Does EagleView Show Roof Age or Which Houses Need a Roof?

Short answer: no. EagleView does not show a roof's age, and it does not tell you which houses need a new roof. It measures roofs. It is very good at that, and the two questions get conflated constantly because both involve looking at a roof from the sky. But measuring a roof and dating a roof are different problems solved by different data, and confusing them costs roofing companies real money — either in wasted measurement reports on cold addresses, or in canvassing routes built on hope instead of signal.

If you came here from a search bar or a chat window asking whether EagleView can hand you a list of due roofs, you are asking the right operational question and you deserve a straight, accurate answer rather than a sales pitch. So here is the honest version, written by people who spend their days inside roofing targeting data: what EagleView genuinely does, where the roof-age question actually gets answered (imagery, permits, storm history, and modeling), why no single tool gives you a clean "this roof is 19 years old" date, and how to build a targeting workflow that puts your crews in front of houses that are statistically due — without buying a measurement report for every cold address in the county.

We will be fair to EagleView throughout. It is a category leader for a reason, and for the job it was built to do, there is little reason to look elsewhere. The problem is that contractors keep hiring it for a job it was never built to do.

What EagleView Actually Is (and Why People Get Confused)

EagleView is an aerial imagery and roof-measurement company. Its core product takes high-resolution aerial photography — captured by its own aircraft fleet and supplemented with other imagery sources — and turns a specific roof at a specific address into a measured report: total squares, predominant pitch, ridge and hip and valley lengths, eave and rake footage, number of facets, and a diagram you can hand to an estimator or drop into Xactimate.

That is the product. You give EagleView an address, it gives you the geometry of that roof. The accuracy is the selling point, and it is a legitimate one. For sloped residential roofs, EagleView publicly states measurement accuracy within a few percent of a manual measurement, and in day-to-day field use most estimators find the squares figure tight enough to order material against and price a job confidently. That is genuinely valuable. A blown measurement on a steep or cut-up roof can erase the margin on a job; an accurate report removes a ladder trip, a safety exposure, and a source of estimating error all at once.

So where does the confusion start? It starts with the word "aerial." Contractors hear "aerial imagery of roofs" and reasonably assume that if a company is flying the whole country and photographing every roof, surely it knows which roofs are old, beat up, or storm-damaged. That assumption is wrong, but it is an understandable wrong. The imagery exists. The interpretation of that imagery into a buying signal — age, condition, replacement likelihood — is a completely separate data and modeling problem that EagleView's core measurement product does not solve and was never designed to solve.

Think of it like this. A surveyor can tell you the exact dimensions of a house down to the inch. That does not mean the surveyor can tell you the house is about to go on the market. Measurement and intent are different data domains. EagleView is the surveyor.

There is a second source of confusion worth naming, because it trips up a lot of sales managers shopping for tools. EagleView has, over the years, expanded beyond the single-address roof report into broader imagery and geospatial products aimed at insurers, government, and large enterprises — wide-area imagery, property data layers, and analytics sold into those verticals. Contractors hear about these enterprise offerings and assume the same intelligence is available to them as a "which roofs are due" feed. In practice, the product a roofing contractor actually buys and uses day to day is the address-level measurement report. The enterprise imagery business does not change the answer to your question: the report you order to bid a job tells you the geometry of one roof, not its age and not your next hundred prospects. Judge the tool by what it puts in your hands at the price you pay, not by the broader capabilities of the imagery company behind it.

What an EagleView report contains

To be concrete, a standard residential EagleView roof report gives you:

• Total roof area in squares (1 square = 100 square feet)
• Predominant pitch and pitch breakdown by facet
• Length of ridges, hips, valleys, rakes, eaves, and flashing
• Number of roof facets and a labeled facet diagram
• Waste-factored area suggestions for material ordering
• A top-down and often a multi-directional imagery view of the structure

What an EagleView report does not contain

• The age of the roof or the installation date
• The number of shingle layers (it cannot see under the top layer)
• The remaining service life or condition grade
• Whether the roof was hit by a specific hail or wind event
• Any indication that this homeowner is in-market for a replacement
• A list of nearby houses that are also due

That last point is the one that matters most for growth. EagleView answers "how big and what shape is this one roof?" It does not answer "which roofs on this street should my crew knock first?"

