Case study: Solar calculator

Your customers get a first solar offer in minutes. Your team does not calculate it by hand.

For solar and battery installers who get the same pricing question again and again.

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The problem

Installers get the same question every day: what does a system cost for my house? Each answer means a manual calculation. The customer waits for a quote, and the installer spends time on every reply.

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What the system does

1. The customer enters the address and yearly power use in a Tally form.
2. Make finds the coordinates of the address (OpenStreetMap, Nominatim).
3. Make loads roof data for that location (Google Solar API) and one year of solar radiation (Open-Meteo).
4. Make calculates system size, yearly yield, savings, payback time, and CO2 saved. Google Sheets stores the input values.
5. A PDF offer is built from a Google Docs template.
6. The offer is sent by email, and the lead is saved in Airtable.

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Sample result

Sample values from the demo. The system uses the same formulas for every request.

Output	Sample value
System size	2.00 kWp
Yearly yield	1,948 kWh
Production as share of yearly use	98%
Estimated cost	2,800 EUR
Savings per year	682 EUR
Payback time	4 years
Savings over 20 years, after cost	10,838 EUR
CO2 saved per year	779 kg

The savings figure is yearly production times 0.35 EUR/kWh, so it is an upper limit. The model does not yet split self-consumption from feed-in. Roof pitch and orientation are not part of the calculation.

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What your team gets

• A first offer without manual calculation.
• The same calculation for every request.
• Each lead saved with the customer's details, in one table.
• Customers who see the numbers before the first call.

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Status

This is a demo with sample data. The next steps are to model self-consumption, add a battery option, and check the results against real installations.