EagleView vs. Roof Targeting Software: Which One Actually Finds You Roofing Jobs

Type "EagleView vs roof targeting software for finding leads" into a search bar and you get a pile of pages that quietly assume the two things compete. They don't. EagleView and the newer wave of roof-targeting tools sit on opposite ends of your sales process, and the contractors who confuse them end up paying for the wrong thing at the wrong time.

Here's the short version, then we'll spend the rest of the page proving it with real workflows, real math, and the edge cases nobody mentions in a demo.

EagleView is a measurement company. You point it at an address you already care about, and it hands you a precise report of the roof's geometry: squares, pitch, facets, ridge and hip lengths, penetrations. It is one of the most useful tools ever built for quoting and ordering material on a roof you've already won. What it does not do is tell you which address to point it at. It assumes you already have the lead.

Roof-targeting software answers the question that comes before the measurement: out of the 3,000 houses in this part of town, which ones are old enough or storm-worn enough to actually need a roof soon? It ranks doors. It tells your canvasser where to walk and your mail house which list to print. It is a top-of-funnel tool.

So the honest framing isn't "EagleView vs. targeting software." It's "measurement vs. targeting" — two different jobs that most growing roofing companies eventually need both of. The mistake is buying a measurement tool and expecting it to fill your pipeline, or buying a targeting tool and expecting it to spit out a stamped estimate. Let's break down exactly where each one earns its keep, where the overlap is starting to blur, and how to spend your software dollars in the right order.

The two jobs hiding behind one search query

Every roofing sale moves through the same rough stages, whether you knock doors, mail, or live off referrals:

1. Find — figure out which homes are candidates worth your time.
2. Reach — get in front of those homeowners (knock, mail, call, ad).
3. Inspect & document — get on or near the roof, capture condition.
4. Measure & quote — pull exact geometry, price the job.
5. Close & build — sign, order material, schedule the crew.

EagleView lives squarely at stage 4, and increasingly stage 3 with its imagery products. Roof-targeting software lives at stage 1, and bleeds into stage 2 by feeding your mail and canvass routes. They never actually touch the same step. When a salesperson tells you their tool "finds leads," the only honest question to ask is: which stage are you talking about?

A measurement report can't find you a lead any more than a tape measure can. A targeting list can't quote a job any more than a phone book can. Both statements sound obvious written down, yet contractors burn real money every quarter buying the wrong one because the marketing language overlaps.

Why the categories get blurred on purpose

Three reasons the line gets muddy:

• Both use aerial imagery. EagleView, the targeting tools, and a half-dozen measurement competitors all start from overhead pictures of a roof. Same raw input, completely different output. One outputs dimensions; the other outputs priority.
• "Leads" is the magic word in this trade. Every vendor knows the buyer's deepest want is more jobs, so every vendor's homepage finds a way to imply they deliver leads. A measurement vendor will say their imagery "helps you win more business." Technically true. Practically irrelevant to filling your week.
• Storm season collapses the funnel. After a hail event, contractors want everything at once — who got hit, where to knock, what to document, how big the roof is. A tool that helps with any one of those gets remembered as "the lead tool," even if it only did measurement.

Keep the five stages in your head and the marketing fog clears fast.

What EagleView actually is (and is genuinely great at)

EagleView's core product is a report you order for a specific address. Their aircraft and imagery capture the roof, their software builds a 3D model, and you get a PDF and data file with the measurements a roofer or estimator needs. The standard outputs:

• Total squares (roof area in 100-sq-ft units) and per-facet areas
• Predominant pitch and pitch per facet
• Ridge, hip, valley, rake, and eave lengths in linear feet
• Facet count and diagram for cut-up and waste planning
• Penetrations like vents and chimneys, depending on the product tier

Why pros love it:

• You don't get on the roof to quote. That's a real safety and time win. Fall hazards are the leading cause of death in construction, and OSHA's fall-protection rules exist precisely because measuring a steep or storm-loosened roof by hand is dangerous. Pulling geometry from imagery keeps a body off a questionable deck.
• Bids get faster and more consistent. A measurement report turns a 45-minute climb-and-sketch into a few minutes of ordering. Material orders tie directly to the squares and linear-foot numbers, so over-ordering and the dreaded second supply run shrink.
• It's defensible. When a homeowner or an adjuster questions your numbers, a third-party measurement report is a credible document. That credibility matters in storm work especially, where the contractor documents conditions and the insurer decides coverage.

