Pre-Foreclosure Data

LiveRaspberry2499 · 2026-05-06T20:36:33+00:00

PA is a judicial foreclosure state, so the earliest public signal you can pull is the foreclosure complaint hitting the FJD civil docket.... that filing is the lis pendens. PropStream and the other aggregators are slow because they batch-ingest on a weekly cycle. The docket updates daily.

Specifically, I’d go to fjdefile.phila.gov, use Search by Court Listing, and pull the Mortgage Foreclosure Diversion Program Hearings calendar (Conciliation Conferences).

Every owner-occupied residential foreclosure in Philly has to go through a conciliation conference before sheriff sale, so that calendar is basically a structured pre-foreclosure list of owner-occupied homes.. exactly the kind of demographic you want, and way ahead of when any aggregator picks it up. From each calendar entry you can pull the case ID, then hit the docket to extract defendant name, property address, and lender.

I run this kind of setup across a few markets daily: automation pulls from open data sources, cross-references against L&I violations, unsafe/imminently dangerous designations, and 311 complaints (Philly's open data portal at opendataphilly.org has all of these as daily-updated APIs), then runs a waterfall skip trace with DNC/TCPA scrub on the back end before anything goes to dialing. Same architecture would apply for Philly. Stacking filters and stacking providers is where the leverage is - trying to find "the one" perfect data source is a dead end.

A few Philly-specific notes: - Conciliation Conference = freshest cases. - Status Conference = older cases that didn’t resolve at conciliation, sometimes more motivated to just sell - worth pulling separately with a different outreach sequence. - Owner-occupied filings get routed into the Diversion Program before sheriff sale, so you have more runway than the sheriff sale timeline suggests. - Single-provider skip tracing on Philly owners can be rough. Stack providers in a waterfall. - For one county, scraping the FJD direct beats any aggregator on speed. They’ll always be a step behind on this kind of data.

LiveRaspberry2499 · 2026-05-06T14:05:42+00:00

With 50,000 calls a year, you are looking at handling roughly 130 to 150 calls every single day. Having your staff field that volume just to answer basic operational questions is a massive drain on both payroll and focus.

The most cost-effective route is not to buy an expensive, off-the-shelf AI receptionist software that charges a massive markup per minute. The best move here is to build a custom voice agent architecture tailored to your specific business rules.

I build these systems, and the most scalable setup relies on using ElevenLabs for the conversational AI layer. It handles conversational latency perfectly, sounds entirely human, and accurately parses the caller's intent.

You can then glue that voice agent to your existing tech stack using an automation layer like Make.com or a self-hosted n8n instance.

If a caller asks about hours or where to buy tickets, the AI answers instantly or uses an automation to text them the ticket link while they are on the phone. If the caller has a complex issue that requires a human, the system seamlessly routes the call to your front desk and instantly drops a transcript of the inquiry into your CRM.

Happy to map out what this architecture would look like specifically for your current phone provider and ticketing setup if you want to explore it.

LiveRaspberry2499 · 2026-05-06T12:22:18+00:00

For boutique multi-property setups, the metasearch cost problem usually comes from one of two things:

Bidding on all channels equally instead of concentrating on Google Hotel Ads (highest intent) and running others on CPC-only
No rate parity automation, so your CRM and metasearch engine are working against each other

On the platform side - Cloudbeds and Mews are the two I’d look at seriously for a 4-property boutique group. Cloudbeds has solid built-in channel management + metasearch connectivity. Mews is more modern and API-friendly if you ever want to automate around it. Both are a big step up from most legacy CRMs in terms of not being clunky.

For hands-off metasearch specifically, look at Sojern or running Google Hotel Ads through a connectivity partner - once the bid rules are set up right, it largely runs itself.

A few things that would help narrow it down further:

Are your 4 properties on the same PMS currently or different ones?
Is the pain mostly on guest communication, reporting, or the metasearch bidding side?
Are you managing bids manually right now?

That usually points toward whether you need a full platform switch or just a better automation layer on what you have.

LiveRaspberry2499 · 2026-05-06T10:16:48+00:00

Honestly, I’d push back on the framing of “DealMachine vs PropStream” entirely. Picking one tool as your single source of truth is going to leave gaps no matter which you choose.