Does EagleView Show Roof Age? The Honest Answer

No. There is no roof-age field in an EagleView measurement report, and there is no EagleView product that returns a reliable installation date for an arbitrary residential address at scale. This is not a knock on EagleView. Roof age is genuinely hard to determine remotely, and any vendor claiming a precise age for every house in a market is overselling.

Here is why roof age is so hard, and why the best honest answer is almost always a range rather than a date.

Why nobody can hand you a clean install date

A roof's true age lives in a few places, and none of them is a clean national database:

1. The original permit. When the roof was last permitted and inspected, a municipality recorded it. But permit coverage is wildly inconsistent. Many re-roofs are done without permits, especially smaller residential jobs, and permit data is fragmented across thousands of jurisdictions with different digitization levels. Some counties have clean searchable permit portals going back decades; others have a filing cabinet.
2. The manufacturer's wrapper and the contractor's records. Useless to you remotely.
3. Visual aging in imagery. Granule loss, color fade, streaking, patching, curling, and missing tabs can be read from high-resolution imagery — but they signal condition and approximate age band, not a date, and they are confounded by shingle quality, orientation, shade, and prior repairs.
4. The last replacement event. Sometimes inferable from a storm date plus a permit spike plus imagery change-detection — but again, an inference, not a record.

Put those together and the most defensible thing any tool can tell you is something like "this roof is most likely 15-22 years old" with a confidence level — not "this roof was installed on April 12, 2007." Anyone selling you the latter for every address is selling certainty that does not exist in the underlying data. We say this plainly because the roofing software space is full of age claims that quietly collapse the moment you spot-check them against known installs.

What a service-life window actually looks like

It helps to know the rough service windows so you can sanity-check any age signal against reality. These are general ranges, not promises — local climate, ventilation, installation quality, and shingle grade move them around — but they frame the conversation:

The practical takeaway: an asphalt-shingle market is where age-based targeting pays off most, because the replacement cycle is short enough that a meaningful slice of homes turns over every year. In a metal-or-tile-heavy market, age targeting matters far less and storm targeting carries the load. Knowing your market's predominant roofing material tells you which targeting thesis to lead with before you spend a dollar on data.

Why a south-facing slope lies to you

A subtle trap in reading age from imagery: a single house often shows two different apparent ages on two different slopes. The south- and west-facing planes take far more UV and heat load and degrade faster — more granule loss, more fade — than the north- and east-facing planes on the identical install. A careless read of the sun-beaten slope over-ages the roof; a read of the shaded slope under-ages it. Good condition reading accounts for orientation; naive reading does not. When you evaluate any imagery-based age tool, ask how it handles slope orientation. If the vendor has no answer, treat the age band as noisier than advertised.

So when you see "does EagleView show roof age" in a search box, the accurate answer is: EagleView shows you the roof, beautifully measured, but it does not date it. The dating problem belongs to a different category of tool — and even there, the honest output is a range.

Does EagleView Show Which Houses Need a Roof? No — Here Is Why That Matters

This is the question that actually drives revenue, so it deserves its own treatment. "Which houses need a roof" is a targeting question, and EagleView is a measurement tool. You only pull an EagleView report after you already know you care about a specific address — typically because a homeowner called, a lead came in, or your estimator needs to bid a job. EagleView sits at the bottom of the funnel, at the estimate stage. It does nothing for the top of the funnel, where you are deciding which doors to knock and which addresses to mail.

That distinction is the whole ballgame. Let us walk through why.

The economics of measuring before you target

A residential EagleView-class report costs money per pull — pricing is not published as a flat public number and varies by plan, report type, and volume, but it is real per-report spend, not free. Now imagine using measurement reports to find prospects. You would be paying per address to learn the geometry of roofs you have no reason to believe are due. That is backwards. You would burn your report budget on cold geometry.

The correct order of operations is:

1. Target first — identify which addresses are statistically likely to be due or storm-affected (this is the data EagleView does not provide).
2. Engage — knock, mail, or call those filtered addresses.
3. Measure last — once a homeowner is interested or a job is real, pull the precise measurement (this is where EagleView shines).