Where it stops, honestly:

• It assumes you have the address. Nothing in an EagleView report tells you whether that homeowner needs a roof, can afford one, or has any reason to talk to you. You bring the lead; it measures the lead.
• It says nothing about roof age or remaining life. Geometry is geometry. A pristine two-year-old roof and a curling twenty-two-year-old roof of the same shape produce nearly identical measurement reports.
• Per-report cost adds up if you measure the wrong houses. Because you pay per address, every report you pull on a homeowner who was never going to buy is pure waste. Measurement tools reward you for already having a qualified target — and punish you for guessing.

That last point is the hinge of the whole comparison. EagleView's economics assume your targeting is already solved. If it isn't, you're paying premium measurement prices to confirm geometry on roofs that didn't need you.

What roof-targeting software actually is

Roof-targeting software starts from the opposite end. Instead of "measure this one roof I picked," it asks "which roofs in this whole area should I pick?" It scans an area — a subdivision, a ZIP, a hail swath — and scores or ranks the homes by how likely they are to need roofing work soon.

The useful ones lean on two signals, sometimes separately, sometimes fused:

1. Roof age / remaining life. Estimated from aerial and street-level imagery — the look of the shingles, granule loss, streaking, patches, prior repairs. Good tools express this as a range (say, 18–22 years), never a fake exact date, because you cannot read an install certificate from the sky.
2. Storm exposure per roof. Not a flat "did it hail in this ZIP," but how a given storm's hail and wind actually loaded that roof — direction, estimated stone size, slope exposure. The difference between a hail map and per-roof modeling is the difference between "it rained somewhere in the county" and "your gutter is full of water."

The output isn't a measurement. It's a prioritized list of addresses plus the reason each one made the list. You hand that list to a canvasser, a mail house, or a CRM campaign.

Why this is a different economic engine

Measurement software saves you time on jobs you already have. Targeting software changes which jobs you go after at all. That's a top-of-funnel lever, and it compounds differently:

• Better targeting means fewer doors knocked per signed job, which means lower payroll and gas per deal.
• Better targeting means a smaller, cleaner mail list, which means more jobs per thousand pieces mailed.
• Better targeting means a green canvasser knocks doors that actually convert, makes money sooner, and quits less often, and rep churn is one of the most expensive hidden costs in residential roofing.

None of those benefits show up in a measurement report, because measurement was never the problem targeting solves.

Side-by-side: measurement vs. targeting

Read that table top to bottom and the "versus" dissolves. There's almost no row where they're doing the same thing. The only real competition between them is for the line item in your budget — and that's a sequencing question, not a head-to-head.

The math: where each tool saves or makes you money

Let's put numbers on it. These are illustrative figures you should replace with your own; the point is the shape of the math, not the exact dollars.

Scenario A: a measurement tool with no targeting

Say you run door-to-door and you measure every interested homeowner with a per-report measurement product.

• Reps knock 100 doors a day.
• Without good targeting, a chunk of the street has roofs under 8 years old — nowhere near needing replacement. Suppose 40% of the homes are simply too new to be real candidates.
• Of the 60 viable-age homes, you book maybe 6 inspections.
• You pull measurement reports on the ones that get to a quote.

The measurement tool did its job perfectly on those quotes. But you spent the entire day's payroll and gas working a street that was 40% dead weight, because nothing told your rep which houses to skip. The measurement report can't fix a targeting problem; it shows up too late in the funnel.

Scenario B: targeting first, then measurement

Now flip the order. You scan the area first and pull only the homes whose roof age range and storm exposure flag them as candidates. Your rep walks a route where, say, 70–80% of the doors are genuinely viable instead of 60%.

• Same 100 doors of effort, but now far fewer are dead-on-arrival new roofs.
• More conversations land because the rep is talking to people whose roofs are actually worn.
• You still pull a precise measurement report at the quote stage — targeting never replaced that.

The two tools didn't compete. Targeting raised the quality of every door before measurement ever entered the picture, and measurement still did the precise work at the end. Same crew, more signed jobs, and you only paid for measurement reports on houses that were real candidates.