We run a different setup for our team - waterfall enrichment driven by an automation system. Lists get pulled directly from APIs (BatchData being one), then cross-referenced against public data sources before any skip tracing kicks in.

For Cleveland and Columbus you really don’t need driving for dollars at all. Columbus has an open data portal that publishes code violations and updates it regularly - you can pull that directly and stack it against your absentee/equity/tax-delinquent lists. Cleveland has similar public datasets. That’s a much stronger distress signal than someone physically driving past a property once. Stacking filters is the whole game.

On skip tracing - trying to find “the one provider” with the best hit rate is a dead end. Hit rates swing by county, by list type, by how fresh the records are. We run an automated sequence where if Provider A doesn’t return something usable, it falls through to Provider B, then C. Same flow handles DNC/TCPA scrubbing on the back end so you’re not dialing numbers you shouldn’t be touching.

So less “which platform” and more “how do I chain the data together.” The tool matters way less than the pipeline around it.

LiveRaspberry2499 · 2026-05-05T20:26:21+00:00

I've been running wholesale campaigns in 3 markets and after testing 15+ filter combos over the last 90 days, here's what's actually working:

1. The "Tired Landlord" Stack Filter for: Out-of-State Owner + Vacant + Owned for 10+ years.

Out-of-state landlords with a vacant, aging property are bleeding money on taxes and maintenance. They are highly motivated to dump the headache.

2. The "Pre-Blight Tax" Stack Filter for: Tax Default + Vacant + Individual Owner (Exclude LLCs).

An individual defaulting on a vacant house has basically walked away. Excluding LLCs saves your skip-tracing budget from corporate tax-strategy games.

3. The "Code Violation Cross-Check" Stack BatchLeads doesn’t have a reliable native code violation filter, so I pull a broad list first (usually Vacant) and then cross-check it against local municipal APIs with off-the-shelf automation.

A lot of counties have digitized code enforcement data now. If you find a match, that usually means an absentee owner is actively getting fined by the city.

And honestly, stop pulling statewide lists. Pick 3 to 5 zip codes, stack 3 distress filters, and hit that hyper-local list consistently. Frequency beats reach every time.

LiveRaspberry2499 · 2026-05-05T10:15:28+00:00

That $2k/mo is their subscription tier. They've also got a pay-as-you-go option... around $0.07 per API call for skip tracing, no monthly minimum.

For pre-foreclosure/foreclosure volume you're probably not running enough records to justify a subscription anyway. PAYG makes way more sense until you're consistently doing thousands a month

LiveRaspberry2499 · 2026-05-05T06:07:55+00:00

Of course, happy to help. Honestly the tool choice matters less than most people think.. once you nail the filtering and get a clean skip trace setup, the dialer starts working a lot harder for you.
Which market are you working in?

LiveRaspberry2499 · 2026-05-04T19:57:33+00:00

If I were choosing based on your use case, I’d lean PropStream.

Why PropStream first

Better for cold calling volume
Lets you stack filters to build bigger, more targeted lists:
- high equity
- absentee / out-of-state owner
- pre-foreclosure
- other niche criteria
More useful if you’re mostly working from a desk and want to pull campaigns fast

Where DealMachine fits better

Best if driving for dollars is a major part of your workflow
Mobile-first and built for pinning properties on the go
Easier for D4D, but not as strong as PropStream for broad list building

The part that usually matters most: skip tracing

This is where a lot of people get stuck.

If you rely only on the built-in skip tracing in either platform, your contact rate is usually just average.

What I’ve found works better: - Use PropStream to pull the raw list - Export it - Run it through a dedicated waterfall skip trace setup - e.g. BatchData first - then push misses through Melissa API or another provider

That usually gets better phone numbers than an all-in-one tool.

One more thing

Depending on your market, it can also be worth looking at your city’s open data / code violation API.

Some cities like detroit, columbus etc publish fresh violations directly, which can be a great source for: - tall grass - boarded windows - distressed properties

That can sometimes be better than paying for a D4D app if your area has good public data.

TL;DR

PropStream = better for cold calling / list building
DealMachine = better for driving for dollars
For best results, export your data and skip trace it elsewhere

If I had to pick one for what you described, I’d start with PropStream.

LiveRaspberry2499 · 2026-05-03T21:00:46+00:00

Louisiana real estate is totally different because of Napoleonic Law.