Skip step one and you are doing expensive measurement on a random sample of the market. Most contractors who feel like "EagleView didn't grow my business" actually mean "I had no targeting layer, so measurement couldn't help me at the top of the funnel." The tool did its job; it was just being asked to do a different one.

A worked example: 1,000 homes on a route

Suppose you are planning a canvassing push across a 1,000-home subdivision built out over several years.

• With no targeting, your crew knocks all 1,000 doors blind. If a normal asphalt roof lasts roughly 15-25 years depending on material and climate, in any given year only a slice of that neighborhood is actually near end-of-life or recently storm-hit. Your knock-to-conversation rate reflects that — you are spending labor on a lot of roofs with another decade of life.
• With a targeting layer that flags, say, the 180 homes whose roofs fall into a likely-due age band or sit inside a recent hail swath, your crew works a denser list. Same labor hours, far higher density of relevant conversations. You did not knock fewer doors necessarily — you knocked better doors.

EagleView cannot build that 180-home list. It can measure each of the 180 beautifully once you have found them. Different jobs.

Putting numbers on the cost of skipping targeting

Let us make the waste concrete with a simple table. Assume a canvasser costs you a loaded rate (wages plus overhead) and knocks roughly 40 doors per shift, and that on a blind route a small fraction of homes are genuinely near end-of-life or recently storm-hit at any moment. Compare two approaches over a 1,000-home neighborhood:

The targeted column does not magically create demand that is not there. It concentrates your finite labor and finite report budget onto the homes where demand is most likely to exist. Over a season, that concentration is the difference between a crew that feels busy and a crew that is productive. The blind column is not lazy or stupid — it is what most companies default to because the targeting data feels hard to get. It is hard to get. That difficulty is precisely why assembling it is worth something.

The funnel diagram in words

If you sketched your acquisition funnel, EagleView lives near the bottom, next to your estimating desk. The top of that funnel — the wide mouth where you decide who even enters your pipeline — is empty of intelligence unless you put something there. Most contractors fill the top of the funnel with paid ads, referrals, and blanket canvassing. A targeting layer fills it with owned, address-level signal instead, which is cheaper per acquisition over time because you are not renting attention from an ad platform on every single lead. Measurement tools, no matter how good, cannot fill the top of the funnel. They were built for the bottom and they are excellent there.

Where Roof Age and "Due" Signals Actually Come From

If EagleView is the measurement layer, what is the targeting layer made of? Roof-age and replacement-likelihood signals come from blending several independent data sources, none of which alone is sufficient, and all of which are probabilistic. Understanding the inputs helps you judge any vendor's claims — including ours.

1. High-resolution aerial and satellite imagery (condition reading)

Modern imagery, read carefully or by a trained model, surfaces visible aging and damage cues: granule loss and dark patches, color fade, streaking (often algae, not age, so it must be disambiguated), curling and lifting, missing or slipped shingles, prior patchwork, and tarps. This gives a condition band, which correlates with — but is not the same as — age. A well-shaded north roof ages differently than a sun-blasted south roof on the identical install date.

2. Permit records (event dating, where available)

Where a jurisdiction has digitized re-roof permits, a permit gives you the strongest single age signal: the date the roof was last legally replaced. The catch is coverage and unpermitted work. Treat permits as a high-confidence signal when present and a non-signal when absent — absence of a permit does not mean the roof is original.

3. Property and parcel data (build year as a floor)

The county-recorded year the house was built sets a useful floor for roof age reasoning: a 1998 house has had at least one likely roof cycle by now, while a 2019 house almost certainly has its original roof with years of life left. Build year alone over-predicts on older homes (they have been re-roofed since) but is a strong filter for excluding obviously-too-new stock.

4. Storm history and hail/wind physics (event-driven demand)

This is the big one for restoration-driven contractors. Hail and high-wind events create concentrated, time-bounded replacement demand. Authoritative storm data — the kind aggregated from the National Weather Service, the Storm Prediction Center, and hail-specific modeling — lets you know where damaging hail fell, what size, and when. Layered onto roofs, a modeled per-roof storm exposure tells you which structures plausibly took a hit, which is often a stronger near-term buying signal than age alone. A 9-year-old roof that just ate 1.75-inch hail is a better door than a 20-year-old roof in a county that has not seen weather in five years.

