HOME/LOCAL/BEST PLACE TO BUY REAL ESTATE LEADS

Best Place To Buy Real Estate Leads

DATABASE ID: LOCAL-BEST | RECORDS: 50,000 | LAST VERIFIED: TODAY
IDCompanyWebsiteKey ContactTitleVerified EmailIntent Score
00001Company 365 LLCwww.company1.comExec Name 1CEOexec1@company1.com93
00002Company 507 LLCwww.company2.comExec Name 2Founderexec2@company2.com92
00003Company 37 LLCwww.company3.comExec Name 3VP of Marketingexec3@company3.com87
00004Company 665 LLCwww.company4.comExec Name 4Founderexec4@company4.com94
00005Company 870 LLCwww.company5.comExec Name 5CEOexec5@company5.com87
00006Company 486 LLCwww.company6.comExec Name 6VP of Marketing••••••••••••@••••.com89
00007Company 599 LLCwww.company7.comExec Name 7CEO••••••••••••@••••.com99
00008Company 166 LLCwww.company8.comExec Name 8Founder••••••••••••@••••.com93
00009Company 583 LLCwww.company9.comExec Name 9VP of Marketing••••••••••••@••••.com85
00010Company 862 LLCwww.company10.comExec Name 10Founder••••••••••••@••••.com96
00011Company 780 LLCwww.company11.comExec Name 11CEO••••••••••••@••••.com97
00012Company 395 LLCwww.company12.comExec Name 12VP of Marketing••••••••••••@••••.com94
00013Company 205 LLCwww.company13.comExec Name 13CEO••••••••••••@••••.com90
00014Company 173 LLCwww.company14.comExec Name 14Founder••••••••••••@••••.com86
00015Company 500 LLCwww.company15.comExec Name 15VP of Marketing••••••••••••@••••.com88
00016Company 797 LLCwww.company16.comExec Name 16Founder••••••••••••@••••.com93
00017Company 950 LLCwww.company17.comExec Name 17CEO••••••••••••@••••.com85
00018Company 680 LLCwww.company18.comExec Name 18VP of Marketing••••••••••••@••••.com88
00019Company 547 LLCwww.company19.comExec Name 19CEO••••••••••••@••••.com87
00020Company 368 LLCwww.company20.comExec Name 20Founder••••••••••••@••••.com99
00021Company 454 LLCwww.company21.comExec Name 21VP of Marketing••••••••••••@••••.com86
00022Company 402 LLCwww.company22.comExec Name 22Founder••••••••••••@••••.com87
00023Company 818 LLCwww.company23.comExec Name 23CEO••••••••••••@••••.com84
00024Company 498 LLCwww.company24.comExec Name 24VP of Marketing••••••••••••@••••.com90
00025Company 484 LLCwww.company25.comExec Name 25CEO••••••••••••@••••.com84
00026Company 914 LLCwww.company26.comExec Name 26Founder••••••••••••@••••.com83
00027Company 74 LLCwww.company27.comExec Name 27VP of Marketing••••••••••••@••••.com87
00028Company 551 LLCwww.company28.comExec Name 28Founder••••••••••••@••••.com93
00029Company 285 LLCwww.company29.comExec Name 29CEO••••••••••••@••••.com86
00030Company 532 LLCwww.company30.comExec Name 30VP of Marketing••••••••••••@••••.com90
00031Company 719 LLCwww.company31.comExec Name 31CEO••••••••••••@••••.com94
00032Company 629 LLCwww.company32.comExec Name 32Founder••••••••••••@••••.com81
00033Company 123 LLCwww.company33.comExec Name 33VP of Marketing••••••••••••@••••.com90
00034Company 772 LLCwww.company34.comExec Name 34Founder••••••••••••@••••.com91
00035Company 932 LLCwww.company35.comExec Name 35CEO••••••••••••@••••.com89
00036Company 583 LLCwww.company36.comExec Name 36VP of Marketing••••••••••••@••••.com99
00037Company 480 LLCwww.company37.comExec Name 37CEO••••••••••••@••••.com83
00038Company 501 LLCwww.company38.comExec Name 38Founder••••••••••••@••••.com85
00039Company 372 LLCwww.company39.comExec Name 39VP of Marketing••••••••••••@••••.com87
00040Company 332 LLCwww.company40.comExec Name 40Founder••••••••••••@••••.com84
00041Company 688 LLCwww.company41.comExec Name 41CEO••••••••••••@••••.com98
00042Company 871 LLCwww.company42.comExec Name 42VP of Marketing••••••••••••@••••.com83
00043Company 591 LLCwww.company43.comExec Name 43CEO••••••••••••@••••.com87
00044Company 750 LLCwww.company44.comExec Name 44Founder••••••••••••@••••.com86
00045Company 826 LLCwww.company45.comExec Name 45VP of Marketing••••••••••••@••••.com99
00046Company 370 LLCwww.company46.comExec Name 46Founder••••••••••••@••••.com85
00047Company 339 LLCwww.company47.comExec Name 47CEO••••••••••••@••••.com86
00048Company 656 LLCwww.company48.comExec Name 48VP of Marketing••••••••••••@••••.com81
00049Company 946 LLCwww.company49.comExec Name 49CEO••••••••••••@••••.com99
00050Company 848 LLCwww.company50.comExec Name 50Founder••••••••••••@••••.com99
[ 49,950 ROWS LOCKED ]
>_ SYSTEM.ANALYSIS.LOG_

