Gopuff Dataset
Live and Historical Data for Teams Tracking America’s Largest Instant-Delivery Convenience Platform
Gopuff built its business on a simple bet: people will pay for speed on the small, forgettable purchases — a bag of chips at midnight, ibuprofen at 6 a.m., a phone charger before a flight. That bet only works because Gopuff owns its own micro-fulfillment centers instead of relying on marketplace sellers, which means pricing, assortment, and stock status are controlled centrally but still vary quite a bit from one metro to the next. A SKU that’s a bestseller in Chicago might not even be stocked in Austin, and the price on a case of energy drinks can shift several times in a week depending on local demand and supplier cost.
That’s a genuinely different data problem than tracking a marketplace like Amazon or Flipkart, which is why we run a dedicated Gopuff Data Scraping pipeline rather than repurposing a generic ecommerce crawler. The output is a Gopuff Retail Product Dataset that captures pricing, listings, reviews, and fulfillment-center-level availability together, refreshed on whatever cycle your team needs. It runs on the same infrastructure behind our Quick Commerce Data Scraping services and sits alongside our broader Quick Commerce Dataset catalog, with custom builds available through our Web Scraping Services team.
Request Free Sample DatasetQuick Stats
Price From
$179Starting Price
Records
2.3M+Total Records
Format
CSV / JSONDelivery Format
Delivery
ImmediateAvailability
13+
Categories Covered
2+ Yrs
Historical Depth
Major Metros
US City Coverage
Daily
Refresh Cycle
Why Teams Choose Our Gopuff Dataset Over a DIY Crawl
Gopuff’s app doesn’t behave like a typical online store — pricing and even product availability can differ by delivery zone, and a fair amount of the catalog rotates in and out based on local micro-fulfillment-center stock rather than a single national inventory feed. That’s exactly the kind of thing a generic scraper tends to get wrong.
One Schema Across Every Field
Product name, SKU, brand, price, rating, and fulfillment-center stock status all arrive in a single Gopuff product dataset — no merging four exports by hand.
Zone-Level Precision
Because Gopuff’s assortment and pricing vary by delivery zone, our Gopuff product listings dataset tracks category placement and pricing at that same granular level rather than averaging it away.
Scoped to What You Actually Need
Pull specific categories or the full catalog, refresh daily, weekly, or near-live, and receive it as CSV, JSON, Excel, or a direct API feed.
Formats Your Tools Already Read
CSV and Excel exports work straight in Power BI or Tableau. JSON and API feeds ship with a documented schema for Snowflake, BigQuery, or Redshift.
Live Pricing, Plus a Real History
See today’s price next to 2+ years of historical price and rank movement, which matters more than usual in a category where prices change fast and often.
Built Around Micro-Fulfillment Reality
Coverage tracks stock at the fulfillment-center level, not just a generic app-wide “in stock” flag that hides local stock-outs.
What’s Actually Inside the Gopuff Dataset
The Gopuff dataset breaks down into four practical questions: what’s on the app, what it costs right now, what customers think of it, and whether it’s actually deliverable in a given zone. Those four questions map to the four sub-datasets described below, and they’re all keyed together so you’re not reconciling four separate exports.
Most of our clients start with pricing, usually because they’re chasing a specific question — is a competitor’s convenience-delivery pricing undercutting theirs in a particular city, or is Gopuff’s own promotional pricing eating into category margin faster than expected? CPG brands lean on the review layer to catch packaging or freshness complaints before they show up in return-adjacent metrics (quick-commerce doesn’t really have traditional returns, but repeat-order drop-off tells a similar story). Data teams mostly just want structured, timestamped records instead of raw app-response JSON, which is really the whole value proposition here. This dataset shares its collection standards with our broader Quick Commerce Dataset catalog.
What people actually build with this dataset:
- Pricing-policy checks: Compare live Gopuff pricing against your MAP or RRP floor across the metros where it operates.
- Zone-by-zone competitive tracking: Watch how pricing and assortment differ between delivery zones instead of assuming one national price applies everywhere.
