This is a live, fully interactive market scoring dashboard — not a slideshow, not a mockup. Explore all 3,222 U.S. counties ranked by market opportunity for pest control. Your model would be built to your vertical, your strategy, and your weights.
Each factor is weighted based on its predictive value for pest control revenue — then scored, normalized, and combined into a single county-level composite. Here's what's driving the model.
Warm climates extend pest season and increase service frequency. Counties with high annual CDD represent year-round revenue, not seasonal contracts.
NOAA 10-yr avgDense residential areas compress drive time between stops and raise rep productivity. Sparse rural counties cost more to serve than they return.
Census ACSHomeowners drive pest control decisions — renters defer to landlords. Counties with high ownership rates have a deeper and more accessible addressable market.
Census ACSOlder homeowners are consistently higher-converting customers for recurring pest services — and are less likely to cancel than younger, more mobile households.
Census ACS 65+Homes built pre-2000 have more entry points, aging foundations, and less effective insulation — all of which correlate with higher pest pressure and recurring need.
Census ACS pre-2000Fast-growing counties bring new construction and new homeowners — a favorable combo for early market entry before competitors saturate the territory.
2024 building permitsRaw market size sets the ceiling. Larger counties have more households, more service routes, and more room to grow revenue without saturating the territory.
Census ACSHigher-income households are more likely to own their homes, invest in recurring services, and convert on premium offerings — all of which improve unit economics.
Census ACSHigh heat combined with humidity accelerates pest activity and breeding cycles. Counties with sustained warm, humid conditions see higher infestation rates and repeat service needs.
NOAA avg tempEach factor is weighted based on its predictive value for solar revenue — then scored, normalized, and combined into a single county-level composite. Here's what's driving the model.
Global Horizontal Irradiance measures raw solar energy available at ground level. Higher GHI means more kilowatt-hours per panel per year — the single strongest predictor of system ROI.
NREL dataSolar ROI is driven by what you're replacing. States with higher utility rates have shorter payback periods and stronger customer motivation — making them significantly easier to close.
EIA state ratesState-level tax credits, rebates, and net-metering programs directly reduce customer cost and compress sales cycles. More incentive programs = lower CAC and higher close rates.
DSIRE program countSolar is a considered purchase. Higher-income households have the credit profile for financing, the savings to buy outright, and the financial literacy to understand long-term ROI.
Census ACSRenters can't install solar — only homeowners make that decision. Counties with high owner-occupancy have a deeper, more accessible addressable market for residential solar.
Census ACSNew construction brings new homeowners who are actively making installation decisions. Fast-growing counties offer early-mover advantage before competitors saturate the market.
Census new unitsLarger counties have more potential customers and more installers competing for them. Population sets the market ceiling and influences the density of qualified leads per route.
Census ACSHigher home values correlate with larger roof systems, better financing terms, and customers who are more likely to invest in premium equipment — all of which increase average contract value.
Census ACSResidential solar is almost exclusively a single-family market. Counties with more detached single-family homes have a larger directly addressable install base.
Census ACSExpected Annual Loss as a percentage of building value captures exposure to climate-related damage. High-risk counties can reduce solar ROI through insurance costs and system vulnerability.
FEMA NRIWhat you just explored is a generic sample built for pest control. Your model would be calibrated to your vertical, your team size, and the markets you're actually targeting.
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