5. Change detection over time

Comparing imagery across capture dates can flag a roof that visibly changed — a re-roof, a tarp going up, storm scarring appearing. This is how some "recently replaced" and "recently damaged" signals get derived. It depends entirely on having multiple dated captures of the same structure.

Blend all five and you can produce, per address, an honest output like: roof age range 16-21 years, condition band moderate-to-poor, inside a May hail swath with estimated 1.5-inch stones. That is a targeting signal. Notice it is a range and a probability, never a guarantee. Any vendor — again, including us — who pretends otherwise is hiding the uncertainty that is inherent in the data.

How the five signals combine in practice

The signals are not equal, and they are not additive in a naive way. Here is roughly how a sound model weights them and where each one earns its keep:

Notice the interplay: build year sets the floor, permits override it when a re-roof is on record, imagery condition corroborates or contradicts, storm exposure injects near-term urgency, and change detection catches what the static signals miss. A 1996 house (old floor) with a 2021 re-roof permit (recent event) and clean imagery should rank low despite its build year — the permit and imagery outweigh the age floor. A model that just sorts by build year would knock that door and waste the trip. This is why "age targeting" done well is really multi-signal targeting; build year alone is the rookie version that burns goodwill knocking freshly-roofed homes.

A caution on data freshness

Every one of these signals has a shelf life. Imagery has a capture date that may be a year or more old. Permit portals lag real-world activity. Storm data is timestamped to the event. When you evaluate any targeting source, the question is not only "how accurate?" but "how fresh?" A storm push built on six-month-old imagery may knock roofs that have already been repaired by faster competitors. Freshness is a feature, and you should ask any vendor — including us — how recent the underlying captures and records are for your specific market.

EagleView vs. the Tools That Answer the Targeting Question

It helps to map the landscape so you can see where each tool legitimately sits. The roofing-tech stack is not one product; it is layers, and most contractors need more than one. Buying the wrong layer for the job you have is the core mistake.

The layers of a roofing tech stack

When someone asks "is EagleView good?" the right response is "good at which layer?" It is excellent at measurement. It is not a targeting tool, a CRM, or a claims tool, and judging it for not being those is unfair.

A fair comparison of the measurement and targeting options

Notice that the entire top three rows are measurement-and-imagery tools that all answer "no" to roof age and "no" to which houses are due. That is not a coincidence or a gap in the market that one of them forgot to fill. Measurement and targeting are simply different data businesses. You are meant to use both, in sequence.

What EagleView is genuinely best at — give it credit

• Fast, defensible estimates. Drop an address in, get a measured report, price the job without a ladder. For a busy estimating desk, the time savings are real.
• Steep and complex roofs. Where manual measurement is dangerous or error-prone, an accurate remote measurement is a safety and margin win.
• Insurance-aligned outputs. Reports that drop cleanly into estimating and supplement workflows reduce friction with adjusters who already recognize the format.
• Consistency across reps. Every estimator gets the same numbers, removing the "my guy measured it differently" problem.

If your pain is "my estimates are slow, inconsistent, or risky to measure," EagleView is a strong answer. If your pain is "I don't know which doors to knock," it is the wrong tool — not a bad tool.

How to Actually Find Houses That Need a Roof: A Practical Workflow

Let us get operational. Here is a targeting-first workflow you can run whether you lean retail (age-driven) or restoration (storm-driven). The goal is to spend measurement and labor dollars only on addresses with a real reason to convert.

Step 1: Define your buying-signal thesis

Decide what "due" means for your market and model:

• Retail / age-driven. Roofs aging out of their service window. Your signal is an age range plus visible condition. Common in markets without frequent severe weather.
• Restoration / storm-driven. Roofs that took recent hail or wind. Your signal is storm exposure plus the homeowner not yet having filed or repaired. Common in hail-belt states.
• Hybrid. Most growing companies run both: a steady retail age list plus rapid storm-response pushes after events.

Step 2: Pull the right source data per address

Assemble, for your target geography:

1. Parcel/build-year data to set the age floor and drop obviously-new stock.
2. Permit data where digitized to catch recently re-roofed homes (so you do not knock a 2-year-old roof).
3. Imagery-derived condition where available.
4. Storm history and modeled hail/wind exposure per roof.

