The aim of my research is to advance our understanding of the entire pay-as-you-go (PAYG) solar home system (SHS) customer journey in East Africa to improve energy access for remote off-grid households.
A SHS consists of a solar panel, a battery and accompanying appliances, such as light bulbs and radios. This research examines the case study of Bboxx’s PAYG SHS customers in Rwanda. The findings derive from structured interviews and focus groups with Bboxx customers. Moreover, a convolutional neural network was developed to forecast users’ future short-term electricity consumption.
A better understanding of the PAYG SHS customer journey may increase the number of households with electricity access, as companies can better address the purchase barriers and tap into the power of customer recommendations. Moreover, this research improves understanding around SHS retention and offers a model that can be used to prolong customers’ electricity access.