- Promotional-cycle analysis: Build a historical record of Gopuff’s bundle deals and flash promotions to plan around them.
- Repricing automation: Feed same-day price signals from the Gopuff price dataset into your own repricing logic.
- Category and freshness research: Mine the Gopuff Customer Reviews Dataset for recurring complaints about packaging, delivery condition, or product freshness.
Key Metrics
Price
$179.00Format
CSV / JSON / APIRecords
2.3M+ Verified RecordsCoverage
United StatesUpdate Frequency
DailyAvailability
Instant AccessDelivery Time
ImmediatelyPreview actual dataset structure before purchase.
A Sample of the Gopuff Dataset
Below is a small, illustrative slice of a single extract. Each row is one SKU captured at a point in time — the full dataset carries 45+ additional fields, including fulfillment-center ID, bundle-deal flags, and full price-history timestamps.
| Product ID | Product Name | Price | Brand Name | Product Size | Product URL | Product Image |
|---|---|---|---|---|---|---|
| p487 | Slim Jim Original Giant Smoked Meat Stick | $2.49 | Slim Jim | 0.97oz | https://www.gopuff.com/p/slim-jim-original-giant-smoked-meat-stick-0-97oz/p487 | https://images.gopuff.com/blob/gopuffcatalogstorageprod/catalog-images-container/resize/cf/version=1_2,format=auto,fit=scale-down,width=800,height=800/09c13ab3-6d44-4c4c-ab8d-6d62712fb8ba.png |
| p101659 | OREO Original Chocolate Sandwich Cookies | $6.99 | OREO | 13.29oz | https://www.gopuff.com/p/oreo-original-chocolate-sandwich-cookies-13-29oz/p101659 | https://images.gopuff.com/blob/gopuffcatalogstorageprod/catalog-images-container/resize/cf/version=1_2,format=auto,fit=scale-down,width=800,height=800/bb303b95-319f-4955-a0a4-966ab41d49f2.png |
| p13622 | Doritos Nacho Cheese Tortilla Chips | $5.99 | Doritos | 9.25oz | https://www.gopuff.com/p/doritos-nacho-cheese-tortilla-chips-9-25oz/p13622 | https://images.gopuff.com/blob/gopuffcatalogstorageprod/catalog-images-container/resize/cf/version=1_2,format=auto,fit=scale-down,width=800,height=800/e1521a5e-e1f7-48b8-901e-fa7ce1fc113f.png |
| p19397 | Hostess Donettes Powdered Mini Donuts Bag | $4.49 | Hostess | 10oz | https://www.gopuff.com/p/hostess-donettes-powdered-mini-donuts-bag-10oz/p19397 | https://images.gopuff.com/blob/gopuffcatalogstorageprod/catalog-images-container/resize/cf/version=1_2,format=auto,fit=scale-down,width=800,height=800/d102619b-5abf-42d2-9b4d-cc7a9ae200b8-background_removed.png |
| p1428 | Premium Original Saltine Crackers | $4.59 | Premium | 16oz | https://www.gopuff.com/p/premium-original-saltine-crackers-16oz/p1428 | https://images.gopuff.com/blob/gopuffcatalogstorageprod/catalog-images-container/resize/cf/version=1_2,format=auto,fit=scale-down,width=800,height=800/db82d67c-d890-44ed-a251-681ec053f07a.png |
| p1006 | Chips Ahoy! Original Chocolate Chip Cookies | $5.49 | Chips Ahoy! | 13oz | https://www.gopuff.com/p/chips-ahoy-original-chocolate-chip-cookies-13oz/p1006 | https://images.gopuff.com/blob/gopuffcatalogstorageprod/catalog-images-container/resize/cf/version=1_2,format=auto,fit=scale-down,width=800,height=800/b092d52d-f274-4be6-867c-1c32e29dc8f8-background_removed.png |
| p68521 | Basically 3ct Microwave Extra Butter Popcorn | $4.19 | Basically | 2.75oz · 3 | https://www.gopuff.com/p/basically-3ct-microwave-extra-butter-popcorn/p68521 | https://images.gopuff.com/blob/gopuffcatalogstorageprod/catalog-images-container/resize/cf/version=1_2,format=auto,fit=scale-down,width=800,height=800/923474d9-8bcb-4130-a57b-b82990a9411d.png |
