US quick commerce promises convenience, but it comes at a price - and that price is not the same on every platform or in every metro. The same basket can cost noticeably more on one app than another, before fees even enter the picture.
This report compares Instacart and Amazon Fresh on basket pricing, platform markup over in-store shelf prices, fees, and metro coverage, using publicly available data. It is written for brands, CPG teams and app builders who need the full quick-commerce picture, not one platform.
Key findings at a glance
Three patterns stand out across the data. (Figures below are illustrative previews - the full report breaks them down by category, platform and metro.)
Key finding 1: platform markup over shelf is the real story
Both platforms price above in-store shelf, but by different amounts - and that markup, not the headline price, is what shapes a shopper's true cost. Ignoring it makes quick commerce look cheaper than it is.
The gap widens once service and delivery fees are layered on, which is why a credible comparison captures item price, markup and fees as separate fields rather than a single blended number.
Key finding 2: coverage varies sharply by metro
Pricing only matters where a platform actually operates. Coverage and availability differ by metro, and the cheaper platform is irrelevant if it does not serve a given ZIP. The sample shows coverage by metro (illustrative).
| Metro | Instacart | Amazon Fresh | Cheaper basket |
|---|---|---|---|
| New York | Full | Full | Amazon Fresh |
| Chicago | Full | Partial | Instacart |
| Dallas | Full | Partial | Amazon Fresh |
| Rural avg | Partial | Limited | Instacart |
Amazon Fresh tends to be deeper in dense metros, Instacart broader across partial-coverage areas - so the right platform depends on where the shopper is.
Key finding 3: fees and categories swing the total
The basket index is only part of the cost. Service fees, delivery fees and category mix (fresh vs packaged) move the effective total meaningfully, and they differ by platform. A shopper optimizing for total cost needs price, markup and fees together - which is precisely what a structured quick-commerce feed provides.
What the underlying data looks like
The report is built from records like the one below - the structure buyers receive in a sample.
{
"platform": "Instacart",
"retailer": "Example Market",
"zip_code": "10001",
"item": "Whole Milk, 1 Gallon",
"platform_price": 4.29,
"shelf_price_ref": 3.49,
"markup_pct": 22.9,
"service_fee_est": 3.99,
"eta_minutes": 60,
"captured_at": "2026-06-29T11:00:00Z"
}
Aggregated to a platform-and-metro view, the same data rolls up into a flat file analysts can model on:
metro,platform,basket_index,markup_pct,coverage
New York,Instacart,118,18,full
New York,Amazon Fresh,108,8,full
Chicago,Instacart,116,16,full
Chicago,Amazon Fresh,110,10,partial
Who this report is for
This report is built for the teams that compete or sell in US quick commerce.
- Same-basket price index by platform
- Platform markup over in-store shelf
- Fees and category-mix effects
- Coverage by metro and density
- Complete methodology, sample size and sources
Methodology & data
The findings are based on publicly available pricing and availability collected across Instacart and Amazon Fresh by location in 2026, with platform prices compared to in-store shelf references and normalised to a basket index by metro. No personal data is involved. The full report details the platforms, categories, metros and how each metric is calculated.
The numbers and charts shown on this page are illustrative previews of the kind of analysis in the report. They are based on publicly available, non-personal web data in aggregate and do not represent any single named company. The full report contains the complete dataset, methodology and sources.
Frequently asked questions
Yes. Enter your details and we will email you the PDF.
Instacart and Amazon Fresh, on a standardized basket, by metro, using publicly available data.
They are illustrative previews of the report's analysis. The full PDF contains the complete dataset, methodology and sources.
Yes. Item price, markup over shelf, and fees are captured as separate fields so the effective total is clear.
Yes. Our quick-commerce intelligence solution delivers platform pricing and coverage for your categories and markets as an ongoing feed.