US Food-Delivery and Grocery Data Research
Planning research around Postmates-visible restaurants, menus, item prices, grocery products or delivery availability?
NenoData helps teams define location-aware dataset requirements and assess authorized source-access options. Postmates-specific field coverage, collection methods, refresh frequency and delivery arrangements must be confirmed before a production project can be agreed.
Qualified project assessment. No claim of an existing Postmates feed or official Uber API integration.
Postmates data scraping services, as discussed here, concern planning and assessing structured datasets from appropriately authorized Postmates-related information sources.
For restaurant chains, grocery retailers and pricing teams, useful observations go beyond a merchant name or displayed price. They need to identify the product or menu item, the location and ordering context, and the time at which information was observed.
This page explains what a potential Postmates dataset could contain, how restaurant and grocery records differ, and which source-access questions must be answered first.
It does not represent NenoData as operating a ready-made Postmates scraper, maintaining a production dataset or possessing official Uber/Postmates credentials.
See also: Uber Eats Data Scraping Services · Food Delivery App Scraping
Postmates is part of Uber. Uber announced completion of its acquisition in December 2020 and stated that Postmates and Uber Eats would continue as separate consumer-facing apps supported by an integrated merchant and delivery network.
This matters for research design. A Postmates-branded observation should be attributed to the consumer experience in which it was made, but buyers should not assume the two brands represent entirely independent restaurant networks or data infrastructure.
NenoData already has an Uber Eats Data Scraping Services page for Uber Eats-specific requirements. The proposed Postmates page is intended for Postmates-branded US observations, including grocery requirements where scoped—not a duplicate Uber Eats page.
US consumer-facing brand
Restaurants · Grocery · Retail
Separate consumer-facing brand
Distinct observations required
Overlapping merchant network — each dataset record must be attributed to the consumer-facing brand, location and observation time in which it was made.
The following are candidate fields, not a verified inventory of NenoData's Postmates extraction capabilities.
| Data category | Proposed fields | Qualification |
|---|---|---|
| Merchant identity | Name, source identifier, merchant reference | Confirm against approved source |
| Restaurant profile | Address, category, cuisine | Where publicly visible or otherwise authorized |
| Geographic context | US city, ZIP code, location input | Preserve search context |
| Menu overview | Menu and category references | Requires menu-level review |
| Pricing | Listed USD prices and visible promotions | Observation-specific |
| Service context | Delivery or pickup status, displayed ETA | Do not confuse estimates with actual fulfillment |
| Provenance | Source reference, brand, timestamp, validation status | Include in agreed schema |
A merchant appearing in more than one location search should not automatically be counted as a separate business each time.
A restaurant menu is hierarchical. Its data model should retain the relationship between categories, items and selectable options:
Merchant → Menu → Category → Item → Modifier group → Modifier option
| Menu component | Candidate attributes |
|---|---|
| Category | Name, source identifier, display order |
| Item | Name, description, item reference |
| Base price | Displayed USD amount |
| Modifier group | Size, preparation choice or add-on group |
| Modifier option | Name, additional price, selection condition |
| Availability | Visible status at observation time |
A modifier price should not be mistaken for the base price. Similarly, a menu listing does not guarantee that every option, condition or item status is visible through an approved source. The final hierarchy and field coverage require representative, authorized feasibility review.
See also: Restaurant Menu Data Scraping.
For Postmates pricing research, distinguish what the customer sees at different stages of an order.
| Price component | Dataset treatment |
|---|---|
| Base item price | Store separately from optional additions |
| Modifier or add-on | Preserve its relationship to the parent item |
| Promotion | Record displayed terms and observation context |
| Delivery fee | Keep separate from menu-item price |
| Other visible charges | Identify the charge type rather than merging values |
| ETA | Record as a displayed estimate, not actual delivery performance |
| Timestamp | Associate with the source observation |
Comparisons should use the same item configuration and a comparable location context. A base-price difference is not necessarily a difference in final basket cost. No fixed Postmates price-monitoring frequency is established by this page.
Postmates' consumer-facing proposition includes grocery and other retail delivery, alongside restaurant food. Grocery data should not be forced into a restaurant-menu schema.
| Grocery category | Candidate fields |
|---|---|
| Product identity | Product name, brand, source identifier |
| Classification | Category and description |
| Packaging | Size, quantity and unit |
| Price | Displayed USD amount, unit price where visible |
| Promotion | Visible offer and conditions |
| Availability | Location-specific displayed status |
| Provenance | Merchant, location input and observation time |
For example, two packages with different weights should not be matched solely because they have similar product names. Grocery catalogue depth, product availability and permitted collection methods must be verified separately from restaurant-menu feasibility.
See also: Grocery Delivery App Scraping for general grocery schema conventions.
Aggregate ratings, review counts and individual review text are different data types.
| Potential field | Required qualification |
|---|---|
| Aggregate rating | Only where displayed and within approved scope |
| Review count | Preserve the source's visible count and observation time |
| Individual review text | Requires separate visibility, rights and privacy review |
| Review author information | Exclude personal information unless a separate appropriate basis exists |
A visible rating does not establish that the underlying review text is accessible or reusable. A review count should not be represented as a count of records collected by NenoData. No universal Postmates review coverage is promised.