| p7123 | Reese's Peanut Butter Cups King Size | $3.99 | Reese's | 2.8oz | https://www.gopuff.com/p/reese-s-peanut-butter-cups-king-size-2-8oz/p7123 | https://images.gopuff.com/blob/gopuffcatalogstorageprod/catalog-images-container/resize/cf/version=1_2,format=auto,fit=scale-down,width=800,height=800/da98aa6f-1f6c-4d33-bdd1-57effab131f5.png |
| p276673 | Crave Shoppe Glazed Donuts | $7.99 | Crave Shoppe | 6ct | https://www.gopuff.com/p/crave-shoppe-glazed-donuts---6ct/p276673 | https://images.gopuff.com/blob/gopuffcatalogstorageprod/catalog-images-container/resize/cf/version=1_2,format=auto,fit=scale-down,width=800,height=800/bf268125-6452-4731-ae60-5b6b037ccf9b.png |
| p13617 | Cheetos Puffs | $5.79 | Cheetos | 8oz | https://www.gopuff.com/p/cheetos-puffs-8oz/p13617 | https://images.gopuff.com/blob/gopuffcatalogstorageprod/catalog-images-container/resize/cf/version=1_2,format=auto,fit=scale-down,width=800,height=800/7765e466-a98e-4756-8e11-aaa85acae3ab.png |
The Four Layers of the Gopuff Dataset
Rather than one flat export, the Gopuff dataset splits into four connected layers, licensed individually or together, joined on a common product key.
Gopuff Product Listings Dataset
The descriptive layer behind every item on the app — what it is, how it’s categorized, and how it’s presented to the shopper.
- Product name, category and sub-category placement, brand, and SKU identifiers
- Description text, pack-size and quantity details, and flavor/variant attributes
- Primary and gallery image URLs
- Bundle and multi-buy configuration where applicable
Gopuff Price Dataset
Pricing here moves faster and more locally than most retail categories — bundle deals, flash discounts, and zone-specific promotions all shift the number a shopper actually sees.
- Current price, was-price, discount percentage, and bundle/multi-buy pricing
- Full price-change history with timestamps, tracked by delivery zone where pricing differs
- Promotional badges (flash deal, bundle discount, first-order pricing) tied to their active window
- Delivery-fee and minimum-order-threshold data by zone
Gopuff Retail Product Dataset (Fulfillment-Center Layer)
Because Gopuff runs its own micro-fulfillment centers rather than a marketplace-seller model, knowing what’s actually stocked in a given local facility matters more here than on most platforms.
- Fulfillment-center-level stock status: in stock, limited stock, or out of stock
- Category and sub-category assortment differences between delivery zones
- Featured or promoted-placement flags within the app’s browsing categories
- Historical stock-status trends to spot recurring local shortages or seasonal patterns
Gopuff Customer Reviews Dataset
Because delivery condition and speed matter as much as the product itself in quick-commerce, review sentiment here often tells a different story than star ratings alone.
- Individual reviews with star rating, title, review text, and submission date
- Verified-order flag and anonymized reviewer identifier
- Aspect-level sentiment: product freshness, packaging condition, delivery speed, and order accuracy
- Rating distribution and week-over-week review velocity trends
Where the Gopuff Dataset Runs Deepest
Gopuff’s catalog is built around impulse and convenience rather than planned grocery runs, so our coverage focuses on the categories where that behavior shows up most.
Snacks & Beverages
The highest SKU velocity on the platform, with frequent bundle-deal and price-cycle activity.
OTC Health & Wellness
Late-night and emergency-purchase pricing tracked separately from planned-purchase categories.