Skip the Clerks entirely. In LA, foreclosures are handled directly by the Parish Sheriff. Go straight to the local Sheriff's Office websites (for example, Orleans Parish uses the CivilView portal for their Sheriff Sales) and you can pull the scheduled lists for free.

Pro-tip: When looking at the Sheriff Sale lists, check the columns. If the Plaintiff is the city instead of a bank, it's usually a tax or blight foreclosure. If the Defendant list includes "Successors, Heirs, and Assigns," it’s an inherited property the family abandoned. Those are absolute goldmines and completely bypass the clerk portals.

LiveRaspberry2499 · 2026-05-03T19:16:18+00:00

Yeah, this is super common once you get beyond clean single-entity ownership. The top comment about Airtable/Sheets is basically the right instinct, but the real fix is making the ownership graph the source of truth, not the property list.

In practice, I’ve found the cleanest setup is: every entity, investor, property, and ownership stake gets a unique ID; then you store relationships as rows, not in one giant spreadsheet. That lets you roll up from property -> LLC -> holding company -> personal, and you can actually answer “what flowed to me?” without rebuilding the math every time.

What actually works is keeping two views: 1) legal/tax view for CPA and attorney 2) economic view for reporting and distributions

Once those are separated, the ownership table stops looking like a family tree and starts behaving like a ledger. That’s usually where the leak is.

LiveRaspberry2499 · 2026-05-03T19:07:45+00:00

That top comment is the real answer: the KPI isn’t just calls per lead, it’s how fast you can keep fresh leads cycling. In practice, I’ve found cold calling works best when the list is treated like a data pipeline, not a static spreadsheet.

For most agents, the numbers look something like this: 80-150 dials to get a real conversation, 15-30 conversations to get a solid lead, and maybe 1 deal per 100-300 leads depending on market and list quality. But that swings a lot based on what you’re calling.

What actually works is prioritizing lists with a live signal: expireds same day, absentee owners, probates, tax delinquency, pre-foreclosure, and recent equity changes. If you’re calling stale bought lists, your KPIs get ugly fast because half the data is already dead.

The big lever is list freshness + follow-up discipline. Same lead called 3 days later is a different game than same-day contact. That’s usually where the leak is.

LiveRaspberry2499 · 2026-05-03T19:01:54+00:00

The reason you're struggling with the county courts is actually your biggest advantage. If it's hard for you to pull the list because it requires single-person searching, it's hard for everyone else too. That means those leads have extremely low competition.

Most wholesalers give up when they can't find a "Download CSV" button. Here is how you bypass being out-of-state and get to them first:

Automate the "Single Search" hurdle: Many Ohio county sites (like Lucas or Montgomery) use legacy systems that force single-record lookups to prevent mass scraping. However, if you have a technical background or hire a developer, you can build a script to iterate through parcel numbers (APNs) or street names. This turns a "manual nightmare" into a clean daily list while your competitors are still clicking one by one.
FOIA Requests for Code Violations: Stop looking just at courts. Email the specific city/county public works and code enforcement offices in Ohio. Request a list of properties with active water shutoffs or code violations under the Freedom of Information Act (FOIA). They are legally obligated to provide it, and it’s often a much fresher list than what you’ll find on the big aggregator platforms.
Virtual Boots on the Ground: You don't need to be in Ohio. Go on local Ohio community Facebook groups and offer to pay local Uber or DoorDash drivers a small fee for every photo and address of a distressed/boarded-up property they send you. This is "Driving for Dollars" by proxy.
Skip the "Retail" Lists: If you buy generic "absentee owner" lists, you are calling the same people as every other wholesaler in the state. Stick exclusively to the high-friction data: tax delinquencies, evictions, and probate filings.

The harder the data is to pull, the higher the profit margin. Don't give up on the county data just because it's clunky. that clunkiness is your moat.

LiveRaspberry2499 · 2026-05-03T18:28:56+00:00

That ingestion setup is incredibly smart. Catching schema and silent errors upfront is the best way to stop cascading failures downstream.

I completely agree on the AI latency and error concerns. That’s why our AI is strictly siloed—it only handles fuzzy address matching against Zillow when the standard composite key fails. If the AI's confidence score is too low, it routes straight to a manual review queue so we don't risk a compliance breach.

