Best Zip Codes for Roofing Leads (And How to Find Yours)
A data-driven framework for picking the zip codes that convert highest for your business — not just the ones with old roofs. Four variables and a 4-quadrant scorecard.
A roofer asked me last month: "Just tell me — which zip codes in DFW are the best for roofing leads?" Fair question. Wrong answer.
Cross-check candidate ZIPs against the free US hail map — recent 1"+ hail moves a ZIP to the top of the list.
Because the best zip codes for your shop are not necessarily the best for the shop down the street. The right answer depends on at least four variables: roof age distribution, household income, insurance claim density, and the neighborhood-replacement cascade effect — all weighted against your specific shop's close rates and job preferences.
This post is the framework I use to score zips. It's repeatable, data-driven, and gives you a personal answer in about 90 minutes of analysis work per metro.
Why "best zip" isn't a universal answer
The three biggest reasons one zip wins for some shops and not others:
1. Job preference / specialty. A shop that specializes in luxury architectural shingles wants different zips than a shop doing standard 3-tab insurance work. Same metro, different ideal zips.
2. Service area + drive time. A great zip 35 minutes from your average job site is worse than a mediocre zip 10 minutes away. Drive time eats margin.
3. Sales-team strength on different door types. If your reps are stronger with older retired homeowners than with younger families with kids, zip demographics matter. If they're equally strong, demographics matter less.
The framework below produces a score per zip. The same framework, applied to two different shops, will produce different rankings — because each shop's weights are different.
Variable 1: Roof age distribution
The highest-leverage variable. A zip where 30% of homes are in the 18-25 year roof age window will outperform a zip where only 8% are, by 3-4x.
How to measure:
Pull property records for the zip (free at most county appraisal districts). Filter by year-built. The roof age proxy is today's year − year_built for any home without a recent re-roof permit. The year-built proxy is the weak point of the whole method, because a 1998 house that was re-roofed in 2021 reads as a 27-year-old roof when it is a 4-year-old roof. If you want to see how that gap gets closed from imagery rather than records, this is how contractors find homes with old roofs without door-knocking.
For a typical DFW zip, 4 distributions are possible:
| Distribution | What it looks like | Roofer outcome |
|---|---|---|
| Young cohort | 70%+ homes under 15 yrs old | Skip — low volume |
| Even spread | 25% in each age bucket | Moderate volume, evergreen |
| Mature cohort | 50%+ homes 18-25 yrs old | High volume, prime years |
| Aged cohort | 50%+ homes 25+ yrs old | Mixed — many already replaced |
The mature cohort zips are the sweet spot. Replacement decisions cluster within a 5-year band, and these zips have the highest density of homeowners in active decision-making.
In DFW, examples of mature-cohort zips (homes built 2000-2008):
- 75024 (West Plano)
- 75093 (Plano east)
- 75070 (McKinney south)
- 76016 (Arlington north)
- 75013 (Allen)
This is publicly-knowable data. Your local equivalents take ~10 minutes per zip to compute from year-built records.
Variable 2: Household income + replacement spend correlation
A roof replacement is a $10-25k decision. Homeowners in lower-income zips don't avoid replacement — they defer it. Higher-income zips replace on schedule; lower-income zips replace when it leaks.
Three ways this affects your prospecting:
- Higher-income zips = higher close rates on full replacement (vs. repair)
- Higher-income zips = bigger ticket sizes (premium shingle upgrades, full property work)
- Lower-income zips = higher volume of repair work but lower per-job revenue
The metric to look at: median household income + median home value. Both are in census + zillow data, free.
For most residential roofing shops, the sweet spot is median income $100-180k. Higher than that and luxury construction firms dominate; lower and the deferred-maintenance problem reduces close rates.
DFW median income approximation for the zips above:
- 75024: ~$135k (Plano, high replacement-on-schedule)
- 75093: ~$165k (Plano, higher tier)
- 75070: ~$120k (McKinney, solid middle)
- 76016: ~$95k (Arlington, mixed — defers more)
- 75013: ~$130k (Allen, solid)
Variable 3: Insurance claim density
In storm-belt regions, insurance-driven replacement is a meaningful share of volume. The closer-to-real-time signal: how many roof-related insurance claims have been filed in this zip in the last 24 months?