The hidden cost most owners miss: wasted measurement spend

Here's the trap. Because measurement reports cost money per address, bad targeting makes your measurement tool more expensive too. Every report you pull on a homeowner who was never going to buy — because their roof was fine, or they're not in the market — is wasted spend on top of the wasted knock or mail piece. Good targeting protects your measurement budget by making sure most of the addresses you measure were worth measuring.

That's the relationship in one sentence: targeting decides which roofs deserve a measurement; measurement prices the roofs targeting qualified.

Why Zillow, the county, and a hail map don't count as targeting

Before we go further, let's kill three common substitutes, because a lot of contractors think they're already doing "targeting" when they're really just guessing with worse data.

"Year built" is not roof age

Pull up any house on a property site and you'll see a year-built field. Contractors use it as a proxy for roof age constantly. It's a bad proxy. A house built in 1994 might be on its third roof; a house built in 2015 might still be on its original builder-grade shingles that are already failing. Re-roofs are invisible to county records and listing sites — nobody updates the tax roll when they swap shingles. Year built tells you the age of the house, which is correlated with, but routinely contradicted by, the age of the roof. Targeting from year built means knocking a lot of doors on homes that were re-roofed five years ago.

A hail map is weather, not per-roof exposure

After a storm, the free hail-swath maps tell you where hail was reported across a region. Useful for knowing a county got hit. Nearly useless for deciding which specific houses to knock, because a swath polygon covers thousands of roofs that experienced very different loading. Hail size, the angle a roof faces, slope, and the direction the storm tracked all change whether a given roof actually took damage. A map shows where it hailed. It does not show which roofs it wore out. Two houses on the same street, same swath, can have completely different damage because one's steep slope faced the incoming stones and the other didn't.

A purchased list is demographics, not roof condition

List brokers sell you homeowners filtered by income, home value, and age of the home. None of that is roof condition. You can buy a tidy list of "homeowners in 3 ZIPs with home value over X" and still be knocking brand-new roofs and skipping the twenty-year-old roof two doors down because it happened to be a slightly cheaper house. The list is sorted by the wrong variable.

Real targeting sorts by the variable that matters: is this specific roof worn out or storm-worn enough to need replacing soon? Age range plus per-roof storm exposure. Everything else is a proxy that quietly leads your crew to the wrong doors.

How roof age gets estimated from imagery (and its honest limits)

Since roof age is the backbone of targeting, you should understand how it's derived — and where it's soft — so you can trust it appropriately.

From aerial and street-level imagery, a few visible signals correlate with roof age and wear:

• Granule loss and color fade. Asphalt shingles shed granules as they age; bald, shiny, or blotchy areas read as wear.
• Streaking and biological growth. Dark streaks (often algae) and moss accumulate over years and read differently than a fresh roof.
• Curling, cupping, and lifted tabs. Visible deformation at the shingle edges is a late-life signal.
• Patches and mismatched sections. Prior repairs hint at a roof that's been limping along.
• Surface texture and sheen. New shingles reflect light differently than weathered ones.

Good targeting fuses those signals into an age range, not a single date. This is the honesty line that separates a credible tool from a snake-oil one: nobody can read the installation invoice from a satellite. If a vendor claims they'll tell you a roof is "exactly 19 years old," be skeptical. A range like "18–22 years" is the honest, useful output. It's tight enough to sort a street and honest enough not to embarrass you on a doorstep.

What imagery can't see, and where a human still wins:

• Decking and underlayment condition below the shingles.
• Ventilation and moisture problems that don't show from above.
• Recent unpermitted repairs the imagery is too old to show (image freshness varies).
• Material quality — a cheap 3-tab and a premium architectural shingle of the same age weather differently, and overhead imagery only partly distinguishes them.

So targeting gets you to the right doors. It does not replace the inspection. Treat the age range as a prioritization signal that gets a qualified rep to a worn roof faster — not as a verdict.

Modeling the storm on each roof, not the whole ZIP

The second targeting signal — storm exposure — is where the gap between "a map" and "real targeting" is widest, and it's worth slowing down on because storm work is where a lot of roofing money is made and lost.

