How it works — no black boxes

We read city complaint data, group nearby complaints together, and rank areas by activity. Here's exactly how. You can see where every number comes from.

Data Sources

Built on public government data

1

City Inspection & Complaint Records

Official government databases · Updated daily

City health departments conduct property inspections across commercial and residential buildings. When someone reports a pest problem, water leak, or code violation, the city logs it — with the address, date, type of issue, and inspection result. All of this is tracked in official city databases and updated continuously.

What the data includes:

  • Inspection date and location (address)
  • Inspection result (passed, failed, action taken, etc.)
  • Type of complaint or inspection
  • Borough and area information

Update frequency: We check for new records regularly. Most recent data is typically 2–7 days old.

2

City Property Records

Official government property database · Updated periodically

Every property in the city is classified in official government records. We use this data to identify whether a property is commercial, residential, or industrial — and how many units it has. This helps you prioritize the big jobs.

What the data includes:

  • Property type (commercial, residential, industrial)
  • Building size and number of units
  • Property address and location
  • Zoning and building classification

Update frequency: Property records are typically updated annually by the city. We ingest updates as they become available.

Process

Four steps. One email per week.

1

We read city data

Inspection records, complaints, and violations are pulled regularly from official city data sources. We focus on the most recent records to keep your list fresh.

2

We group complaints by area

Complaints near each other get grouped together into areas. If multiple properties in the same area have recent complaints, that's an area worth knowing about.

3

We check property type

Each complaint is matched to city property records so you know if it's a restaurant, apartment building, office, or house. Commercial properties are flagged so you can prioritize the big jobs.

4

We rank and deliver

Areas are scored using multiple factors — how many complaints, how recent, whether properties have repeat issues, and the property mix. Every Monday, you get the top areas in your territory. Takes 30 seconds to skim.

Why a 7-day window? A rolling 7-day window balances recency (identifying emerging problem areas) with stability (avoiding noise from a single isolated complaint). Daily updates with day-over-day comparisons help you see which areas have sustained activity versus temporary upticks.

Scoring

How areas are ranked

Each area gets a score based on how much activity is happening there. Higher scores mean more complaints, more recent activity, and more properties involved. Here's what goes into the score:

What the score considers

Factor

Recent failed inspections

Properties with failed inspections or active complaints in the past 7 days. More recent activity = higher score.

Factor

Overall complaint volume

Total number of inspection records and complaints for properties in the area over time.

Factor

Repeat properties

Properties that show up more than once in recent data. Repeat complaints indicate persistent problems — your warmest leads.

Factor

Number of properties

How many different properties in the area have activity. More properties = more potential jobs.

High scoreLots of recent, concentrated activity
Medium scoreModerate activity worth watching
Low scoreEmerging or declining activity

Using the data

What to know before you call

These leads work best when you understand how the data behaves. Here's what experienced operators keep in mind:

Data is 1–7 days old

Records reflect conditions from earlier in the week. A failed inspection doesn't guarantee there's still an active problem today — the property may have already been treated. Best practice: treat these as warm leads and do your own assessment on-site.

Property classifications can lag

Building classifications are updated periodically, not in real-time. A property that recently changed use may still show its old classification. If something looks off, trust what you see on the ground.

Area boundaries are approximate

We group complaints by geographic proximity using clustering algorithms. If your service area is smaller or larger than our areas, boundaries may not align perfectly with your territory.

Complaints are leads, not guarantees

Multiple complaints at one address signal a strong lead, but not every address will convert. The operators who get the most out of this data treat it as a prioritized call list — not a guarantee.

Multi-complaint locations close fastest

Addresses with repeat activity have the highest conversion rates because the problem is confirmed and ongoing. Start your week there, then work outward to surrounding properties.

Disclaimer

DemandZones organizes public government data to help local service businesses identify potential opportunities. Areas and addresses are based on complaint and inspection records — not confirmed service needs. Actual results depend on your outreach, pricing, and local market conditions.