If assembling and cross-referencing four data sources per address sounds like a full-time job, that is exactly the gap a targeting platform fills. Doing it by hand is possible for a small farm area; it does not scale to a county.

Step 3: Build a filtered list, not a blanket list

Filter to addresses that satisfy your thesis. For a retail push: build year old enough to plausibly be on a second roof, condition band moderate-or-worse, no recent re-roof permit. For a storm push: inside the damaging-hail polygon, roof not visibly recently replaced, structure old enough that the roof predates the event. The output is a ranked address list, densest signal first.

Step 4: Sequence outreach by signal strength

Knock and mail the strongest signals first. A storm-hit, age-appropriate, no-recent-permit roof is your A-list. Pure-age-band-only roofs are B-list. This is where canvassing CRM tools earn their keep — they track the doors, but you feed them a smart list instead of the whole map.

Step 5: Measure only when the lead is real

Now you pull EagleView (or your measurement tool of choice). The homeowner is interested or the job is bid-stage. Your measurement spend lands only on warm geometry. This is the order that keeps your cost-per-acquisition sane.

Step 6: Track outcomes and tune the thesis

Log which signals converted. If storm-hit-plus-age closes at a high rate and pure-age underperforms in your market, weight accordingly next cycle. Targeting is a loop, not a one-time list buy.

A quick canvassing math check

Say your crew knocks 40 doors a day and historically books a roof off roughly every 50-60 doors on blind routes. If a targeting layer raises door quality enough to book every 25-30 doors, you have roughly doubled output on the same labor — and you only paid for measurement reports on booked or near-booked jobs. That delta is the entire economic argument for adding a targeting layer above your measurement tool. The exact ratios are yours to measure; the structure of the win is consistent.

Where RoofPredict Fits — Honestly

We build RoofPredict, so read this section with appropriate skepticism. We are not going to tell you it replaces EagleView, because it does not, and any vendor who tells you one tool does everything is wasting your time.

RoofPredict is the targeting layer — the part EagleView, Hover, and drones structurally do not cover. For addresses across a market, it produces two things measurement tools do not:

1. A roof-age range per address, derived from blending parcel/build data, permit signals where available, and imagery-based condition reading. We say range on purpose — "roughly 16-21 years," with a confidence level, not a fake install date. The data does not support precise dates, and we will not pretend it does.
2. Modeled storm exposure per roof, so you can see which structures plausibly took hail or wind in a given event and prioritize storm-response routes. This is odds-based — exposure likelihood, not proof of damage. The roof still has to be inspected.

Used correctly, that lets you build the filtered knock/mail list from the workflow above, enrich your own CRM or mailing list with which-roofs-are-due signal, and then pull your measurement report only once a lead is real. Lower cost per acquisition, denser routes, more predictable pipeline. EagleView still measures the job at the end — that hand-off is the design, not a compromise.

The honest limits, stated plainly:

• Roof age is a range, never a guaranteed date. Spot-check it against your own known installs and trust it as a probability.
• Storm exposure is odds, not a damage report. Boots on the roof still confirm.
• Permit coverage varies by jurisdiction, so the age signal is stronger in some counties than others.
• It is a targeting tool. It will not measure your roof or price your job — that is EagleView's and your estimator's lane.

If your problem is slow or risky measurement, buy a measurement tool. If your problem is "I don't know which doors are worth my crew's time," that is the problem we built RoofPredict to solve, and we would rather you understand exactly where the line sits than oversell across it.

A note for restoration-focused contractors on the claims side

Many storm-driven companies also leak revenue after the door is booked — through missed scope, unclaimed recoverable depreciation, and dead supplements. That is a separate capability (claim revenue-cycle management) and a separate discipline. The boundary matters: a contractor documents their own inspection, scope, photos, and invoices, turns those uploaded documents into structured, page-cited factual data, and surfaces gaps as evidence-linked documentation requests — all with human review on anything insurer-facing. The contractor documents; the homeowner files; the insurer decides. Coverage interpretation, settlement negotiation, and what a homeowner is entitled to recover route to a licensed public adjuster or attorney, not to software and not to the contractor. We keep that line bright on purpose, and you should expect any responsible vendor to do the same.