A hail map answers "where did it hail?" Per-roof storm modeling answers a sharper question: "given how this specific storm moved, how hard did this roof actually get loaded?" That requires accounting for:

• Estimated hail size through the area, beyond a plain yes/no on hail.
• Storm track and direction, which determines which roof slopes faced the incoming stones.
• Slope and orientation of the individual roof, since a face angled into the storm takes more impact energy than one in the lee.
• Wind exposure, since wind damage and hail damage are different failure modes and a roof can have one without the other.

The practical payoff: on a single hail-affected street, per-roof modeling can tell you that the houses on the windward side took real loading while the ones tucked behind them likely didn't. A hail map paints the whole street one color. Per-roof modeling sorts it. That sorting is exactly what lets a storm crew work the roofs the storm actually broke instead of the whole ZIP.

A hard guardrail here, because it's where contractors get themselves in trouble: storm modeling is odds, not proof. A model that says a roof was likely loaded by 1.5-inch hail from the northwest is a strong reason to go inspect and document. It is not evidence of damage, and it is never something to wave at a homeowner or anyone else as proof a roof is covered. The roofer documents the conditions and the estimate; the insurer decides coverage; the homeowner owns the claim. Targeting tells you where to look. Your inspection and the carrier's process do the rest. Confuse "likely hit" with "definitely damaged and covered" and you'll burn trust fast.

Where RoofPredict fits in this comparison

If you've read this far, the category map is clear, so here's where our tool sits, plainly and with its limits.

RoofPredict is a targeting tool, not a measurement tool. It does the stage-1 job: scan an area and tell you, house by house, which roofs are actually due. It does that by fusing the two signals above — an estimated roof-age range per address from imagery, and storm exposure modeled per roof (hail and wind loading on that specific roof, beyond the swath the ZIP sat under). The output is a ranked list of doors with the reason each one made the cut, so your crew knocks and your mail house prints the houses that are worn out and skips the ones that aren't.

It's deliberately not trying to be EagleView. We don't hand you squares, pitch, or linear feet, and we won't replace the measurement report you pull at the quote stage. We don't get on the roof for you, and we don't replace the inspection — the age figure is a range, the storm figure is odds, and both are prioritization signals, not verdicts. We don't handle, file, or negotiate insurance claims; we hand you a starting point and the documentation context, and the carrier and homeowner do what only they can do.

What it changes is the order of your funnel. Instead of measuring whatever doors you happened to knock, you scan first, work the right houses, and then pull your measurement report on the ones that earned it. The two tools stack: RoofPredict decides which roofs deserve a measurement; your measurement tool prices the ones it qualified. If the only thing you take from all of this is the sequence — target, then measure — you've already got the most expensive lesson in the trade for free.

Honest limits, said out loud: imagery freshness varies, so a very recent re-roof can occasionally read older than it is; age ranges are wider on roofs with unusual materials; and storm modeling is strongest as a reason to go inspect, not as proof of anything. If a vendor — us included — won't say where their data goes soft, that's the vendor to worry about.

A practical workflow: combining both, in order

Here's how a growing residential or storm-restoration company actually wires these tools together across a week. Adapt the numbers to your shop.

Step 1 — Scan the area before anyone moves (targeting)

Pick the area you're going to work — a subdivision, a few ZIPs, or a hail-affected band. Run it through your targeting tool and pull the ranked list of homes by roof-age range and, if you're in storm mode, per-roof exposure. This is the cheapest step and the highest-leverage one, because it decides where every other dollar goes.

Output: a sorted list of addresses, each with a reason ("roof age ~19–23 yrs" or "likely 1.5-inch hail loading, windward slope").

Step 2 — Split the list by motion (reach)

Different homes deserve different outreach:

• Top of the list, dense streets → assign to canvassers as a walking route.
• Top of the list, spread out → drop into a targeted mail run.
• Past customers and old estimates that re-surface on the list → route to your CRM for a personal re-engagement call. These are the warmest doors you'll ever knock, because there's already a relationship and a record.

Step 3 — Knock or mail with a real reason (reach → inspect)

A rep who walks up able to say something specific about that roof outperforms a rep reciting a generic pitch. "Your roof's reading right around twenty years from the street, and this part of town took hail in the spring — worth a free look" is a different conversation than "we're doing roofs in the neighborhood." The targeting data is what lets a green rep sound like a veteran without ever climbing a ladder.

