Clean energy for the last-mile: customizing delivery to match rural customers’ preferences

Energy is vital to daily life, wherever you live. In rural sub-Saharan Africa, where three out of every four people lack access to electricity, energy poverty has real consequences for people’s livelihoods and well-being.

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Jonars B. Spielberg

The good news is that off-grid solutions are getting better: cheaper, longer-lasting, more environmentally-friendly. Thanks to new business models, which include innovative financing and delivery options, technology is reaching more and more customers.

Even so, last-mile customers — the poorest and most remote, who stand to benefit most from greater electricity access — remain difficult to reach. Their low density and purchasing power means that servicing this market segment is hard to justify from a purely for-profit perspective. Even when commitment to reach last-mile customers exists, we still don’t know enough about them. Not all customers think alike.

When targeting last-mile customers, we need to understand their needs and preferences. The best technology will go unused, sitting on a shelf collecting dust without an appropriate, tailored delivery platform that gets it into the hands of customers.

Photo: Johanna Pinneo, Ripple Effect Images, Solar Sister Photo: Johanna Pinneo, Ripple Effect Images, Solar Sister

What are last-mile customers’ sales channel preferences when it comes to household energy products?

Working in Tanzania with Solar Sister, a social enterprise that trains and recruits last-mile women entrepreneurs to sell solar lanterns in their local communities, we set out to answer this question.

Over the course of 5 weeks in summer 2017, my research team and I administered a survey-embedded experiment to 350 rural residents in 15 villages across central and eastern Tanzania. We selected villages close to those where Solar Sister operated, but that had no direct contact with the organisation. The intent was to find residents similar to Solar Sister customers but who did not know about them, so that their preferences would not reflect biases that any interaction might cause.

Each survey respondent was presented with five pairs of hypothetical salespeople. Each salesperson was defined by four randomly assigned characteristics that could take on one of two values. The four characteristics were: assistance (local or over the phone), familiarity (know and trust or don’t know), gender (male or female), and payment option (single payment or multiple payments). For each pair, the survey respondent was asked to choose which salesperson they were more likely to buy a solar lantern from. By analysing all of the choices, we could then determine which characteristics are more or less important for last-mile customers.

This type of experiment called discrete choice or conjoint, has advantages over directly asking respondents their preferences. It helps minimise ‘desirability bias’, which is having the respondent give us the answer he or she thinks we want to hear. It also presents choices in a way that is more realistic: having to choose between two people, rather than two abstract characteristics.

What did we learn?

The main results show that rural respondents have a strong preference in favour of local assistance and for salespeople they know. Of less importance are the payment option and gender of the salesperson, though multiple over single payments and women over men salespeople were slightly preferred. This supports the notion that rural customers place considerable importance on the social aspects of a purchase, which far exceeded the financial consideration of paying for a product in installments.

“The best technology will go unused, sitting on a shelf collecting dust without an appropriate, tailored delivery platform that gets it into the hands of customers.”
Photo: Johanna Pinneo, Ripple Effect Images, Solar Sister Photo: Johanna Pinneo, Ripple Effect Images, Solar Sister

The data can also be parsed in a few different ways to gain further insights. For instance, we can see preferences for combinations of characteristics, such as local assistance from a woman or payment in installments from someone the customer doesn’t know. Two points stand out. First, a multiple payment schedule becomes more preferable when paired with either a local or familiar salesperson. One way to interpret this is that higher levels of trust are preferred as a way of easing transaction costs when collection of payments over time is required. Second, in all three combinations that include the gender characteristic reveal a preference for men. Though these preferences are small in magnitude, it does suggest a gender bias against women. This underscores the important role that empowering women with entrepreneurial opportunities might play in counteracting such bias.

We can also sort respondents into different categories to see how their preferences change. We did this in two ways: by gender and degree of ‘last-mileness’. Women tend to prefer local assistance, women salespeople, and multiple payments more than men; the preference for familiarity was essentially the same in magnitude across men and women.

We also developed a last-mile index, or LMI, to see if preferences change as a customer becomes more last-mile. The LMI is a composite of three indicators that measure poverty level, grid access and physical remoteness. The results show that, as LMI increases — that is, as respondents become more last mile — the preferences for local assistance and a familiar salesperson remain stable. In contrast, as LMI increases, the preference for multiple payments over a single payment increases slightly, and the gender preference of the salesperson switches slightly from female to male. Though the switch for gender preference is small in magnitude, it suggests greater bias against women in more last-mile areas, where gender roles tend to be more traditional and fixed.

Photo: Johanna Pinneo, Ripple Effect Images, Solar Sister Photo: Johanna Pinneo, Ripple Effect Images, Solar Sister

In conducting this research, we sought to capture the view from below: to give voice to rural residents and what they want. Efforts to reach last-mile customers need to be based on a solid understanding of their needs — not only their technological inclinations but also their sales channel preferences.

Those seeking to put clean energy products into the hands of last-mile residents should take note. Rural villagers, especially women, place great importance on local, in-person after-sales assistance and close familiarity with a salesperson. Those designing new delivery models would be well-served to think beyond financial and technological factors. Important as these may be, social aspects also matter to last-mile customers, perhaps even more so.


Jonars B. Spielberg is a PhD student at MIT’s Department of Urban Studies and Planning. His research examines interactions between service providers and users, and the role of technology in international development. From 2013 to 2017, he worked on the Comprehensive Initiative on Technology Evaluation at MIT.


This article was featured in The Beam #8 — Together for Climate Justice, subscribe to The Beam for more. It is also available to view on our Medium page.