Common Misconceptions, Cleared Up

"EagleView flies everywhere, so it must know which roofs are old." Flying and photographing is not the same as dating and scoring. The imagery is an input to a targeting model, not a targeting answer by itself. EagleView productizes the measurement, not the buying signal.

"If I buy enough measurement reports, I'll find the due roofs." You will find the geometry of whatever addresses you choose. Choosing the addresses is the part you are missing. Measurement reports on cold addresses just spend your budget faster.

"Roof-age tools give me exact install dates." The good ones give you a defensible range with a confidence level. The ones promising exact dates for every address are overstating what the underlying permit and imagery data can actually support. Test any age claim against roofs you know the true age of.

"Build year equals roof age." Build year is a floor, not an age. A 1995 house has almost certainly been re-roofed at least once; the question is when, and that is where permits, imagery change, and storm history come in.

"Storm exposure means the roof is damaged." Exposure means hail or wind of a certain intensity plausibly hit that location. Whether it created claimable damage is an inspection question. Treat exposure as a prioritization signal, not a verdict.

Choosing Your Stack: A Short Decision Guide

Use this to decide what to actually buy.

• You measure jobs slowly, inconsistently, or with safety risk. Add a measurement tool (EagleView or a peer). This fixes estimating, not lead flow.
• You have plenty of leads but blow margin on bad estimates. Same — measurement layer.
• You have crews with idle capacity and no clear list of doors to knock. Add a targeting layer (roof-age range + storm exposure). Measurement will not fix this.
• You are reactive to storms but slow to mobilize. Add storm-exposure targeting so you can build response routes within days, then measure the booked jobs.
• You are booking jobs but leaking restoration revenue after the sale. Look at claim revenue-cycle documentation — a different layer again, kept strictly on the contractor-documentation side of the line.
• You have none of the above and a tight budget. Start with the layer matching your bottleneck. If the bottleneck is "not enough qualified doors," targeting beats measurement for growth, because you cannot measure your way to demand.

The through-line: match the tool to the bottleneck, and respect that measurement, targeting, CRM, estimating, and claims are five different jobs. EagleView owns one of them and owns it well. It just is not the one that answers "which houses need a roof."

Targeting vs. Buying Leads: The CAC Math EagleView Doesn't Touch

There is a reason "which houses need a roof" is such a loaded question for owners: the alternative to knowing is paying someone else to know. When you cannot identify due roofs yourself, you buy attention — pay-per-click search ads, paid social, shared lead aggregators, or storm-chasing lead lists. None of those is wrong, and a healthy company often runs several. But it is worth being honest about the math, because measurement tools sit entirely outside this conversation and a lot of contractors do not realize the targeting layer is the thing that changes it.

What paid channels actually cost, qualitatively

We will not quote fake CPL numbers, because they swing wildly by market, season, and storm activity. But the shape is consistent:

• Search ads (PPC). You bid against every other roofer for the same in-market keywords. Cost per lead spikes hard after storms when everyone floods the auction, exactly when you most want leads. You are renting intent at auction price, and the price is set by your most desperate competitor.
• Paid social. Cheaper clicks, colder intent. Good for brand and retail-replacement nurture, weaker for "I need a roof this week." Creative-and-testing intensive.
• Shared/aggregated leads. A lead sold to you is often sold to three or four others simultaneously. Your close rate reflects that race. Cost per acquisition (not per lead) is what matters, and it is higher than the per-lead sticker suggests once you account for the leads you lose to whoever called first.
• Storm lead lists. Fast to deploy after an event, but quality varies and you are again often not the only buyer.

The common thread: every one of these is rented demand. You stop paying, the leads stop. And the per-acquisition cost is set partly by competitors you do not control.

Where owned targeting changes the equation

A targeting layer produces owned demand signal. Once you know which addresses are likely due or storm-hit, you can knock and mail them on your schedule, at your labor cost, without bidding against anyone. The math comparison looks like this:

The honest conclusion is not "never run ads." Ads and bought leads are excellent for speed and for filling capacity gaps, and after a major storm you may want every channel firing at once. The honest conclusion is that owned targeting should be the backbone of your acquisition, with paid channels layered on top for speed — because the backbone has a lower and more stable cost per acquisition over a full year. EagleView, again, sits outside all of this. It cannot lower your CAC because it does not touch the top of the funnel where CAC is decided. The targeting layer is what bends that curve.