Step 4 — Inspect and document (inspect)

Now a human gets eyes on it — from a ladder, a drone, or the ground depending on your safety rules and the homeowner's permission. This is where you confirm what targeting predicted, capture condition, and document honestly. Targeting got you to a worn roof; the inspection is what's real.

Step 5 — Measure and quote (measure)

For the inspections that turn into real opportunities, now you pull the precise measurement report — EagleView or a competitor. You're spending measurement dollars only on qualified, inspected, interested homeowners. This is where measurement software is worth every penny, because targeting made sure you're not measuring dead roofs.

Step 6 — Close, order, build (close)

Material orders flow off the measurement numbers; the crew schedules; the job gets built. Full circle.

Notice the tools never overlapped. Targeting owned steps 1–3. Inspection is human. Measurement owned step 5. Anyone selling you one tool to do all of it is overselling.

Common mistakes contractors make picking between these

After enough conversations with roofing owners, the same expensive mistakes repeat. Here they are, with the fix.

Mistake 1: buying measurement and expecting leads

The pitch sounded like "this software grows your business," so the owner bought a measurement subscription expecting the phone to ring. It didn't, because measurement is a stage-4 tool. Fix: if your problem is an empty pipeline, you have a targeting problem, and no measurement product solves it.

Mistake 2: buying targeting and expecting a stamped estimate

The reverse. An owner scans an area, gets a great list, and then complains the tool "didn't give me squares." It was never supposed to. Fix: keep your measurement tool for quoting; targeting feeds it, it doesn't replace it.

Mistake 3: trusting year-built or a hail map as "targeting"

Covered above, but it's worth repeating because it's the most common one. Year built misses re-roofs; hail maps miss per-roof variation. Both send crews to the wrong doors with confidence. Fix: sort by roof condition signals — age range and per-roof storm exposure — not by house age or weather polygons.

Mistake 4: measuring before qualifying

Pulling per-address measurement reports on homes you haven't inspected or even confirmed are interested. Every one of those on a dead roof is wasted spend. Fix: measurement is the last paid step, not the first.

Mistake 5: treating storm odds as proof

Using a storm model to tell a homeowner their roof is "definitely damaged" or implying coverage. That's both inaccurate and a fast way to lose trust and run afoul of how claims actually work. Fix: storm modeling is a reason to inspect and document; the inspection and the carrier decide the rest. The contractor documents, the insurer decides coverage, the homeowner owns the claim.

Mistake 6: ignoring rep economics

Owners obsess over per-report cost and ignore the much bigger cost: a green canvasser who knocks bad doors, never makes money, and quits in six weeks. Fix: good targeting is partly a retention tool. Reps who knock viable doors close, earn, and stay.

A buyer's checklist before you spend a dollar

Run any tool — measurement or targeting — through these questions before you commit.

For a measurement tool (EagleView and competitors):

• How fast is turnaround on a report, and is there a same-day option for storm rushes?
• What's the per-report cost at my expected volume, and is there a subscription that lowers it?
• Does it integrate with my estimating and ordering software so squares flow straight into a quote?
• How accurate is it on steep, complex, or heavily treed roofs where imagery struggles?
• Does it cover the geographies I work, including rural addresses?

For a targeting tool (RoofPredict and the category):

• Does it give roof age as an honest range, or does it pretend to know an exact date? (Range = credible.)
• Does it model storm exposure per roof, or is it just re-skinning a hail map? Ask them to explain the difference; if they can't, walk.
• How fresh is the imagery, and how does it handle recent re-roofs that imagery might miss?
• Does the output route cleanly into how I actually work — canvass routes, mail lists, CRM re-engagement?
• Will the vendor state plainly where the data is soft? (Honesty about limits is a quality signal, not a weakness.)
• Does it stay on the right side of claims — documentation and prioritization only, no promises about coverage, deductibles, or "free" roofs?

For the sequencing question (the one that actually saves money):

• Am I solving a pipeline problem (need targeting) or a quoting problem (need measurement)? Be honest about which one is actually bleeding money.
• If pipeline, am I about to waste measurement dollars on unqualified doors? Fix targeting first.
• Can these two tools stack so I scan, qualify, inspect, then measure — in that order?

A closer look at the measurement category beyond EagleView

EagleView gets named in the search because it's the most recognized brand, but the measurement category has real competition, and understanding the field helps you avoid overpaying or locking into one vendor. Treat this as orientation, not an endorsement of any single product.

