Statistics · public data · 2015 to 2025
Severe weather is a roofing-demand engine.
We tested a simple claim on 10 years of public data across 8 hurricane-belt states: when a storm hits, homeowners rush to search for roofers: a sharp, short-lived surge that lands exactly when local roofers are too swamped to pick up the phone. The data backs it, hard.
- +95%
- emergency search lift, storm week
- 7.1×
- urgency vs. planned searches
- ~3 wks
- the overflow window
- 221
- major storms, 8 states
Event study · 221 storms · weeks −8 to +8
The pattern
Each storm is aligned to “week 0,” and we track the search index for 8 weeks before and after, indexed so each series' own pre-storm level = 100. Emergency searches leap; planned searches stay flat.
Search demand around a storm (week 0 = storm), indexed to pre-storm baseline = 100
What we found
- 01
Magnitude. Emergency roofing searches rise +95% in the storm week versus their pre-storm baseline.
- 02
Speed. The peak is immediate: the storm week itself. There is no lag to wait out.
- 03
Persistence. Demand decays back to baseline in ~3 weeks, the window a roofer must cover before the wave passes.
- 04
Urgency. Emergency searches spike 7.1× harder than planned-roofing searches (+95% vs +13%), proof the surge is storm-driven urgency.
- 05
Dose response. Bigger storms, bigger spikes: the highest-damage third of storms drove +170% vs +68% for the smallest.
Every state confirms it
Emergency-search lift in the storm week, by state (states with lower everyday search volume show the largest percentage jumps):
The storms behind the spikes
The biggest named storms produced the sharpest surges. Here is the peak emergency-search index (0 to 100) in the landfall week:
| Storm | State | Landfall week | Property damage | Peak index |
|---|---|---|---|---|
| Hurricane Ian | Florida | 2022-09-25 | $15.4B | 49 |
| Hurricane Laura | Louisiana | 2020-08-23 | $10.7B | 8 |
| Hurricane Michael | Florida | 2018-10-07 | $8.9B | 7 |
| Hurricane Ida | Louisiana | 2021-08-29 | $8.6B | 25 |
| Hurricane Harvey | Texas | 2017-08-20 | $7.0B | 46 |
| Hurricane Helene | Florida | 2024-09-22 | $4.2B | 12 |
| Hurricane Florence | North Carolina | 2018-09-09 | $1.7B | 50 |
| Hurricane Irma | Georgia | 2017-09-10 | $77M | 31 |
Why you can trust it
✓ Placebo test. Running the same event-study on random calm weeks (no storm) produces no spike. The effect only appears around actual storms, so it isn't a seasonal or data artifact.
✓ Consistency. All 8 states are positive, from +55% to +292%. ✓ Clean data. 149,597 NOAA storm events and 92,848 weekly search readings, reconciled and tested at every step.
What it's worth
Using the +95% search lift as a stand-in for the inbound-call surge: a roofer fielding ~25 calls a week at a ~75% answer rate faces roughly double the volume in a major-storm week while the answer rate drops under the load, leaving roughly 20 to 25 missed calls that week. A voice agent that catches ~70% of the overflow recovers 15 to 18 leads; at a ~25% lead-to-job rate and ~$10,000 per job, that's on the order of $40k to $70k in recovered revenue per major-storm week, and more for a named hurricane.
These are illustrative assumptions, not measured results. The point is the shape: a big, brief, catchable surge.
How we built it
A fully reproducible pipeline on 100% public data. No client data, no black boxes.
- Data
- NOAA Storm Events Database (every recorded storm, 8 states, 2015 to 2025) joined to Google Trends weekly search interest for ~19 roofing keywords (via the DataForSEO API). Loaded into a Snowflake warehouse.
- Modeling
- A medallion pipeline (RAW → CLEAN → ANALYSIS) in dbt: storm damage parsed to dollars, events categorized into roof-relevant perils (wind, hail, tornado, tropical, heavy rain), searches grouped into emergency / hire / planned clusters, conformed to a state × week grain and tested at each layer.
- Analysis
- A pooled event-study across 221 major-storm episodes measuring the search lift relative to a pre-storm baseline, with placebo and per-state robustness checks.
- Honest caveats
- Google Trends is a relative interest index, not a call count (so the business figures above are illustrative). The rarest emergency terms are sparse week-to-week, so we read them as cluster aggregates. Flood damage is excluded from “roof-relevant” because flooding damages homes from below, not the roof.
Scope · FL · TX · LA · NC · SC · GA · AL · MS · 2015 to 2025 · Sources · NOAA NCEI Storm Events Database · Google Trends (DataForSEO), public data.
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