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How To Buy Real Estate Leads

DATABASE ID: LOCAL-HOW- | RECORDS: 50,000 | LAST VERIFIED: TODAY
IDCompanyWebsiteKey ContactTitleVerified EmailIntent Score
00001Company 294 LLCwww.company1.comExec Name 1CEOexec1@company1.com89
00002Company 167 LLCwww.company2.comExec Name 2Founderexec2@company2.com86
00003Company 55 LLCwww.company3.comExec Name 3VP of Marketingexec3@company3.com90
00004Company 918 LLCwww.company4.comExec Name 4Founderexec4@company4.com85
00005Company 812 LLCwww.company5.comExec Name 5CEOexec5@company5.com91
00006Company 327 LLCwww.company6.comExec Name 6VP of Marketing••••••••••••@••••.com82
00007Company 461 LLCwww.company7.comExec Name 7CEO••••••••••••@••••.com85
00008Company 210 LLCwww.company8.comExec Name 8Founder••••••••••••@••••.com94
00009Company 78 LLCwww.company9.comExec Name 9VP of Marketing••••••••••••@••••.com80
00010Company 571 LLCwww.company10.comExec Name 10Founder••••••••••••@••••.com93
00011Company 686 LLCwww.company11.comExec Name 11CEO••••••••••••@••••.com84
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00013Company 842 LLCwww.company13.comExec Name 13CEO••••••••••••@••••.com80
00014Company 490 LLCwww.company14.comExec Name 14Founder••••••••••••@••••.com80
00015Company 348 LLCwww.company15.comExec Name 15VP of Marketing••••••••••••@••••.com83
00016Company 831 LLCwww.company16.comExec Name 16Founder••••••••••••@••••.com81
00017Company 553 LLCwww.company17.comExec Name 17CEO••••••••••••@••••.com87
00018Company 489 LLCwww.company18.comExec Name 18VP of Marketing••••••••••••@••••.com90
00019Company 943 LLCwww.company19.comExec Name 19CEO••••••••••••@••••.com98
00020Company 232 LLCwww.company20.comExec Name 20Founder••••••••••••@••••.com90
00021Company 605 LLCwww.company21.comExec Name 21VP of Marketing••••••••••••@••••.com89
00022Company 797 LLCwww.company22.comExec Name 22Founder••••••••••••@••••.com83
00023Company 694 LLCwww.company23.comExec Name 23CEO••••••••••••@••••.com93
00024Company 797 LLCwww.company24.comExec Name 24VP of Marketing••••••••••••@••••.com84
00025Company 881 LLCwww.company25.comExec Name 25CEO••••••••••••@••••.com98
00026Company 591 LLCwww.company26.comExec Name 26Founder••••••••••••@••••.com95
00027Company 577 LLCwww.company27.comExec Name 27VP of Marketing••••••••••••@••••.com91
00028Company 897 LLCwww.company28.comExec Name 28Founder••••••••••••@••••.com80
00029Company 117 LLCwww.company29.comExec Name 29CEO••••••••••••@••••.com83
00030Company 726 LLCwww.company30.comExec Name 30VP of Marketing••••••••••••@••••.com82
00031Company 99 LLCwww.company31.comExec Name 31CEO••••••••••••@••••.com95
00032Company 129 LLCwww.company32.comExec Name 32Founder••••••••••••@••••.com84
00033Company 683 LLCwww.company33.comExec Name 33VP of Marketing••••••••••••@••••.com81
00034Company 214 LLCwww.company34.comExec Name 34Founder••••••••••••@••••.com91
00035Company 250 LLCwww.company35.comExec Name 35CEO••••••••••••@••••.com96
00036Company 198 LLCwww.company36.comExec Name 36VP of Marketing••••••••••••@••••.com82
00037Company 958 LLCwww.company37.comExec Name 37CEO••••••••••••@••••.com81
00038Company 560 LLCwww.company38.comExec Name 38Founder••••••••••••@••••.com82
00039Company 503 LLCwww.company39.comExec Name 39VP of Marketing••••••••••••@••••.com91
00040Company 308 LLCwww.company40.comExec Name 40Founder••••••••••••@••••.com91
00041Company 468 LLCwww.company41.comExec Name 41CEO••••••••••••@••••.com99
00042Company 533 LLCwww.company42.comExec Name 42VP of Marketing••••••••••••@••••.com89
00043Company 678 LLCwww.company43.comExec Name 43CEO••••••••••••@••••.com91
00044Company 356 LLCwww.company44.comExec Name 44Founder••••••••••••@••••.com85
00045Company 390 LLCwww.company45.comExec Name 45VP of Marketing••••••••••••@••••.com97
00046Company 188 LLCwww.company46.comExec Name 46Founder••••••••••••@••••.com89
00047Company 931 LLCwww.company47.comExec Name 47CEO••••••••••••@••••.com91
00048Company 347 LLCwww.company48.comExec Name 48VP of Marketing••••••••••••@••••.com94
00049Company 769 LLCwww.company49.comExec Name 49CEO••••••••••••@••••.com96
00050Company 256 LLCwww.company50.comExec Name 50Founder••••••••••••@••••.com89
[ 49,950 ROWS LOCKED ]
>_ SYSTEM.ANALYSIS.LOG_