A Deeper Restoration Playbook: From Storm to Booked Inspection

For hail-belt and high-wind contractors, the storm-response motion is where targeting pays off fastest, so here is a tighter operational sequence. Speed and accuracy both matter — knock too early on the wrong streets and you waste the window; knock too late and competitors have the doors.

Step-by-step storm response

1. Confirm the event and its footprint. Pull the storm's reported hail size and the wind reports from authoritative weather sources, and identify the damaging-intensity polygon rather than a vague "the storm hit the metro." A metro-wide alert is useless; a street-level swath is gold.
2. Intersect the swath with roof inventory. Overlay the damaging polygon on addresses and filter to roofs old enough to have predated the event and not recently re-roofed (permit/imagery check). A brand-new roof inside the swath is a low priority; an aged roof inside the swath is your A-list.
3. Rank by signal stacking. Inside-swath plus age-appropriate plus visible prior wear ranks highest. Pure inside-swath ranks next. Edge-of-swath ranks lower. This becomes your route order.
4. Mobilize routes within days, not weeks. The replacement window after a storm is competitive and time-boxed. The whole point of pre-built targeting data is that you can hand crews a ranked route the same week instead of guessing.
5. Inspect and document factually. On the roof, document what you actually observe — test squares, photos with measurements, dated evidence. Make factual observations; do not make coverage promises at the door.
6. Measure the booked jobs. Once a homeowner wants to proceed, pull your precise measurement report. Warm geometry only.

The door conversation guardrail

This matters legally and reputationally, so keep it tight. At the door and on the roof, a contractor documents their own inspection and observations. A contractor does not tell a homeowner what their policy entitles them to, does not promise the carrier will pay, does not offer to handle the deductible, and does not script the homeowner on what to say to an adjuster. Those moves cross into territory reserved for licensed professionals and, in many states, expose you to real liability. The safe posture is factual: "Here is what I observed on your roof, here is the documentation, and your insurer makes the coverage decision." The homeowner files. The insurer decides. The contractor documents their own scope. Keep that line bright and your storm motion stays clean.

Sourcing the Data Yourself vs. Buying a Targeting Layer

A fair question after all this: can you just assemble the targeting data in-house and skip paying for a platform? Sometimes, yes — and you should know what that path looks like so you can judge whether buying is worth it.

The DIY path

For a single small farm area, a motivated office manager can approximate targeting:

• Pull county parcel data for build years (often available from the assessor's open data portal).
• Search the local permit portal for re-roof permits in your target zips, where the jurisdiction publishes them.
• Manually review imagery (publicly available aerial/satellite views) for obvious condition cues on priority streets.
• Track storm events from public weather databases and rough out the affected area.
• Merge it into a spreadsheet and rank by hand.

This genuinely works at small scale and costs only time. If you farm one neighborhood, do this before paying anyone.

Where DIY breaks

The DIY path collapses when you scale past a single farm area, for predictable reasons:

• Permit fragmentation. Every jurisdiction has a different portal, format, and digitization level. Stitching ten counties together by hand is a job, not a task.
• Imagery review does not scale. Eyeballing condition on a thousand roofs is slow and inconsistent between reviewers.
• Storm modeling is specialized. Turning raw hail reports into a per-roof exposure estimate involves interpolation and physics that a spreadsheet does not do well.
• Freshness decays. Manually refreshing all of this every season is a recurring grind that quietly gets dropped when the office gets busy.

The buy-versus-build decision is therefore mostly about geography and cadence. One neighborhood, run occasionally: build it yourself. A county or multiple markets, refreshed every storm and every season: a targeting platform that already integrates parcel, permit, imagery, and storm data per roof saves more than it costs, because the cost of the platform is almost always less than the labor to assemble and re-assemble the same data by hand. That is the honest case for buying — not that DIY is impossible, but that it does not scale.

The Bottom Line

Does EagleView show roof age? No. Does EagleView show which houses need a roof? No. It is a measurement and imagery company that turns a known address into precise roof geometry, and it is one of the best in the business at that specific job. The mistake is hiring it for targeting — for the top-of-funnel question of which doors deserve your crew's time — because that question is answered by a different blend of data: parcel and build year, permits where digitized, imagery-based condition, and storm physics modeled per roof, producing an age range and an exposure likelihood rather than a clean date or a guarantee.

