Use case: energy and utilities

Automating the sales of renewable energy systems

Parts of selling solar and other renewable energy systems can be automated by combining data on buildings, roof suitability, solar radiation and existing installations. Solar cadastres rate roofs and estimate their yield. AI on satellite imagery can detect panels that already exist. Sales teams can then rank prospects before anyone visits a site.

Reference
UC-09
Technologies
  • Earth observation
  • Artificial intelligence
Industry
Challenge
Sales and market development
Updated
Published by
LETO SPACE

01When you need it

The task

Selling solar and other renewable energy systems to building owners takes work before the first offer: finding buildings that suit a system, checking the roof, estimating the yield and finding out whether a system already exists. When these checks run by hand, every prospect that turns out not to fit costs that work again.

Automation moves these checks to the start of the process. Data on every building in a sales region is combined, each building is scored, and the team works through a ranked list instead of a map.

02Data

Which data helps

03Technology

How the automation works

  1. Define the target: the sales region, the customer segment and the product, for example commercial roofs for photovoltaics with storage.
  2. Collect the layers: roof suitability, radiation and existing installations for every building in the region.
  3. Score and rank: the layers are combined into a score per building, using fixed rules or a model trained on past sales.
  4. Hand over: the ranked list goes into the CRM, with the key facts per building, so the team prepares each contact with data.
  5. Learn: the results of each contact flow back into the scoring.
A higher score means a more promising contact. Roofs that already carry panels are flagged as a case for storage or an upgrade. Illustrative list, not real data.

04Limits

Limits

  • Limit 01

    The roof itself needs a site check

    Data narrows the list, but it does not show the condition or load capacity of a roof. A technical check on site remains part of every offer.

  • Limit 02

    Data ages

    Roof models and imagery show the state at the date of the survey or image. Buildings and panels added since then are missing.

  • Limit 03

    Personal data

    Linking roof data to the owners of private homes creates personal data Source: European Union, EUR-Lex, 27 April 2016European Union, EUR-LexRegulation (EU) 2016/679 (General Data Protection Regulation), Article 4(1)27 April 2016Open source (opens eur-lex.europa.eu). The process needs a legal basis and a clear rule for how data is used.

05Our work

Our client project in this sector

One of our four anonymised client projects covers this topic, at an energy company. It used Earth observation and AI.

06Next steps

How we help

A ranked list is useful only once it reaches the CRM and the daily sales routine. In strategy and use cases we test the business case for your sales region; in implementation we run the pilot with KPIs and take it into daily sales work.

To find providers of roof analyses and imagery, Spacegraph, our discovery platform, has an industry category "Energy & Utilities".

07Use cases

Frequently asked questions

Q1Which data sources can feed an automated sales process for solar systems?

Roof suitability and yield from a solar cadastre, such as the one published for Styria Source: Land Steiermark, accessed 6 October 2026Land SteiermarkSolarpotenzial Steiermarkaccessed 6 October 2026Open source (opens technik.steiermark.at), solar radiation for each location Source: European Commission, Joint Research Centre (JRC), accessed 8 October 2026European Commission, Joint Research Centre (JRC)PVGIS: Data sources and calculation methodsaccessed 8 October 2026Open source (opens joint-research-centre.ec.europa.eu), and a map of the panels that already exist Source: Joule, 19 December 2018JouleDeepSolar: A Machine Learning Framework to Efficiently Construct a Solar Deployment Database in the United States (Yu et al., Joule 2, 2605 to 2617)19 December 2018Open source (opens doi.org). Your own customer and grid data complete the picture.

Q2Does data protection law apply to roof data?

It does as soon as the data relates to an identified or identifiable natural person, for example when roof data is linked to the owner of a private home Source: European Union, EUR-Lex, 27 April 2016European Union, EUR-LexRegulation (EU) 2016/679 (General Data Protection Regulation), Article 4(1)27 April 2016Open source (opens eur-lex.europa.eu). Clarify the legal basis with your data protection officer before the first campaign.

Q3How do we start?

Start with one sales region and one product, and compare the ranked list with the results of your current approach over a few months. This shows whether the data improves the hit rate before you integrate it into your CRM. Our consulting overview shows the path from the problem to the pilot.

Sources (4)

  1. Land Steiermark, accessed 6 October 2026Solarpotenzial Steiermark (opens technik.steiermark.at)
  2. European Commission, Joint Research Centre (JRC), accessed 8 October 2026PVGIS: Data sources and calculation methods (opens joint-research-centre.ec.europa.eu)
  3. Joule, 19 December 2018DeepSolar: A Machine Learning Framework to Efficiently Construct a Solar Deployment Database in the United States (Yu et al., Joule 2, 2605 to 2617) (opens doi.org)
  4. European Union, EUR-Lex, 27 April 2016Regulation (EU) 2016/679 (General Data Protection Regulation), Article 4(1) (opens eur-lex.europa.eu)

Contact

How does your sales team find customers for renewable energy systems today? Let us start there.

Prefer to talk?

Tell one of our experts about your project. Together we work out where you stand, whether satellite data and AI can help and what a sensible next step would be.

Both calls are free of charge and take place online. You choose a date in our booking calendar.