Some state insurance departments publish this. Texas Department of Insurance publishes aggregate hail claim data by zip on a 6-12 month lag. Florida and Colorado have varying availability.
Where you can get this data:
- Texas: TDI bulletins (somewhat clunky to query)
- NOAA Storm Events: confirmed hail in the zip in the last 24 months — proxy for claim potential
- Local public adjuster networks: they track this for their own work; sometimes share informally
The signal: zips with confirmed hail events + above-average insurance claim density = likely high storm-driven replacement volume. Even if you're not pursuing insurance work directly, these zips have high replacement activity. If storm work is your bread and butter, the free and paid tools for finding storm-damaged roofs are worth an afternoon before you commit a season to a zip.
For DFW, the zips most affected by 2024-2026 hail events (rough order):
- 75150, 75180, 75181 (Mesquite, hit repeatedly)
- 76016, 76017 (Arlington, hail-active)
- 75044 (Garland)
- 75070, 75071 (McKinney south)
Variable 4: Neighborhood replacement cascade effect
The most overlooked variable. When 3+ homes on a block replace their roofs in a quarter, the next 5-10 on that block become 3-4x more likely to replace within the next 18 months.
The mechanism: social proof. Homeowners see their neighbors investing, they hear talk over the fence, they get the comparative-aging conversation ("my roof is the same age as the Johnsons'..."). Within 12-18 months, half a block can replace.
How to detect cascades at the zip level:
- County permit data — pull all roof permits in the zip from the last 12 months
- Geo-cluster the permits — anywhere 5+ permits sit within a 400-foot radius is a cascade zone
- Multiple cascades = active zip — a zip with 4-6 active cascade zones is in an active-replacement cycle
Cascade-active zips outperform comparable zips by 2-3x on close rates because every door you knock benefits from "your neighbors just did this" social proof. And this is the one variable where a zip-level average actively lies to you: a zip with six hot blocks and forty dead ones scores the same as a zip that is uniformly lukewarm, and only one of those is worth your Monday.
Putting it together: the 4-variable scorecard
For each zip in your candidate set, score 1-5 on each variable. Total score out of 20.
| Variable | Score 1 (low) | Score 5 (high) |
|---|---|---|
| Roof age (% homes 18-25 yrs) | Under 10% | Over 30% |
| Income (median household) | Under $70k | $100-180k |
| Insurance (recent claims) | None | Active hail event past 24 mo |
| Cascade (active clusters) | 0-1 in zip | 4+ in zip |
A zip scoring 15+ is a top-tier prospect zip for your shop. A zip scoring 8-12 is moderate. Below 8 = skip.
Important: weight the four variables based on YOUR shop's profile.
- Insurance-restoration specialists: triple-weight Variable 3 (insurance density)
- Retail-cash-job shops: triple-weight Variable 2 (income)
- High-volume door-knocking shops: triple-weight Variable 1 (roof age density)
- Storm-chase shops: triple-weight Variable 3 (insurance) + Variable 4 (cascade)
The same scoring framework, different weights, gives you a personalized answer instead of a generic best-zip list.
A worked example: scoring 5 DFW zips
Using equal weights, here's how the framework scores five DFW zips for a residential generalist shop:
| Zip | Roof age | Income | Insurance | Cascade | Total | Rank |
|---|---|---|---|---|---|---|
| 75024 (West Plano) | 4 | 5 | 2 | 4 | 15 | Top |
| 75070 (McKinney south) | 5 | 4 | 4 | 4 | 17 | Top |
| 75150 (Mesquite) | 3 | 3 | 5 | 3 | 14 | Moderate-top |
| 76016 (Arlington north) | 4 | 3 | 4 | 3 | 14 | Moderate-top |
| 75093 (Plano east) | 4 | 5 | 2 | 3 | 14 | Moderate-top |
For a generalist DFW residential shop, 75070 ranks #1 — highest combined signal across all four variables. For an insurance-restoration specialist, 75150 (Mesquite) would top the list because of the Variable 3 weighting.