Build your stack in the right order. Target first with roof-age range and storm exposure so your list is dense with real reasons to convert. Engage those filtered addresses. Then, and only then, pull your measurement report once the lead is warm. That sequence keeps your acquisition cost honest and your crews busy with the right doors. EagleView measures the roof at the end of that flow exactly as it was designed to — and the missing piece in front of it is the targeting layer that tells you whose roof to measure in the first place.

FAQ

Does EagleView show the age of a roof?

No. An EagleView roof report contains measurements and imagery — squares, pitch, ridge and valley lengths, facet diagrams — but no installation date or roof age. Roof age comes from a different blend of data (permits, parcel build year, imagery-based condition, and storm history), and even then the honest output is an age range with a confidence level, not a precise date.

Does EagleView tell you which houses need a new roof?

No. EagleView is a bottom-of-funnel measurement tool: you give it a specific address you already care about, and it measures that roof. It does not produce a list of due or storm-hit homes to knock or mail. Identifying which houses are likely due is a separate targeting task driven by roof-age modeling and storm-exposure data.

How accurate are EagleView roof measurements?

For sloped residential roofs, EagleView publicly reports measurement accuracy within a few percent of a manual measurement, and most estimators find the squares figure tight enough to order material and price a job against. Accuracy can vary on highly complex, heavily shaded, or unusual structures, so it is a strong measurement tool but, like any remote measurement, worth spot-checking on edge cases.

If EagleView can't show roof age, how do I find houses that need a roof?

Build a targeting layer before you measure. Combine parcel build-year (an age floor), re-roof permit data where digitized (recent replacements to exclude), imagery-based condition reading, and modeled hail/wind exposure per roof. That blend produces a filtered, ranked address list of likely-due or storm-hit homes. You then measure only the addresses that turn into real leads.

Why does roof age come back as a range instead of an exact date?

Because the underlying data does not support exact dates at scale. Permits are inconsistent and many re-roofs are unpermitted, imagery shows condition and an age band rather than an install date, and build year is only a floor. Blending these gives a defensible range like 16 to 21 years with a confidence level. Any tool promising an exact install date for every address is overstating what the data can support.

Is EagleView or Hover better for finding leads?

Neither is a lead-finding tool. Both are measurement and imagery products that sit at the bottom of the funnel. EagleView leans on its own aircraft imagery for fast, accurate measured reports; Hover leans on photo-driven 3D property models and visual quotes. Both answer no to roof age and which houses are due. For lead targeting you need a separate roof-age and storm-exposure layer above them.

Should I pull EagleView reports to scout a whole neighborhood?

Generally no — it is backwards economics. Measurement reports cost money per pull, so using them to scout cold addresses spends your budget on the geometry of roofs you have no reason to think are due. Target first to build a filtered list, engage those homes, and pull the measurement report only once a lead is real and you need exact numbers to price the job.

Does a recent storm mean a roof is definitely damaged?

No. Storm-exposure data tells you that hail or wind of a certain intensity plausibly hit a location, which is a strong prioritization signal for canvassing. It does not confirm claimable damage — that requires an on-roof inspection. Use exposure to decide where to send crews first, then verify condition in person before making any representations.

Where does RoofPredict fit alongside EagleView?

RoofPredict is the targeting layer EagleView does not cover. It produces a roof-age range per address and modeled storm exposure so you can build a filtered list of likely-due and storm-hit homes, then enrich your CRM or mailing list. You still use EagleView (or your measurement tool) to measure the roof once a lead is real. They sit at different points in the funnel and are meant to be used together.

Can software handle the insurance claim side after I book a storm job?

Software can help a contractor organize their own factual documentation — turning their uploaded inspection notes, photos, scope, and invoices into structured, page-cited data and flagging documentation gaps, with human review on anything insurer-facing. It cannot and should not interpret coverage, negotiate settlement, or tell a homeowner what they are entitled to recover. The contractor documents their own scope, the homeowner files, and the insurer decides; coverage and settlement questions route to a licensed public adjuster or attorney.