Alcohol
Region-specific availability tracking, reflecting how alcohol delivery varies by local regulation.
Baby & Household Essentials
High-frequency reorder categories where stock-outs matter more than in discretionary purchases.
Add-Ons
zone-by-zone price-differential mapping, bundle-deal historical archives, and delivery-fee/minimum-order tracking by metro.
How Different Teams Put This Dataset to Work
The same dataset ends up solving fairly different problems depending on who’s using it.
Competitive Price Monitoring
Track how competitor products priced on Gopuff move week to week, instead of manually checking the app across multiple cities.
Dynamic Repricing
Feed live signals from the Gopuff price dataset directly into your own repricing logic to react to promotional cycles as they happen.
Quick-Commerce Market Research
Use multi-year price and rank history to understand how the instant-delivery convenience category is evolving city by city.
Demand Forecasting
Build forecasting models on top of 2+ years of price, stock, and review-velocity data to anticipate demand spikes around holidays and local events.
AI and LLM Training Data
Use the clean, labeled Gopuff product listings dataset as training data for product-attribute extraction and recommendation models.
Catalog Benchmarking
Compare listing quality — image count, description depth, variant coverage — against how Gopuff presents comparable products.
Who Actually Uses the Gopuff Dataset
The Gopuff Dataset provides insights into product listings, pricing, inventory availability, promotions, and consumer purchasing trends, enabling businesses to optimize pricing strategies, monitor competitors, identify market opportunities, and make informed decisions in the on-demand delivery and quick-commerce industry.
CPG & Beverage Brands
Track how their products are priced and positioned on Gopuff relative to convenience-store and grocery channels.
Quick-Commerce Competitors
Benchmark pricing and assortment strategy against one of the category’s largest US players.
AI & ML Companies
Source structured US quick-commerce data for pricing models and demand-forecasting engines.
Market Research Firms
Build category reports on instant-delivery convenience retail using multi-year historical depth.
Retail Consulting Firms
Validate assortment and zone-pricing strategy recommendations with verified, current data.
Investment & Analyst Teams
Use pricing behavior and category expansion as an alternative-data signal for the quick-commerce sector.
What This Dataset Actually Saves You
Manually tracking Gopuff pricing across multiple cities isn’t really feasible past a handful of SKUs, and it definitely won’t catch a zone-specific price change that only lasts a few hours.
Hours Back, Not Days
A structured feed replaces manual, city-by-city price-checking entirely — what used to take days is available on a schedule you set.
Forecasts Grounded in Real History
2+ years of price and rank data lets you separate genuine demand shifts from one-off promotional spikes.
Reacting in Hours, Not Weeks
Bundle deals and flash promotions move fast on quick-commerce apps. A same-day feed means you find out the same day it changes.
Built Around Your Pipeline, Not Ours
Pick the categories, metros, and cadence that matter to you — delivered as CSV, JSON, API, or Parquet.
How the Gopuff Data Scraping Pipeline Actually Works
Here’s the straightforward version of how this gets built, not a marketing summary of it.
Collection Approach
Ethical, rate-limited collection from Gopuff’s publicly visible pages — no credential bypass, no access to restricted internal APIs.
Validation Before Delivery
Every batch runs through automated schema checks, then a manual spot-check pass before it ships.
Deduplication
Repeat pulls of the same SKU are collapsed into one clean historical record instead of duplicate rows.
Refresh Scheduling
Daily, weekly, or intraday cycles keep pricing and stock fields current without you having to request a re-pull.
Stable Schema
Field names and structure stay consistent release over release, so your ingestion pipeline doesn’t break on the next refresh.
Compliance
Only publicly available data is collected, consistent with standard commercial data practice and platform terms.
This methodology is the same one behind our Quick Commerce Data Scraping services more broadly — Gopuff Data Scraping is a maintained pipeline, not a one-off project.
Delivered However Your Stack Expects It
Access the Gopuff Dataset in your preferred format with flexible delivery options that integrate seamlessly into your existing workflows and technology stack.