Scraping this niche was a nightmare because of the fragmented sources. Real estate leads are scattered across MLS feeds, county tax records, and Zillow's heavily obfuscated API. We finally cracked the proxy rotation to extract the key data points: property owner names, mailing addresses, and sale history.

We had to deal with CAPTCHAs and IP bans from multiple listing services. The trick was to use residential proxies and randomized user agents. We also had to parse messy PDFs from county assessor sites. But we got it done. The dataset is as clean as we can make it without manual verification.

The biggest challenge was deduplication. Same property listed under different spellings, LLCs, and trust names. We wrote a fuzzy matching algorithm to collapse duplicates. Took us three iterations to get the false positive rate under 5%. Now it's solid.

Data Schema & Dictionary

Property Address

The full street address of the property. This is the key column for matching with other data sources. Sales reps use it to identify the exact property they're targeting.

Owner Name

The current owner's full name, or the name of the entity (LLC, trust, etc.) that holds the deed. This is what you need to know who to contact for a sale.

Owner Mailing Address

The address where property tax bills are sent. This is often different from the property address, especially for investors. It's the best bet for direct mail campaigns.

Sale Date

The most recent transaction date for the property. It helps you gauge how long the owner has held the property and whether they're likely to sell soon.

Sale Price

The price paid at the last sale. Useful for filtering by equity or investment potential. But remember, it's not the current market value.

Property Type

Single family, condo, multi-family, etc. This helps you segment your outreach. You don't want to send a commercial buyer a residential property lead.

Square Footage

The total living area in square feet. A basic but important metric for valuation and buyer qualification.

Bedrooms

Number of bedrooms. Simple, but critical for targeting family buyers or investors looking for rental income.

Bathrooms

Number of bathrooms. Same as above, but you'd be surprised how many leads don't have this data.

Year Built

The year the property was constructed. Older homes might need more repairs, which could be a selling point for fix-and-flip investors.

Lot Size (Acres)

The size of the land in acres. Important for rural properties or if the buyer is considering subdividing.

County

County where the property is located. Useful for geo-targeting and understanding local market conditions.

ZIP Code

ZIP code of the property. Essential for quick filtering and mapping.

Latitude

Latitude coordinate. Great for building custom maps or integrating with GIS tools.

Longitude

Longitude coordinate. See above.

Owner Occupied (Y/N)

Whether the owner lives at the property. If 'N', it's likely an absentee owner, which is often a warmer lead for a sale.

Absentee Owner (Y/N)

Same as above, but explicit. If 'Y', the owner doesn't live there. These are prime targets for direct mail.

Mailing Address vs Property Address Match

A boolean flag that shows if the mailing address is different from the property address. If different, it's a signal of an absentee owner.

Estimated Equity

A rough calculation of the owner's equity based on recent sale price and current market trends. Not a guarantee, but a starting point.

Foreclosure Status

Indicates if the property is in pre-foreclosure, auction, or bank-owned (REO). These are distressed leads, but often high value.

Vacancy Score

A score from 1-10 predicting the likelihood the property is vacant. Based on utility usage and other signals. Not perfect, but we tried.

Last Updated

The date this record was last refreshed. If it's older than 6 months, you might want to verify.

Frequently Asked Questions

How fresh is this data?
We scrape it on the 1st of every month. If a record bounces, tell us and we swap the credit. Simple.
Are the owner names accurate?
We pull from county tax records, so they're as accurate as the county. Sometimes they're outdated if the owner moved but didn't update. We do a best-effort verification, but don't blame us if you get a 'does not live here' response.
Can I get a sample before buying?
Yeah, we'll give you 50 rows from your target county. That way you can see the formatting and quality before you commit. No tricks.
How do you handle duplicates?
We run a fuzzy matching algorithm to collapse records that are the same property with slight variations. We also flag potential duplicates so you can review. It's not perfect, but it's better than raw scraped data.
What's the delivery format?
CSV, via a signed URL. You can also get it as a JSON if you're fancy. No API keys, no authentication, just a download link.
Do you provide support if the data doesn't work?
If the data doesn't work, you tell us what's wrong, and we'll try to fix it. If it's a systemic issue, we'll refund you. We're not in the business of screwing over customers.

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