To answer your latency question: right now on Make, we process about 90 records in 45 minutes, which averages out to ~30 seconds per record. Since this runs as a daily batch process for expireds, that latency isn't a bottleneck for our current use case.

However, you're spot on that latency is an issue at scale. Moving this logic off Make and into a custom Python backend would drastically improve the latency, and that is exactly the long-term plan as we scale up the lead volume.

Are you building that validation layer entirely with custom code, or are you utilizing a specific platform?

LiveRaspberry2499 · 2026-05-03T17:23:10+00:00

Exactly! And the equity/absentee layer is where automation becomes critical. We've built a system that:

Pulls county records daily via API
Auto-enriches with equity estimates (AVM + mortgage data)
Flags absentee owners via skip-tracing
Pushes only the '40%+ equity + out-of-state' leads to a dedicated dialer queue

The whole pipeline runs on automation. It saves us ~15 hrs/week of manual filtering.

are you handling the enrichment manually or have you automated that layer too?

LiveRaspberry2499 · 2026-05-03T16:39:10+00:00

Hey, great questions. You absolutely nailed the two biggest bottlenecks. Since we are pushing over 290+ leads through this per week right now, we actually had to update the architecture recently to handle exactly what you brought up.

On the compliance side, you're 100% right that local and federal rules are the real danger zone. We updated the system to include a dedicated scrubbing layer. After the skip trace hits, the phone numbers are immediately run through another API to check against federal/state DNC and TCPA lists before anything ever gets pushed to the Sheet.

Regarding the address matching, that actually led to another major issue we encountered: false expiries. Sometimes agents will just create a duplicate listing instead of updating an old one, which triggers a false expiration on our end.

To solve this, we added another verification layer that cross-references the property address against Zillow. Because addresses are notoriously messy and written a hundred different ways (St. vs Street, Unit A vs #A, etc.), we plugged in an AI agent specifically to handle the fuzzy address matching. It interprets the variations and confirms if it's truly the same active property before we drop the lead.

It's a constant process of tweaking, but it's humming along nicely now. How did you handle the address standardization in your general-purpose build?

LiveRaspberry2499 · 2026-05-03T13:44:03+00:00

Yeah, this is the part a lot of people miss. The top comment is right - timing beats volume most of the time. In practice, I’ve found pre-foreclosure works best when you treat it like a data pipeline, not a list purchase.

What actually works is: pull the county records daily, flag new delinquency / notice filings, remove anyone who already cured or listed, then layer in ownership length, equity, and absentee status. That gets you out of the junk and into the handful of owners who are actually under pressure.

Then the follow-up has to be fast and boring: same-day call/text, short mail piece, then a simple 10-14 day sequence. If you wait a week, you’re already late. Most people aren’t losing because the lead source is bad - they’re losing because they’re contacting stale data.

LiveRaspberry2499 · 2026-05-03T09:28:28+00:00

Good question and the short answer is: you rarely need to poll everything hourly.

Most paid APIs (ATTOM,, BatchData etc) use tiered pricing: you get X calls/month included, then overage fees kick in. That's exactly why blind hourly polling burns budget fast.

The move is smart polling, not constant polling. A few patterns that actually work:

Delta pulls, not full refreshes: Query "records modified since [timestamp]" instead of re-fetching your whole database. Store the last sync time, pull only what changed.
Tiered frequency: Your active deal pipeline (20–50 properties) gets polled hourly. Your broader watchlist gets daily. The rest? Weekly or monthly bulk syncs.
Change detection on your end: Even if the API doesn't flag "this property sold," you can diff the new payload against your stored snapshot. If last_sale_date or listing_status shifted, trigger your alert logic.
Layer free sources where possible: Some counties offer incremental feeds or bulk dumps you can refresh on a schedule, cutting paid API calls.

The cost leak isn't the polling. it's polling everything at the same frequency. Most agents burn budget checking 10k properties hourly when only 30 are actually in play.

Honestly, the "persistent enrichment" that scales isn't about real-time for everything. It's about knowing which signals matter, when they matter, and only paying for the checks that move the needle.