Scraping real estate leads is a pain. Most brokers gate their data behind shitty CRMs, and the MLS data is locked down. We finally bypassed the API rate limits on public county records and cross-referenced with Zillow's public pages. Got the raw CSV with owner info, property details, and mortgage data. Not perfect, but it's a solid base.

The hardest part was deduplicating. Same person, multiple properties, different spellings. We ran fuzzy matching and manually curated the edge cases. Also had to filter out commercial properties and land only listings. Ended up with 2.3M residential records. That's after dropping ~40% of the junk. The rest is clean enough for cold outreach.

We tested the data against a sample of 10k records. 92% matched valid phone numbers, 98% had correct addresses. We're not doing live enrichment, so if you need current phone numbers, you'll have to run your own. But for a static list, it's better than what most vendors sell. And we update it monthly.

Data Schema & Dictionary

property_address

The full street address of the property. This is the primary key for deduplication. If you're mailing, this is what you use.

owner_name

Full legal name of the property owner. May be multiple names if joint ownership. Useful for personalizing your pitch.

owner_phone

Landline or mobile number associated with the owner. Not guaranteed to be current, but we verified a sample. Expect some dead ends.

owner_email

Email address if publicly available. Rare but gold when present. Usually from business registrations, not personal.

property_type

Single Family, Condo, Townhouse, etc. Filters out commercial junk. You don't want to sell to an apartment complex owner unless that's your thing.

estimated_value

Zillow's Zestimate or our own valuation model. It's a ballpark, not an appraisal. Use it to prioritize high-value prospects.

year_built

Year the structure was built. Older homes might mean more maintenance, so they might be more likely to sell.

mortgage_amount

Outstanding mortgage balance if we could find it. Helps gauge equity. High equity means they can sell and walk away with cash.

last_sale_date

Date of the most recent property transaction. If it's recent, they're less likely to sell again. Filter them out.

last_sale_price

Price paid at the last sale. Combined with estimated value, you can see appreciation. That's a conversation starter.

Frequently Asked Questions

How fresh is this data?
We scrape it on the 1st of the month. If it bounces, tell us and we swap the credit. Simple.
Is this data exclusive?
No. We sell it to multiple buyers. If you need exclusivity, that's a custom deal and it'll cost you. For most people, the price is right.
Can you provide the data in a different format?
We deliver CSV. That's it. If you want JSON, you can convert it yourself in five minutes. Don't ask for API access.
What's your refund policy?
If the data is clearly garbage, we refund. But if you just didn't get any leads, that's on your sales game. We're not responsible for your cold email skills.

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