• Aerial-only measurement (EagleView and similar): aircraft or satellite imagery, no one on site, fast turnaround, strong on standard residential geometry. The weak spot is heavily treed lots, very steep or complex roofs, and addresses where the imagery is stale.
• Drone-and-software measurement: a rep flies a drone over the property and software builds the model from the captured images. More control over freshness and angle, and you can document condition at the same time, at the cost of sending a body and a drone to each site.
• Phone-and-photo measurement apps: a rep walks the property with a phone, and the app stitches a model from photos. Cheaper per job, useful for a small shop, but slower and more dependent on the rep doing it right.
• Sketch-from-imagery services: a human draftsperson traces the roof from imagery you provide. Flexible, sometimes cheaper, turnaround varies with the queue.

The common thread across all of them: you bring the address. Every product in the measurement category assumes the targeting question is already answered. That's the whole reason measurement and targeting aren't rivals — no measurement vendor, however good, is trying to tell you which 200 houses out of 3,000 to chase. They're competing with each other on price, speed, and accuracy of the geometry, not with the targeting category at all.

When you compare measurement vendors, the real axes are turnaround time, per-report cost at your volume, integration with your estimating software, and accuracy on the hard roofs you actually run into. None of those axes is "finds me leads," because none of them do.

A closer look at the targeting category

The targeting category is younger and messier, so buyers get burned more often here. The products fall into a few buckets, and knowing which bucket you're being sold matters.

• List brokers with a roofing skin. These resell demographic and property data — home value, year built, owner age, equity — with roofing-flavored labels. Useful for a rough mail list, but as covered, they sort by the wrong variable. Year built is not roof age, and income is not roof condition.
• Hail-map and storm-alert services. These tell you a region got hit and sometimes draw a swath. Good for situational awareness the morning after a storm. They generally do not resolve damage likelihood down to the individual roof, so they leave the real sorting to you.
• Imagery-based condition and age tools. These read the roof itself from aerial and street imagery to estimate wear and age. This is the bucket that actually answers "which roof," and it's where the honest age-range and per-roof modeling live.
• Full route-and-outreach platforms. Some tools layer canvass-route building, mail integration, and CRM hooks on top of the condition data, so the ranked list flows straight into how you work.

The quality gap inside this category is wide. A list broker and an imagery-based age tool both call themselves "lead targeting," and they are not remotely the same product. The tell is simple: ask what signal the ranking is built on. If the answer is "home value and year built," you're buying a demographic list. If the answer is "the condition and age of the actual roof, plus how the storm loaded it," you're buying targeting that sorts by the variable that matters.

Worked example: a 2,000-home subdivision

Numbers make the categories concrete. Walk through a single subdivision two ways. Replace these figures with your own; the structure is what teaches.

Assume a built-out subdivision of 2,000 homes, mixed ages, that took a moderate hail event in the spring.

The guess-and-go approach (no real targeting):

• You mail all 2,000 homes a generic storm postcard.
• A typical cold residential mail response lands in the low single digits per thousand. Say you get 30 calls.
• Of those 30, a chunk have roofs that are fine or too new; suppose 12 turn into real inspections.
• You pull measurement reports as quotes firm up — say on 12 addresses — and some of those still don't convert.
• You paid to print and mail 2,000 pieces and measured a few homes that were never strong candidates.

The target-then-reach approach:

• You scan the 2,000 homes first and surface the subset whose roof-age range and per-roof storm exposure flag them as real candidates — say 600 homes instead of 2,000.
• You mail those 600. Because every recipient has an actual reason to care, response rate per thousand climbs.
• Your canvassers walk the densest clusters of those 600 with a specific reason at each door, so conversation-to-inspection rates rise.
• You pull measurement reports only on inspected, interested homeowners — and almost none of that measurement spend lands on a dead roof.

Same subdivision. The second approach mails a third as many pieces, gets a higher response on each thousand, sends reps to better doors, and protects the measurement budget. The measurement tool was identical in both runs and did its job perfectly both times. What changed was everything that happened before the measurement — and that's exactly the work targeting does and measurement can't.

