Everyone in this business preaches "stack your lists." Almost nobody publishes what stacking actually looks like, because almost nobody has the data to. Here's ours. These are real co-occurrence numbers from the live database, not an industry rule of thumb.
One scope note up front, because it matters. Our code violation data spans seven Puget Sound markets, but the other signals, 311 complaints, expired permits, and fire incidents, are Seattle-only right now. So the stacking numbers below are Seattle, where we track all four. That's still 11,686 violation properties to work with.
How often a second signal lands on a violation property
Take Seattle's violation properties and ask a simple question: how many also show up in another public-records system? The overlap is bigger than most people expect.
| Second signal | Violation properties that also have it | Share of Seattle violation properties |
|---|---|---|
| 311 complaint (dumping, overgrowth, encampment) | 4,829 | about 41% |
| Expired building permit | 1,240 | about 11% |
| Fire incident | 549 | about 5% |
More than four in ten cited properties in Seattle also have a distress-related 311 complaint on record. That's not a coincidence; it's the same neglect showing up in two different systems. One in nine has an expired permit, a stalled project. One in twenty has a fire incident.
How deep the stack goes
Co-occurrence with one signal is useful. What you really want is the properties where several signals converge, because that's where distress is least ambiguous. Looking at our scored leads by how many independent signals they carry:
| Signals on the property | Scored leads |
|---|---|
| Violation only | 8,708 |
| Violation + 311 | 3,069 |
| Violation + expired permit | 602 |
| Violation + fire | 147 |
| Violation + two or more other signals | 698 |
Put the stacked rows together and about a third of our scored leads (roughly 4,500) carry at least one signal beyond the code violation. Nearly 700 carry two or more extra signals, a property that's been cited and reported to 311 and has a stalled permit or a fire on record. Those are the leads at the very top of the list.
Why this is the whole strategy
A single signal is a guess. A weeds citation might be distress or might be a homeowner on vacation. The reason signal stacking works isn't a magic conversion rate, and we don't claim one. It's that each independent record you add shrinks the list and raises the odds the owner behind the address is actually under pressure. Two systems flagging the same house is a stronger statement than one.
The numbers above are the proof. Distress genuinely clusters: the same properties keep showing up across violations, 311, permits, and fire. That's what a distress score is built to capture, and it's why a small, stacked list beats a big single-source one. It's also data no lead vendor can hand you, because they don't hold the underlying records the way a city-data tool does. If you want the method behind the numbers, start with the guide to property distress signals.
Frequently asked questions
What does it mean to stack distress signals?
It means cross-referencing independent public records, code violations, 311 complaints, expired permits, fire incidents, and prioritizing the properties that appear in more than one. Each additional signal narrows the list and raises the likelihood the owner is genuinely distressed. It's the opposite of mailing one big single-source list.
How often do code violations overlap with other signals?
In our Seattle data, about 41% of cited properties also have a distress-related 311 complaint, about 11% have an expired building permit, and about 5% have a fire incident on record. Roughly a third of scored leads carry at least one signal beyond the violation itself.
Do stacked signals guarantee a motivated seller?
No, and we don't make probability claims. Stacking is a ranking method, not a guarantee. What the data shows is that distress clusters: the same properties recur across multiple public-records systems, so a property flagged by several signals is a better bet to contact than one flagged by a single citation.
Where does this data come from?
From the FlaggedLeads live database. Code violations cover seven Puget Sound markets; 311, expired permits, and fire incidents are Seattle-only today, so the co-occurrence figures here are for Seattle, where all four signals are tracked. The numbers refresh as the data updates.
Can I reproduce these numbers?
The underlying records are all public, code violations, 311, permits, and fire incidents are published by the city, so the overlaps are reproducible by anyone willing to pull and match the datasets. The work is in normalizing addresses across systems that each format them differently, which is what the tool automates.