Home Services & Trades · Scenario 29

Roofing Company

After a storm, roofing demand spikes in specific neighbourhoods — and fades streets away. We map where damage and demand actually are and aim crews and marketing at the blocks that convert.

Method · Geospatial demand targeting

The situation

A roofing company markets across a whole metro evenly, even though demand is intensely local: a hailstorm hammers a few postcodes while leaving others untouched, and door-knocking or ads outside the damage zone waste time and money. Crews drive across the city between jobs, and the highest-converting streets go under-canvassed.

There is no map linking storm tracks, building age and past jobs to where demand and conversion are highest — so territory, canvassing and ad spend are spread thin instead of concentrated where roofs actually need replacing.

Whole-metro
spread evenly
Storm-driven
demand is hyper-local
Cross-town
crew drive time
No map
of damage & demand

Where we dig for the truth

We map storm tracks, building age and historical conversion to find the blocks where roofing demand — and the odds of closing — are highest right now.

Storm & hail track dataGeocoded job historyBuilding age & roof typeConversion by areaCrew routes & drive timeAd & canvassing spend
Booked jobs by storm-impact zoneDemand concentrates where the damage is04794142189160Direct hit95Adjacent482-3 km out204-6 km7Beyond

Demand collapses with distance from the storm track. Marketing and crews aimed at the direct-hit and adjacent zones convert several times better than a city-wide spread.

Our approach — Geospatial Storm-Demand & Territory Targeting

We overlay storm and hail data with building age and our own conversion history to score every neighbourhood for demand and close-rate, then concentrate canvassing, targeted ads and crew routing on the highest-scoring blocks while the damage window is open.

Routing is tightened so crews work clusters instead of criss-crossing the metro, cutting drive time and fitting more jobs into each day where demand is densest.

From a flat metro to a demand map1Map the demandOverlay storm tracks,building age and pastconversion.2Score the blocksRank neighbourhoods bydemand and close-rate.3Concentrate spendAim canvassing and adsat the highest-scoringzones.4Cluster the crewsRoute jobs by densityto cut drive time.
Weekly booked jobs after territory targetingSame crews, concentrated where demand is019395877W1W2W3W4W5W6W7W8S&I starts

Concentrating effort in the high-demand zones lifts booked jobs and close rate while crews drive less between them.

What changes

Same crews and budget, aimed by geography. Representative for a regional roofing company.

Representative 90-day movementClose rate14%27%▲ +13 ptsCrew drive time2.6 h/day1.5 h/day▼ -42%Cost per booked job$320$165▼ -48%Monthly revenue$420k$590k▲ +40%
Where the gain comes from+$170kmonthly revenueHigher close rate in-zone44%Less crew drive time30%Focused ad & canvass spend26%
Why this is not "social media management"
We didn't blanket the city with roofing ads. We mapped where the storms, the old roofs and our wins actually were, and aimed crews and budget at those blocks. Geography is data — and in roofing it decides who wins the post-storm rush.

Frequently asked questions

How do you target roofing marketing after a storm?
We overlay storm and hail tracks with building age and your own conversion history to score neighbourhoods for demand and close-rate, then concentrate canvassing, ads and crews on the highest-scoring blocks while the damage window is open.
What is geospatial demand targeting?
It is using location data — storm tracks, building characteristics, past wins — to map where demand and conversion are highest, so marketing and crews go where roofs actually need replacing instead of spreading across a whole metro.
Isn't blanketing the city with ads simpler?
Simpler and far more wasteful. Roofing demand is hyper-local after a storm; we aim crews and budget at the blocks that convert. Book a marketing audit.

Want this run on your numbers?

Send your job history and we’ll map where your next roofs — and best odds — are.