The lesson hiding in the numbers: in the guess-and-go run, the measurement tool looked like the expensive line item, but the real waste was upstream — the 1,400 wasted mail pieces and the reps' wasted days. Owners who only watch the per-report invoice optimize the wrong number.

Storm season vs. retail: the funnel changes shape

The right tool mix shifts depending on whether you're working a storm or running steady retail replacement, and contractors who run both modes should think about them separately.

Storm mode

After a hail or wind event, time compresses and the targeting question gets sharper. The whole region is suddenly a candidate, out-of-town crews swarm in, and homeowners get a postcard from everyone. Here, per-roof storm modeling earns its keep most: it separates the roofs that actually took loading from the ones that just sat under the same swath. A storm crew that works the windward, hardest-hit roofs instead of the whole ZIP gets to real damage faster and wastes fewer inspections.

Measurement matters in storm mode too, because adjusters and homeowners want documentation and you want fast, defensible numbers. But the documentation has to stay honest: you document the conditions and the estimate; the carrier decides coverage; the homeowner owns the claim. A storm model is a reason to inspect, never a coverage promise. Storm mode is exactly where contractors get tempted to overclaim, and exactly where overclaiming costs the most in trust and reputation.

Retail mode

Between storms, the funnel is calmer and roof age carries more of the weight than storm exposure. You're working aging-out roofs — the twenty-year-old shingles that are due regardless of weather. Targeting here means sorting a neighborhood by age range and working the oldest roofs first, plus mining your own customer book and old estimates for roofs that have crossed into replacement territory since you last talked.

Retail mode is where a lot of shops underuse their own data. Past customers and dead estimates from years ago are sitting in a CRM, and some of those roofs are now genuinely due. Targeting that re-surfaces them turns work you already paid to acquire once into work you can win again, without buying a single new lead. Measurement still shows up at the end to quote them — same sequence, calmer pace.

The takeaway: in storm mode, lean on per-roof storm modeling; in retail mode, lean on roof-age range and your own book. The measurement step is identical in both. Only the targeting signal you weight changes.

What good targeting data should and shouldn't claim

Because the targeting category is young, the marketing runs ahead of the reality more often than it should. Here's a plain table of what an honest targeting tool can and can't tell you, so you can hold any vendor — including us — to it.

If a vendor lives in the right-hand column, the data underneath is probably weaker than they're letting on, and the overclaiming itself is the warning. A tool that tells you where it's soft — stale imagery, unusual materials, the limits of modeling — is showing you it understands its own data. In a trade where everybody's been burned by a marketing subscription at least once, honesty about limits is the most useful signal you'll get from a sales call.

Integrating targeting and measurement into one tech stack

If you decide to run both — which most growing shops land on — a few practical notes on wiring them together so they actually save time instead of creating busywork.

1. Keep the systems of record straight. Targeting feeds the top of your CRM as new candidate records or campaign lists. Measurement reports attach to the opportunity at the quoting stage. Don't let either tool become a second, competing CRM.
2. Tag the source of every candidate. When a door comes from a targeting scan, tag it, so months later you can see whether targeted doors closed at a better rate than walk-ups and referrals. Without the tag, you'll never know if the tool paid for itself.
3. Hand reps the reason, not the raw data. A canvasser doesn't need the whole model. They need one line: the roof-age range and whether the area took a storm. Push that into whatever route or canvassing app the reps already use.
4. Trigger measurement off a stage change, not a hunch. Pull the measurement report when an opportunity hits "inspected and interested," not before. That single discipline keeps measurement spend off dead roofs and is the easiest money you'll save all year.
5. Review the funnel monthly. Look at doors worked, inspections booked, quotes pulled, and jobs signed, split by source. If targeted doors aren't converting better than your old guess-and-go, something in the data or the pitch is off, and you want to know fast.

Wired this way, the two categories reinforce each other instead of duplicating effort. Targeting decides where to spend attention; measurement prices what attention earned. The CRM ties the two ends together and tells you whether the whole machine is working.

So which one should you buy first?

If you have steady leads and your bottleneck is quoting speed and material accuracy, a measurement tool is the obvious spend, and EagleView is a category leader for good reasons. If your trucks have capacity and your reps are burning days on streets full of new roofs, a measurement tool won't touch that — you need targeting first, and only then will your measurement spend stop leaking onto dead roofs.

