How to tell a climate tech investor story when your evidence is a measurement
A pilot proves the hardware works, not that a buyer will pay at scale. How to build a climate tech investor story on claims that survive diligence.
- Pair each technical result with a named buyer's cost, risk or revenue change, then show the measurement behind it.
- A successful pilot shows the hardware works under tested conditions. Investors at Series A and B also need evidence that a buyer will pay and that you can deliver at scale.
- Label every number measured, modelled or projected, and keep the data and assumptions in the data room.
- Lead with technical feasibility at Seed, a named buyer's economics at Series A, and repeatable unit economics at Series B.
Climate hardware companies are rarely short of evidence. They are short of evidence arranged in the order an investor decides in: buyer first, economics second, measurement third.
Why does a successful pilot not convince Series A and B investors?
Because a pilot shows the technology works under tested conditions, not that a buyer will pay for repeat deployments at viable margins. A battery pilot's efficiency reading says little about what a customer would pay, what each installation costs, or how performance holds in routine use.
Capital intensity raises the bar. When funding tightens, capital-intensive climate tech companies are among the first to struggle to raise, because the business behind the hardware needs factories and long sales cycles before it pays back. A strong technical result does not carry that round on its own.
Connect each pilot result to one buyer's economics. If a utility is evaluating your battery, show how measured performance changes its cost per unit of energy delivered, under its operating conditions and with stated cost assumptions. Keep the measured result separate from the estimated cost change, and never treat an evaluation as a purchase commitment.
What does an investor-grade climate tech story contain?
It starts with a named buyer, the cost, risk or revenue change you expect for that buyer, and the measurement that supports it. Put the buyer's decision first, so the investor can judge whether the technical result affects something anyone would pay for.
Take a grid operator testing a transformer. A lower operating temperature demonstrates technical performance. Claiming lower maintenance cost also requires showing how temperature drives maintenance, what the operator spends today, and which assumptions link the two. The temperature is measured, the saving is modelled, and neither establishes that the operator will buy at your price.
Then explain what happens after the pilot: manufacturing cost, installation requirements and the buyer's purchasing process all change the economics at scale. We cover the same gap for every deep tech company in the prototype works, now prove the commercial case.
How should founders label claims as measured, modelled or projected?
Label every number in the deck and name its source.
- Measured: observed performance under stated conditions, with instrument records and method.
- Modelled: a calculation that applies assumptions to measured evidence, such as a customer's expected cost per cycle.
- Projected: a future scenario, such as savings across a planned fleet, even when a model produced the figure.
Conflating them creates the diligence problem. If projected fleet savings are presented as measured, the investor finds the underlying records cover one pilot installation, and every other number in the deck is now in doubt. Keep each claim inside its tested boundary and state how sensitive the modelled results are to their assumptions.
How much MRV detail belongs in the deck and how much in the data room?
The slide carries a labelled headline number, its category and the conditions that make it meaningful. The data room carries the full monitoring, reporting and verification trail: raw sensor records, calibration logs, methodology assumptions and third-party verification reports.
Keep a detail on the slide if removing it would change how the number reads. That usually means the baseline, the measurement period, the operating conditions and any limit on the claim. A footnote should lead an investor to the supporting file, never hide a qualification that belongs beside the headline. We set out how to structure the room in what goes in a deep tech data room.
How do founders avoid vague green language?
Replace "clean", "green" and "sustainable" with a named metric, a baseline and a method for comparing the two. If a battery cuts emissions, say what equipment it replaces, which emissions are counted, and whether the difference was measured in a pilot or modelled.
Regulators already treat vague claims as a risk. The UK Competition and Markets Authority's Green Claims Code says general claims such as eco-friendly or sustainable must reflect the whole life cycle of the product and be justified by the evidence. A CMA-led global sweep found 40% of green claims made online could be misleading. An investor deck is not consumer advertising, but investors read it with the same suspicion, and a measured efficiency gain does not by itself prove a life-cycle emissions reduction.
What should lead the story at Seed, Series A and Series B?
Technical feasibility at Seed, a named buyer's economics at Series A, and repeatable unit economics at Series B.
| Stage | Lead evidence | Labels expected | Common failure |
|---|---|---|---|
| Seed | Prototype tests or early pilot data under stated conditions | Measured results, modelled unit cost kept separate | Treating lab performance as proof of commercial cost |
| Series A | Field pilot results and a named buyer's letter of intent or offtake talks | Measured pilot performance, modelled buyer savings, projected orders | Presenting a non-binding letter of intent as revenue |
| Series B | Signed offtake or repeat orders, yield across batches, cost per unit | Measured production cost and contracted revenue, projected scale savings labelled | Using one good batch to claim repeatable unit economics |
The branding side of the same problem, 3 buyers each needing a different argument, is in strategic branding for cleantech companies.
Where should the market numbers come from?
From an original source an investor can check, such as IEA investment data or BloombergNEF research, rather than an agency blog or a social post. Record the institution, publication date, period, geography and what the figure actually measures, because energy investment, venture funding and your addressable market are different pools of money.
A sector investment figure establishes scale. It does not establish demand for your equipment. If a statistic, client name or result cannot be verified, leave it out: one invented number discredits the rest of the account.
What else do climate founders ask?
What if we have not built MRV infrastructure yet? Keep the pilot's raw readings, instrument records and calculation assumptions, say which results an independent party could reproduce, and label anything unverified as such.
How should we describe a carbon benefit? Name the emissions boundary, the baseline and the calculation method. If equipment performance was measured but the emissions impact was modelled, call the carbon saving modelled.
Does grant funding change the story? A grant shows how a technical milestone gets funded without more equity. It does not show buyer demand, so show separately what customers have committed to buy.
The evidence sets the limit of each claim. Founders who keep those limits visible give investors a story they can test, and keep an evidence trail that rebuilds itself for the next round.
Written by Mejo Kuriachan. More in the blog, the glossary and the FAQ.