KenyaEnergy and utilities2024 – ongoingENGIE Energy Access
Machine learning market targeting for solar appliance sales in Kenya
ENGIE Energy Access raised monthly sales 48% in a Kenyan pilot region that followed machine learning market recommendations
Problem
ENGIE Energy Access was a relatively early entrant in Kenya's off-grid solar market. In late 2022 its Kenya team named customer qualification and acquisition as top priorities. It needed to find dense areas with weak grid access where people could afford and repay for its solar appliances.
Approach
ENGIE used Atlas AI's Aperture platform, which combines geospatial machine learning data with ENGIE's sales data. It modeled spending levels and electrification for each of the 1450 wards in Kenya and recommended where to focus sales teams. In a pilot across three regions, the Western and Eastern teams were control groups. The Coast manager followed the recommendations and targeted the named areas.
Results
Takeaway
The result comes from one pilot region against two control regions. The page does not give the pilot's length or the sales base.
Categories
- Size
- Large enterprise
- Industry
- Energy and utilities
- Business function
- Marketing and sales
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and ML
- Adoption
- Vendor solution
- Evidence
- Vendor case study
Sources
Source summaries
Google Cloud's customer story describes how ENGIE Energy Access in Kenya used Atlas AI's Aperture platform to pick high-potential wards for solar appliance sales. In a three-region pilot, the region that followed the recommendations saw a 48% rise in monthly sales. The page carries no date; the Internet Archive first saved it on August 11, 2024.
Full details are in the original sources.
