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ProfFausat/market-segmentation-nigeria

Domaine:

environment and energysocioeconomic

Type de record:

project
Créateur:
Pro
Hôte:
Which local government areas should an off-grid energy operator enter? A SQL-first market segmentation of Nigeria's 774 LGAs # Market Segmentation for Off-Grid Energy Expansion in Nigeria **Which local government areas should an off-grid energy operator prioritise for expansion, and what does each type of market need?** A pay-as-you-go solar company deciding where to expand faces a problem that looks like customer targeting but sits a level above it. Before asking which household to approach, the company must decide which *market* to enter — where to place agents, stock, service infrastructure and credit exposure. Enter the wrong local government area and no amount of household-level targeting will recover the cost. Nigeria has 774 LGAs and they differ enormously in the things that determine whether an off-grid energy business succeeds: how many people live there, how many lack electricity, whether they can pay, and how expensive they are to serve. Treating that variation as a ranked list loses information. LGAs are not better and worse versions of each other — they are *different kinds of market*, and each kind calls for a different operating model. The output is therefore a **typology**, not a ranking: a small number of market types, each named, profiled, and paired with what an operator should do differently there. --- ## What this project has found so far **Nigeria's electrification data cannot speak for a quarter of the country, and until now nobody had measured by how much.** The settlement-level electrification model this project depends on (World Bank GEP) publishes 708,536 settlement clusters with coordinates but no LGA. Assigning each to an LGA by its single representative coordinate misattributes population wholesale wherever a cluster is large and the LGAs beneath it are small. Two independent tests measure the damage (`sql/04_gep_quality.sql`): | | result | |---|---| | LGAs whose indicators are usable without a caveat | 600 of 774 (73.4% of population) | | LGAs flagged `suspect` | 169 | | LGAs with no settlement clusters at all | 4 — Agege, Ajeromi-Ifelodun, Mushin, …