CSV / Excel
Drop straight into Excel pricing models, Tableau dashboards, or Power BI reports.
JSON / API Feed
Documented schema, ready for direct ingestion into your application backend or data pipeline.
Cloud Storage / Database
Automated delivery to S3, SFTP, Snowflake, BigQuery, or Redshift on whatever cadence you set.
Pick the Plan That Matches Your Scope
Choose from flexible Gopuff Dataset pricing plans designed to match your business needs, data volume, update frequency, and scalability requirements. Access reliable Gopuff product, pricing, inventory, and promotional data to support competitive analysis, market research, and business growth.
One-Time Dataset Purchase
From $179
A one-time Gopuff dataset snapshot, delivered right away — no subscription commitment.
What’s included:
- Full point-in-time dataset snapshot
- CSV, JSON, or Parquet delivery
- Filter by category and metro before delivery
Enterprise License
Contact Sales
Full-category, multi-metro coverage with unlimited access and an SLA behind it.
What’s included:
- Unlimited API calls and delivery volume
- Dedicated account manager, 99.5% SLA
- Custom schema design and white-label delivery
A Team That’s Actually Built This Before
Trusted Gopuff Dataset solutions powered by accurate product, pricing, and inventory data to help businesses make smarter, data-driven decisions.
Track Record at Scale
Millions of verified records collected and refreshed continuously across major US quick-commerce and ecommerce platforms — Gopuff is one of several, not a one-off build.
Support That Doesn’t Disappear After Launch
Dedicated account management, SLA-backed delivery, and proactive alerts if a schema ever needs to change.
Compliance-First, By Default
Only publicly accessible data is collected — no credential bypass, no restricted-API workarounds.
Custom Builds When You Need Them
Need a field, category, or metro we haven’t listed here? We build custom Gopuff dataset configurations on request.
Questions People Actually Ask Us About the Gopuff Dataset
These come from real conversations with brands, analysts, and engineering teams evaluating this dataset.
It’s a structured export of Gopuff’s retail data — product listings, pricing, micro-fulfillment-center availability, and customer reviews — cleaned, deduplicated, and delivered as CSV, JSON, or an API feed through our Gopuff Data Scraping pipeline.
CSV, Excel (XLS/XLSX), JSON, and API feeds by default. Parquet is available on request for Spark, Databricks, Snowflake, or BigQuery pipelines.
Pricing and stock fields can refresh intraday on enterprise plans, since promotional pricing and local stock levels change quickly. Listings update daily, and reviews update on a rolling basis.
Yes — tell us the categories, metros, fields, and refresh cadence, and we build the extract around that scope rather than delivering a generic full export.
Yes, more than two years of historical pricing, including current price, was-price, and discount timestamps — useful for spotting real demand trends versus one-off promotions.
Yes. The Gopuff price and retail product datasets track SKU-level pricing over time, so you can flag when a listing drops below your policy floor without manual checking.
Yes. Because Gopuff’s assortment and pricing differ across delivery zones and fulfillment centers, the dataset tracks availability and price at that granular level rather than showing one national average.
Yes. Only publicly visible pages on Gopuff’s platform are collected, using rate-limited, ethical methods. We don’t bypass logins or access restricted internal APIs.
A DIY scrape typically returns inconsistent, messy data that needs significant cleanup. This dataset is already normalized, deduplicated, and schema-stable, ready for analysis the same day it arrives.
Yes, where publicly listed. Availability for these categories can vary by region due to local regulation, and that variation is reflected in the fulfillment-center layer of the dataset.
Mostly CPG and beverage brands, competing quick-commerce platforms, market research firms, AI/ML teams, retail consultants, and investment analysts tracking the instant-delivery sector.
Yes — automated delivery to S3, SFTP, Snowflake, BigQuery, or Redshift on whatever schedule you choose.
Get a Real Look at Gopuff’s Quick-Commerce Data
2.3M+ verified records, daily pricing refreshes, and 2+ years of historical depth across America’s leading instant-delivery platform — starting at $179.