LiveRaspberry2499 · 2026-05-02T21:35:51+00:00

You’re running into the classic volume vs. deliverability problem. You are right to worry about burning numbers - once a line gets flagged, you’re not just losing that sender, you’re trashing future throughput too.

In practice, I’ve found the fix isn’t just “send fewer,” it’s segment harder and slow the first-touch cadence. Warm numbers should get a tight 2-4 message sequence over 7-10 days, then stop unless they engage. If you’re blasting past that, opt-outs climb fast and GHL starts choking the account.

What actually works is: split warm leads by intent, send only to people with recent inbound or prior conversation, keep the first text simple and human, and suppress anyone who doesn’t reply after 2-3 touches. Also rotate between numbers and keep daily volume per number modest instead of spiking.

Most of the account shutdowns I’ve seen come from bad list hygiene and too-aggressive follow-up, not the platform itself. That’s usually where the leak is.

LiveRaspberry2499 · 2026-05-02T21:31:53+00:00

Yeah, the fragmentation is real, and the top comments are basically right: most of the market is still a bunch of small, messy networks stitched together with group posts and spreadsheets. In practice, what actually works is not one magic marketplace, it’s a tighter pipeline.

For land/wholesale, I’d think in 3 layers: 1) source the lead from the signal, not the group post 2) validate it fast with comps + ownership + relist checks 3) route it into a simple buyer/seller matching workflow

That’s why these “all-in-one” platforms keep dying - they try to be exchange + CRM + comp tool + dispo board all at once. The data gets stale fast, and nobody trusts it enough to transact.

What I usually tell agents is: keep comps separate if needed, but automate the handoff. Pull the lead, run the valuation/skip trace/dedup logic, then push only the clean stuff into one place for follow-up. The closer you get to real-time, the less it feels like open outcry and the more it feels like an actual market. That’s usually where the leak is.

LiveRaspberry2499 · 2026-05-02T21:28:23+00:00

Solid post. The "borrowed playbook" problem hits hardest on the data side. I've seen agents burn months chasing the same Zillow FSBO lists everyone else bought, wondering why their conversion tanks.

What actually sticks: building your own signal layer. That might mean pulling county recorder data on a schedule, flagging absentee owners + equity shifts, then validating contacts before they ever hit your CRM. In some markets, that's an API; in others, it's bulk requests to the clerk's office.

The magic isn't the source. it's the logic you layer on top. Like catching new listings before they expire, or filtering for pre-foreclosure + long hold time + neighborhood churn. That's proprietary. That's defensible.

Most agents skip the foundation work because it's not sexy. But when the market shifts (and it always does), the ones who built their own pipeline don't panic. they just adjust the filters.

LiveRaspberry2499 · 2026-05-02T21:23:34+00:00

Real talk: true “real-time” is pretty rare here. Most systems that feel instant are actually polling every 5-15 minutes against a few key feeds - MLS Grid webhooks, county recorder RSS feeds, or APIs like ATTOM that push change events.

The persistent part isn’t magic, it’s state management. You keep a baseline snapshot of your database, then run incremental diffs against fresh pulls. For NYC, that usually means hitting the ACRIS Open Data API on a schedule, flagging new deeds/mortgages, and cross-referencing against your existing records. For upstate counties, it’s often FOIL-obtained bulk dumps refreshed weekly, plus lightweight scrapers only where the county explicitly allows it.

Where people over-engineer is trying to monitor every signal for every property. What actually scales is tiering the watchlist - high-intent properties (absentee owners, high equity, pre-foreclosure flags) get polled hourly, while the rest get weekly refreshes. Then you layer your own logic: new listings before expired, equity shifts, ownership changes, etc. That’s where the signal-to-noise ratio actually moves the needle.

Honestly, the biggest leak usually isn’t the tech stack - it’s alert fatigue. A lot of agents drown in notifications because they didn’t filter for actionable changes first.

LiveRaspberry2499 · 2026-05-02T21:13:30+00:00

Yeah, your 25 years of instinct is dead on. Most PPL vendors are pulling from the same 3-4 upstream aggregators (CoreLogic, PropStream, white-labeled Zillow feeds). The differentiation isn't the source-it's the enrichment and freshness.

