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In the last 15 years, the price of solar and wind declined 83% and 63%, respectively. At the same time, the average cost of an electric vehicle has dropped by ~50%.
These cost declines unlock massive growth in these technologies' total addressable market size. They also create a new can of worms. The net result is still very positive, but it's worth noticing the unique risks that come with being a widely adopted technology.
As the price of any consumer good goes down, the average income of the purchaser begins to correlate more closely with the average income of a given population. As things get cheaper, more people can afford them.
But, the more available a good is to the broader public, the more susceptible it is to demand shocks.
Solar has entered this phase. The median US household income for owner-occupied households was $79K in 2021. 48% of residential solar adopters have a household income below $100K in the same year - the most recent available.
With higher interest rates and new regulatory structures in California, we've seen how price-sensitive the solar market can be now that a majority of households can afford it.
Higher monthly payments, due to interest rates and longer payback periods thanks to new net metering and storage regulations, affect the mass market more than higher-income populations with disposable income.
EVs are not far behind. The average income of an EV owner is still 2x the average income of a US household. But income is the lagging indicator. The cost of the technology is the leading indicator, and EVs are more affordable than ever.
Derivatives from the Consumer
Not all consumer exposure in B2B software is the same. I've started to think of the risks as levels of derivation from the purchase decision.
The first level is one step removed from the consumer, where consumer surplus creates new demand. Carbon offsets are a great example.
Delta, Disney, JetBlue, and GM are amongst the largest offset purchasers in the world. Their primary customer is the individual consumer - if your business sells to them, you're also exposed to the consumer barring any regulatory intervention.
The next level (call it 1.5 derivatives) is one step removed but mission-critical. At this level, your customer is exposed to consumer trends and buying habits, but your software is essential for their day-to-day operations regardless of demand.
Examples include ERP systems, office of the CFO software, and HR/back office. Your customer might reduce their budget, and expansions will slow, but your solution runs a crucial part of the business.
The final level is two derivatives from the consumer - a solution sold to an operator who works with someone who sells to the consumer. EV charging network software fits this framework.
These networks now have owner-operators who need solutions to manage them effectively. The actual purchase of EVs is the only exposure in this ecosystem. Once EVs hit a critical mass, the demand for operating and maintaining charging networks becomes more insulated from any singular purchasing cycle.
Consumer Risk = Mass Adoption
After the last decade, adding any risk to a climate technology will give some of us PTSD. But, this risk retires an old one - the risk of mass adoption.
We now know costs in crucial technologies are at levels where a shift in consumer sentiment impacts near-term purchasing habits. A decade ago, we didn't know if these technologies would ever reach the average American. That’s a major win.
I'd much rather solve cyclical problems where greater than 50% of the household market is in play than worry if more than 3% would ever care.