental yield calculations, which some investors ask me about, Zillow's Rent Zestimate is even less reliable for Vermont. The algorithm doesn't weight seasonal demand well, so a lakeside rental in North Troy that commands four thousand a month in July and August might show a yearly average that's half that figure, making the property look like a terrible investment when it's actually solid at the right purchase price. I override Zillow's rent estimate by pulling actual short-term rental comps from Vrbo and Airbnb listing archives, then calculate the seasonal adjusted annual income myself. The biggest limitation of relying on Zillow data for Vermont is simply the coverage gap. In Chittenden and Rutland counties, you're getting maybe eighty-five to ninety percent accuracy on listed sales because those MLS feeds are well-maintained. But go north into Essex County or west into Orleans County and the data quality drops noticeably. Some towns don't feed their MLS into Zillow at all, and for those properties you're working with public records that are months or even a year old. If your analysis depends on those areas, Zillow will give you a false sense of completeness. You need to go to the county register of deeds directly for the actual deed transfer amounts, which are sometimes different from what was publicly listed.

If you want to build your own dataset, the most efficient method I've found is to use a combination of Zillow's search filters to identify your target properties, then write a Python script using the requests and BeautifulSoup libraries to scrape the sold listing pages in bulk. Store everything in a CSV with columns for address, list price, sold price, days on market, price per square foot, and the date pulled. Then run that through a pandas script that cleans the address formats and matches them against the Vermont Department of Taxes property search tool for the official assessed values. This whole pipeline takes me about fifteen minutes to run for a typical ten-property search, compared to the two hours it would take to do it manually. The script isn't elegant but it gets the job done. A word of caution on the export process: Zillow's terms of service prohibit automated scraping, so if you're doing this at scale for a business, you should probably be using a licensed data provider instead. PropStream or ATTOM Data Solutions will cost you a monthly subscription fee but they give you clean, compliant data with proper documentation trails that matter if anyone ever questions your methodology. For occasional personal research or a single transaction analysis, the manual Zillow route is fine.