Automating the scoring
The four variables can all be pulled from public data, but doing it manually for 30+ zips per metro is a half-day of work per quarter.
This is where AI prospecting tools save time. There is a whole category of them now, and the best AI-powered tools for identifying roofing prospects by zip code is a fair comparison of what each one actually does with a zip.
Roofbird, the tool I build, takes the same four variables and skips the zip average. Before you even draw a polygon, it tells you which blocks in a city are worth your morning — housing era, share of roofs reading worn, real home count from building footprints, hail in the last 12 months, and whether the block is walkable or scattered acreage, because scattered acreage on long driveways is bad canvassing even under a perfect storm. Click a suggestion and it draws the area for you. Every lead then carries two scores: NEED (how bad the roof is) and NOW (whether anything is forcing a decision on that specific house). Neighbourhood hail deliberately does not raise NOW, because every home in the scan shares it, so it cannot separate one door from the next — it belongs in the pitch, not the ranking. Roofbird also compares each roof against its immediate neighbours — the "everyone on this street went new except you" close. The full property record and an owner-equity estimate show free; only the DNC-scrubbed phone and email need a click. Where hail is on record, it shows roughly how long the owner has left to file a claim (estimate, verify with the carrier). See a live scored area without signing up, or read how Roofbird scores a roof from imagery.
Alternatively, build your own scorecard using:
- Year-built data: County appraisal district records (free)
- Income data: U.S. Census API or Zillow (free)
- Insurance data: state insurance commissioner bulletins + NOAA Storm Events
- Permit data: county building department records (free)
Plan for 30-60 min per zip to build the data manually, less if you script the queries.
What to do this week
- List 8-12 zips you've worked in over the last 12 months
- Score each one using the 4-variable framework (use equal weights for v1)
- Sort by total score
- Focus next month's prospecting on the top 3 zips
- After 30 days, compare actual close rates by zip against the predicted ranking
- Adjust the variable weights based on what you see in the data
The shops with the most efficient prospecting motions aren't the ones knocking everywhere. They're the ones knocking precisely in the right 3-5 zips, repeatedly, until those zips are saturated.
— Jake
FAQ
Q: How does Roofbird's block-level scoring differ from my manual zip analysis?
A: Manual zip analysis takes hours and still averages across an entire zip. Roofbird scores every block within your service area automatically — it reads roof wear from satellite and Street View, counts homes from building footprints, checks recent hail, and flags walkability. A block with 30% worn roofs and a hail event last spring gets a higher priority than a block with 15% worn roofs and no hail, even if they share the same zip. You get a ranked list of blocks to scan, not just a zip to guess at.
Q: What does it cost to score an area?
A: Nothing. Scanning new ground and ranking every roof in it is free at any size, and asking, searching, sorting and saving lists are free and unlimited. Credits are only spent on doing work: reading a roof properly, both photographs plus the property record, is 1 credit per 8 roofs; the owner's name, phone and email is 7/8 of a credit a roof, so a read plus the owner runs about 1 credit a house; opening a house completely is 1 credit; postcards are 3 credits a card for 4x6 or 6x9 and 4 for the big 6x11, with printing, First-Class postage, the address check and per-house tracking included. The trial is 10 credits, free, no card, no expiry, and after that you buy one-off packs — Starter $49 for 49 credits, Crew $99 for 125, Hunter $199 for 300, Pro $399 for 800. Credits never expire and nothing renews. What a credit buys is laid out in full.
New in Roofbird
Now with the homeowner's contact details on every lead
Finding the roof is half the job — you still have to reach the owner. Roofbird now unlocks the homeowner's name, phone, email, and mailing address on any lead, every phone DNC-scrubbed so you know who's safe to call, plus whether they're an owner-occupant or an absentee owner. No skip-tracing tools, no bought lists: find the roof, get the owner, call or mail the same day.
Written by
Jake Thompson
Roofbird
Have a question about anything in this post? Reach the Roofbird team at support@roofbird.ai.
Try Roofbird: 10 free credits in your area
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