The Wrong Diagnosis

On counting markets versus reading them

Every few months, another B2B commerce company collapses in Nigeria and the same articles appear. Thin margins. Brutal unit economics. Wrong market, wrong timing. The diagnosis arrives after the court order, after the fleet sale, after the employees have scattered — delivered with confidence, as though timing were incidental.

Alerzo is the latest. The company raised $20 million, built a network of roughly 200 vehicles and 20 warehouses across Ibadan and Southwest Nigeria, and is now watching a Federal High Court freeze its assets over ₦4.38 billion owed to Moniepoint. The story has the familiar shape and the familiar explanations are already circulating. Most of them identify real things. What they miss is the earlier question — the one that should have been asked before the first vehicle was purchased.

Whether the model was ever viable, given the specific conditions it was entering, is a different question from whether the margins turned out to be thin. The first question has a method. The second is just a post-mortem.

Start with how a market gets counted.

Alerzo’s pitch, like every B2B informal retail pitch before it, began with a large number. Nigeria has roughly 10 million informal retail outlets. Southwest Nigeria alone accounts for perhaps 2.5 million. The number is real. The problem is what gets done with it next.

In the B2C consumer context, we’ve written before about the Population Illusion — the way headline consumer figures overstate demand by counting bodies rather than buyers. The same trap exists in B2B, wearing different clothes. Here the unit of count is retail outlets rather than consumers, but the inflation mechanism is identical: raw count standing in for convertible demand.

Run the actual filters on those 2.5 million outlets. How many carry sufficient daily turnover to absorb formal restocking at minimum viable order sizes? How many restock frequently enough — three or more times per week — to generate the transaction data that makes a platform defensible over time? How many operators have WhatsApp or any digital touchpoint that makes platform ordering feasible at all? Crucially, how many have the financial slack to consolidate purchasing with a single supplier, rather than buying opportunistically from whoever shows up with the right product at the right moment? It’s worth noting that even outlets with sufficient turnover often split purchases across suppliers deliberately — a rational hedge against stockouts and unreliable delivery in an environment where both are common. Consolidation requires not just financial slack but a level of platform reliability that takes time and track record to establish.

These are not hypothetical filters. They are the variables that determine whether a retail outlet can actually behave the way the model requires. Apply them honestly and the addressable base in Southwest Nigeria compresses to somewhere between 350,000 and 600,000 outlets — perhaps a quarter of the headline count. Still a substantial number. Large enough to build a real business. Alerzo was building and burning capital as though all 2.5 million were in play. Every naira spent acquiring an outlet that would never consolidate, that bought from Alerzo on Monday and from the open market on Thursday, registered as a customer in the metrics and as waste in the economics.

The second question is whether the cost architecture could survive what the market would actually pay.

B2B FMCG distribution in Nigeria yields 3–6% gross margin in realistic conditions. That ceiling is market-set. No operational efficiency, technology layer, or investor subsidy moves it meaningfully. The traditional distributors who survived in this sector for decades understood this before any startup arrived. They built accordingly: lean headcount, owner-operated transport, no delivery unless the order justified the trip. They also carried structural advantages that were harder to see from the outside — informal trade credit extended on relationship rather than data, enforcement through community accountability rather than contract, deep route knowledge built over years. Calling them unsophisticated gets it exactly wrong. They were correctly calibrated to what the market would actually bear, with tools a VC-backed platform couldn’t replicate quickly.

Alerzo and its peers laid a fundamentally different cost base across those same margins. Owned fleet. Twenty warehouses. Full logistics operations. Technology teams. The bet was that scale would enable backward integration — direct manufacturer relationships, private-label margin, financial services revenue layered on top of transaction data — turning a thin-margin distribution play into something with the unit economics of a fintech. It was a coherent thesis. The problem was that it required volume, at a pace and scale the genuinely convertible market could not deliver. At 3–6% gross on a ₦10,000 retailer order — ₦300–₦600 before any costs — the company needed to pick the order, load a vehicle, drive through Ibadan or Lagos traffic, locate a retailer who may have moved since registration, unload, and return the vehicle, all before a single naira reached the financial services layer it was banking on. That break-even volume only made sense against a demand figure that included every outlet in the count. Against the genuinely convertible subset, it was unreachable.

Capital instrument choice is the third variable, and often the most telling.

A business with thin margins, heavy fixed costs, and a long path to density needs patient equity with no fixed repayment schedule, released in stages as unit economics get proven at each level of scale. Warren Buffett’s McLane distributes $50 billion annually at thin margins and generates steady, compounding returns — but McLane was built over decades, with capital that waited for the density to come. It was never a 10x venture bet on an 18-month clock.

Alerzo’s ₦5 billion Moniepoint loan in January 2025 implied roughly ₦278 million in monthly repayments across 18 months. By December, the company had been repaying approximately ₦62 million per month — 22% of the required rate, across ten consecutive months. That number is not a cash flow timing signal. A business with sufficient operating cashflow does not miss 78% of its debt obligation for ten months running. The loan put a fixed obligation on top of a revenue base that was never going to generate the cashflow to service it. When the runway ended, the court order followed.

The pattern, assembled cleanly, looks like this.

A real inefficiency exists in a large market. A founder with genuine insight raises capital to address it. The pitch uses outlet counts as the demand figure. The model assumes purchasing behaviour that the target customer’s daily economics make structurally improbable — consolidation, advance ordering, platform loyalty. Fixed infrastructure gets built against thin margins and a variable, cash-dependent revenue base. Capital gets consumed reaching outlets that were never genuinely convertible. When venture funding tightens, debt fills the gap. The debt surfaces the underlying cashflow problem. The company fails.

Then the articles explain that the margins were thin.

The margins were knowable at the start. What failed was the demand assessment — and downstream of that, the cost architecture — and downstream of that, the capital structure. Each was predictable in its logic, even where the precise timing — how fast funding would dry up, how sharply the naira would move — was genuinely uncertain.

This matters beyond Alerzo. MarketForce shut down its B2B platform. Sabi pivoted to commodity exports. Vendease abandoned its warehouses. The Wasoko-MaxAB merger, positioned as Africa’s largest B2B tech consolidation, has already seen a co-founder exit and a competition inquiry opened. The sector is not suffering from bad luck or bad timing. It is working through the consequences of demand figures that were never built to reflect what the market would actually do.

The opportunity itself is real. Nigeria’s FMCG distribution chain still carries more hands than it needs. The margin spread still exists for whoever can capture it with a cost base the market can support. A lighter model — one that aggregates demand through low-cost digital touchpoints, partners with existing distributors rather than replacing them, and makes its money on the working capital credit relationship rather than the delivery fee — can work. Several operators are quietly finding this out.

Getting there requires building the demand assessment before the infrastructure — and that principle holds well beyond B2B commerce. A solar home system operator sizing rural household demand, an agri-input platform counting smallholder farmers, a logistics network mapping last-mile coverage: each faces the same prior question. Of the total count, how many units — outlets, households, farmers, endpoints — will actually behave the way the model requires? What does the convertible subset look like when the optimistic assumptions are removed? And is that number, honestly arrived at, sufficient to justify the fixed cost base being considered? The capital instrument question follows the same logic. Patient equity for the experimental phase, revenue-based financing once a credit book or recurring revenue stream is demonstrated, expansion capital only after unit economics hold at the first cluster. The sequencing is not sector-specific. It is the difference between a venture designed around what the market will do and one designed around what the projections need it to do.

The Population Illusion and the $10 Customer Problem essays cover the demand-assessment methodology behind this framing in full. Both are in the archive.