Most growing shops end up with both, in that order: target to decide which roofs deserve attention, then measure the ones that earned it. They aren't rivals. They're consecutive steps in the same sale, and the contractors who understand that stop overpaying to measure roofs that were never going to buy — and stop knocking the whole street when only part of it ever needed them.

The search that brought you here framed it as a fight. It isn't one. It's a sequence. Get the sequence right and both tools earn their keep.

FAQ

Is EagleView a lead-generation tool?

No. EagleView is an aerial measurement tool. You give it an address you already care about and it returns precise roof geometry — squares, pitch, ridge and hip lengths, facet diagrams — for quoting and ordering material. It does not tell you which addresses to point it at, whether a homeowner needs a roof, or which doors to knock. Finding the lead is a separate, earlier job handled by targeting software.

What's the actual difference between EagleView and roof-targeting software?

They solve opposite problems in your sales funnel. Measurement software (EagleView) answers 'how big and what shape is this one roof?' at the quoting stage. Targeting software answers 'which roofs in this area are worth going after?' at the very top of the funnel, before you've spent a dollar reaching out. One assumes you have the lead; the other helps you find it. Most growing companies use both, in that order.

Can roof-targeting software give me roof measurements for a quote?

Generally no, and you shouldn't expect it to. Targeting tools output a ranked list of addresses with a reason each one qualified — usually a roof-age range and storm exposure. They don't produce squares, pitch, or linear feet. You still pull a measurement report at the quoting stage. The two tools stack rather than replace each other.

How accurate is roof age estimated from aerial imagery?

Accurate enough to sort a street, honest only as a range. Imagery reveals wear signals — granule loss, streaking, curling, patches, fading — that correlate with age, so a credible tool returns something like '18–22 years,' not a fake exact date. Nobody can read an install invoice from the sky. Treat the range as a prioritization signal that gets a qualified rep to a worn roof, not as a final verdict; the on-site inspection confirms condition.

Why isn't a hail map good enough for storm targeting?

A hail map shows where hail was reported across a region — useful for knowing a county got hit, but it paints thousands of roofs one color. Per-roof storm modeling accounts for estimated hail size, storm track and direction, and each roof's slope and orientation, so it can tell you the windward houses took real loading while sheltered ones likely didn't. The map shows where it hailed; per-roof modeling shows which roofs it actually wore out.

Does targeting software replace the on-site roof inspection?

No. Targeting gets you to the right doors faster by flagging worn or storm-exposed roofs, but imagery can't see decking, underlayment, ventilation, or moisture problems, and image freshness varies. A human still has to get eyes on the roof to confirm and document condition. The age figure is a range and the storm figure is odds — both are reasons to inspect, not substitutes for inspecting.

Which should I buy first, measurement or targeting software?

Diagnose your bottleneck. If you have steady leads and your pain is slow quoting or material errors, buy measurement first. If your crew burns days knocking streets full of new roofs and your pipeline is thin, you have a targeting problem that no measurement tool can fix — buy targeting first. Bad targeting also wastes measurement dollars, since every per-address report you pull on a dead roof is pure loss.

Why doesn't 'year built' work for finding roofs that need replacing?

Year built is the age of the house, not the roof, and re-roofs are invisible to county and listing records — nobody updates the tax roll when shingles get swapped. A 1994 house may be on its third roof; a 2015 house may have failing builder-grade shingles. Targeting from year built sends crews to plenty of recently re-roofed homes. Sort by roof condition signals instead.

Where does RoofPredict fit relative to EagleView?

RoofPredict is a targeting tool, not a measurement tool. It scans an area and ranks homes by an estimated roof-age range and storm exposure modeled per roof, so you knock and mail the right doors and skip the new ones. It does not produce squares or pitch and won't replace the measurement report you pull at quoting time. The two stack: RoofPredict decides which roofs deserve a measurement; EagleView or a competitor prices the ones it qualified.

Can I use storm modeling to tell a homeowner their roof is damaged or covered by insurance?

No, and doing so is a fast way to lose trust and create problems. Storm modeling is odds, not proof — a strong reason to go inspect and document, never evidence of damage or coverage. The contractor documents conditions and the estimate, the insurer decides coverage, and the homeowner owns the claim. Keep targeting data in its lane: it tells you where to look, not what's covered.