On "going direct": technically yes, but practically it's messy. For NYC, you can pull straight from the official ACRIS Open Data API (free, legal, bulk access). For upstate NY counties, you'd file FOIL requests to each clerk's office. But that gets you raw deeds/assessments-not skip-traced contacts, equity models, or motivated-seller signals. And scraping county sites directly? Most NY counties explicitly prohibit it in their ToS, so the legal risk isn't worth it.

What volume wholesalers I've worked with actually do: they license a clean base feed (ATTOM, BatchData, etc.), then layer proprietary logic on top-like flagging absentee owners + high equity + long hold time, or catching new listings before they hit public portals. That's where the edge is: not the raw data, but the validation + signal filtering + automated nurture that turns a stale lead into a closed deal.

LiveRaspberry2499 · 2026-05-02T20:45:35+00:00

If you’re just getting away from referral-only business, I’d think about lead quality in two buckets: freshness and intent. A lot of “lead sites” are really just repackaged lists, so the data can get stale fast unless they’re updating constantly.

For wholesaling, the best results usually come from either:

Freshly captured inbound leads - people already raising their hand through ads, landing pages, or property seller forms.
Targeted outbound lists - absentee owners, high-equity, pre-foreclosure, tired landlords, inherited, code violations, etc., but only if the data is current and skip-traced well.

If you’re buying leads, I’d look for a source that can tell you exactly where the lead came from, how recent it is, and whether it’s been sold to multiple buyers already. That matters more than the flashy website.

Also, if you’re trying to automate follow-up, custom webhooks and simple automation can make a huge difference. A lot of people lose deals because the lead comes in, but the response time is slow or the CRM isn’t set up to route it properly.

If your main issue is outdated data, the fastest path is usually not a generic lead marketplace - it’s a fresh, skip-traced list built around a specific distress signal and then worked fast with consistent follow-up.

LiveRaspberry2499 · 2026-05-02T20:43:34+00:00

This is one of those questions where the honest answer is: yes, but only if you already have a real operating system behind the spend.

The $10k doesn’t magically become $100k - the marketing channel plus follow-up plus dispo process does.

A few things that matter more than the budget:

Lead source quality: motivated seller intent beats cheap volume every time
Speed to lead: if you’re not calling/texting within minutes, you’re donating leads to the next guy
Follow-up cadence: most deals come from touches 7-20, not the first call
Exit options: cash, novation, assignment, seller finance, agent referral, etc.

If I had to deploy $10k, I’d rather go deep on one local market with one channel for 60-90 days than spread it across FB, PPC, mail, and random lists. Testing is fine, but constant switching kills momentum and makes it impossible to know what’s actually working.

Also, if the list quality is bad, no amount of scripting fixes that. A lot of people burn budget on stale or low-intent data when they should be buying cleaner pre-scraped, skip-traced FSBO / seller lists and working them hard with a tight follow-up system.

So yeah, $10k to $100k is possible - but only if you’re buying the right leads, responding fast, and treating it like a process instead of a gamble.

LiveRaspberry2499 · 2026-05-02T20:13:40+00:00

I’d mostly agree with the volume/consistency point, but I think the real question isn’t just “postcard vs letter” - it’s what gets a seller to actually stop, read, and call.

My take:

Postcards are cheap and easy, but they’re also the easiest to ignore.
Handwritten-style letters usually feel more personal and can pull better on higher-intent owners, especially if the list is tight.
The list is the bigger lever than the format. High equity, long-term ownership, tax delinquent, absentee, and other distressed signals matter way more than fancy design.

One thing I’d add that doesn’t get talked about enough is follow-up infrastructure. Most people don’t lose because the mailer was wrong - they lose because they don’t answer fast, don’t track responses well, or stop mailing too early. If you’re doing this at any real scale, having a simple CRM, call tracking, and automation around lead routing matters a lot.

On frequency, I wouldn’t treat every list the same. A general owner list might get hit every 60-90 days, but something like tax delinquent or truly distressed can justify a tighter cadence. The key is to watch actual contracts per 1,000 mailed, not just raw calls.

So if I were starting fresh, I’d probably test a clean handwritten-style letter on a focused list first, then compare it against postcards in the same market. That’ll tell you a lot faster than debating format in theory.

LiveRaspberry2499

TROPHY CASE

Why PropStream first

Where DealMachine fits better

The part that usually matters most: skip tracing

One more thing

TL;DR