Postmates observations should preserve the delivery location or other agreed location key, merchant identity, ordering method and observation timestamp.
A restaurant or product missing from one ZIP-code search should not automatically be labelled permanently unavailable. Likewise, an estimated arrival time is not evidence of an actual completed delivery duration.
For multi-location projects, the proposed dataset should distinguish a merchant's identity from each location-specific appearance. Coverage across US cities, ZIP codes or delivery addresses is subject to source access and feasibility testing.
Uber's official Eats Marketplace APIs are intended for approved partner activities such as store management, menu synchronization and order processing. Its documentation describes OAuth 2.0 authentication, endpoint-specific scopes and production approval requirements. These are distinct from an unrestricted public interface for collecting competitors' Postmates menus, grocery catalogues, reviews or prices.
| Access model | Purpose | Qualification |
|---|---|---|
| Official Uber Marketplace API | Approved merchant and integration workflows | Requires applicable authorization and scopes |
| Authorized source access | Access permitted for an agreed research purpose | Must be established |
| Managed data collection | Source-specific collection under approved scope | Not verified as operational for Postmates |
| NenoData output API | Structured delivery to a buyer's downstream system | General service only; Postmates-specific delivery unverified |
An output API does not confer rights to access the underlying platform. Nor does an existing Uber Eats integration imply Postmates-wide competitive research access. The applicable Uber/Postmates agreements, collection permissions, intended commercial use and redistribution rights must be reviewed before operational work. See also NenoData's Web Scraping API Services.
A useful specification separates merchants, menu items, grocery products and observations.
| Entity | Proposed fields |
|---|---|
| Merchant | merchant_id, name, brand context, category, location |
| Menu item | Merchant reference, category, item name, base price, modifier group |
| Grocery product | Merchant reference, product name, brand, size, listed price |
| Observation | Location key, service type, availability, observed time |
| Provenance | Source reference, collection scope and validation status |
Illustrative schema only—not a genuine Postmates record:
{
"source": "illustrative-delivery-source",
"consumer_brand": "illustrative",
"merchant": {
"merchant_id": null,
"name": "Example Merchant",
"category": null
},
"record_type": "menu_item",
"item": {
"name": "Example Item",
"base_price_usd": null,
"modifier_groups": []
},
"observation": {
"location_key": null,
"service_type": "delivery",
"listed_price_usd": null,
"availability": null,
"observed_at": null
},
"source_reference": null,
"validation_status": "illustrative_only"
}The example defines a possible data contract. It is not evidence of an existing feed, confirmed fields or a working Postmates endpoint.
Real-time API synchronization, recurring price observations and historical datasets are not interchangeable.
| Model | Meaning | Postmates-specific status |
|---|---|---|
| One-time dataset | A defined set of timestamped observations | Not verified as an existing inventory |
| Scheduled collection | Repeated observations at an agreed interval | Subject to authorization and feasibility |
| On-demand collection | Collection initiated by an agreed request | Not established |
| Real-time feed | Operational freshness under defined latency expectations | Not verified |
Uber's official merchant APIs may support real-time operational synchronization for approved integrations. That does not establish a real-time Postmates competitive-intelligence feed. Where recurring observations are authorized, the dataset should retain source observation time separately from delivery time where relevant.
NenoData's existing Uber Eats, food-delivery, grocery and API service pages describe general scoped data workflows, including field planning, representative feasibility checks, validation and structured delivery. The Postmates-specific application of that methodology remains conditional.
Define the requirement
Identify target US markets, brand-specific observations, restaurant or grocery fields, intended use and delivery preferences.
Establish access rights
Review the relevant platform agreements, authorization, permitted collection methods and commercial reuse requirements.
Assess fields and schema
Where access is approved, evaluate representative records, menu hierarchy, grocery matching, location context and missing values.
Confirm a delivery plan
Agree validated fields, format, cadence and operational responsibilities before making a production commitment.
Depending on the agreed service, general NenoData offerings discuss structured formats such as CSV, Excel, JSON and API-ready delivery. A Postmates-specific output arrangement must be confirmed separately. See also How It Works.
| Within this page's scope | Not established or promised |
|---|---|
| Postmates-branded US dataset planning | Independent global marketplace coverage |
| Restaurant and grocery schema design | Complete field or geographic coverage |
| Menu and pricing requirements | Existing production Postmates dataset |
| Ratings and review-field assessment | Universal individual review access |
| Official API clarification | NenoData Uber/Postmates API entitlement |
| Permission-based feasibility review | Unrestricted automated extraction |
| Potential monitoring requirements | Guaranteed real-time collection |
| Conceptual output schema | Genuine Postmates sample or production endpoint |
Private customer information, order histories, payment details and restricted account records are outside the proposed scope without an appropriate, separately established basis. Collection permission, commercial reuse and redistribution rights must be verified independently.
Tell NenoData which Postmates-branded restaurant, menu, grocery or pricing observations matter to your research.
Include the target US cities or ZIP codes, required fields, intended commercial use, existing source permissions, expected collection frequency and preferred output format. The team can discuss the appropriate authorization and feasibility review before confirming any source-specific delivery arrangement.
Related: Uber Eats Data Scraping Services · Food Delivery App Scraping · Restaurant Menu Data Scraping