More Revenue Is Concentrating in Fewer, Larger Catalogs
Stores that cross R$200,000 in monthly revenue make up only 1.5% of Brazil's active online shops, yet they capture 48% of monthly revenue and 63% of annual growth, according to Nuvemshop's June 2026 Radar do E-commerce D2C, based on more than 96,000 active stores [2]. That growth gap is a central argument for SKU rationalization as catalogs scale.
The gap is not just about size: the table below shows how far that top tier has pulled ahead of smaller stores on growth and average ticket. Larger stores are also far more likely to run free-shipping rules and sell through an integrated physical location, both of which add branching logic to every SKU decision [2].
As catalogs scale into this tier, the number of SKUs tends to scale with them, often faster than the systems and processes built to manage them.
| Segment | Share of active stores | Share of monthly revenue | YoY revenue growth | Average ticket |
|---|---|---|---|---|
| Over R$200k/month | 1.5% [2] | 48% [2] | 69% [2] | R$336 [2] |
| Under R$100k/month | n/a | n/a | 26% [2] | R$231 [2] |
Is SKU Rationalization Just Cutting SKUs?
A wider catalog is not automatically a competitive advantage: in fashion, accessories and beauty, it is common to run operations with hundreds or thousands of SKUs added continuously as new collections launch, without a matching review of older products [1]. The real question most retailers skip is how many of those SKUs actually move the business forward.
Unchecked catalog growth creates a specific kind of drag. Each new purchase order ties up more capital and adds operational complexity, while slow-moving items keep occupying space that could serve better sellers, who in turn face stockouts [1].
The paradox of choice compounds the problem: when shoppers face many similar options without strong filtering, comparison tools or curation, the extra choice raises cognitive effort and can delay or kill the purchase decision [1].
SKU rationalization isn't about cutting indiscriminately. It means replacing instinct with a productivity view of every item already on the site.
An ABC Curve Alone Hides as Much as It Reveals
A revenue-only ranking of SKUs is a starting point, not an answer: a product can sell heavily while carrying thin margin, while another with modest revenue share can anchor order value or profitability in ways a simple ABC curve won't show [1].
The indicators that matter most, used together, are:
A product with 60 to 90 days without a sale deserves investigation, but not automatic removal, since seasonality, limited exposure, missing size variants or weak content can all explain a cold streak that has nothing to do with real demand [1].
- Revenue: how much each SKU represents in total sales.
- Contribution margin: what remains after variable costs.
- Inventory turnover: how fast the product actually sells.
- Stock coverage: how long current inventory can meet demand.
- Stockout rate: how many sales opportunities are lost to unavailability.
- Sales history: performance over time, including seasonality and campaign effects.
A Three-Tier Model for Managing What Stays, Grows, or Gets Tested
Rather than treating every SKU the same, retailers can split the catalog into three groups with different buying, content and marketing rules [1].
This structure also changes how media budgets get allocated. A catalog of hundreds of items does not mean every item deserves equal ad spend: campaigns can split deliberately between best-sellers, a target category and new tests, instead of distributing budget by catalog size alone [1].
- 1Validated products: items with a consistent sales history and strong commercial indicators, which merit priority in restocking, content and acquisition campaigns.
- 2Expansion products: items that broaden the assortment, support combinations, or build out a strategic category, often lifting average order value.
- 3Experimental products: new items without enough history to justify large purchase volumes, introduced in controlled quantities alongside tests of messaging and acceptance.
Marketplace Concentration Raises the Stakes for Curation
Curation matters more when discovery itself is concentrated: Mercado Livre and Shopee together account for 66% of traffic among Brazil's largest e-commerce sites, according to a Similarweb and Snaq survey of the third quarter [3].
That concentration raises the cost of listing products without a clear productivity signal attached. A SKU that is hard to filter, poorly described or missing from a platform's ranking logic loses visibility in exactly the channels that carry most of the traffic. Catalog governance stops being a back-office exercise and becomes a visibility strategy.
What This Means for Commerce and Platform Teams
SKU-level productivity data only helps if the systems behind the storefront can act on it in real time: syncing stock by location, updating margin signals and reflecting coverage and stockout risk before a shopper hits a sold-out product page. As catalogs scale past the complexity threshold described above, platform decisions increasingly hinge on that operational layer rather than storefront appearance [2].
Commerce, IT and merchandising teams evaluating a catalog strategy should treat the three-tier model and the multi-indicator scoring as a joint exercise between merchandising and the platform team, not a spreadsheet exercise run in isolation. The data only creates value when it flows back into buying, content and media decisions on a regular cycle rather than once a season.
Sources
- [1]E-Commerce Brasil, Menos SKUs, mais estratégia: o desafio de transformar variedade em vendas no e-commerce — ecommercebrasil.com.br
- [2]E-Commerce Brasil, Plataforma para operações complexas: o que avaliar além da vitrine — ecommercebrasil.com.br
- [3]E-Commerce Brasil, Mercado Livre e Shopee concentram 66% do tráfego dos grandes e-commerces — ecommercebrasil.com.br
