Grocery Deals & Flyer Scraper for Flipp (US & Canada)

Grocery Deals & Flyer Scraper for Flipp — Weekly Ads, Online Deals, Prices & Discounts

A fast, no-code grocery deals & weekly flyer scraper for Flipp that turns any product search into a clean retail pricing dataset. Extract weekly-flyer circulars and online deals across thousands of US and Canadian supermarkets, pharmacies, and big-box retailers — including item name, current sale price, original "was" price, computed discount %, sale story promo text, merchant name & ID, validity dates, brand IDs, weight/size, and product images — localized to any US ZIP code or Canadian postal code. No login, no coding, and no browser overhead.

Export every deal to JSON, CSV, Excel, or API in seconds.

Built for retail and CPG competitive-intelligence teams, grocery price-tracking apps, coupon and deal-aggregation websites, inflation researchers, and smart-cart tools that need structured Flipp data on demand.

ℹ️ Disclaimer: This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Flipp Operations Inc. or any retailer featured in weekly circulars. "Flipp" and all related brand names and logos are trademarks of their respective owners and are used here strictly to describe the publicly available data source. Please use this Actor in compliance with Flipp's Terms of Service and applicable laws.

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⚡ At a glance

Feature	Details
Data source	Public weekly-flyer & online deal listings on Flipp (en-us United States & en-ca Canada)
Deal types extracted	Printed weekly-ad flyer deals (type: "flyer") and e-commerce offers (type: "online"), interleaved for balanced sampling
Core fields	name, currentPrice, originalPrice, discountPercent, saleStory, merchant, merchantId, validFrom, validTo, itemWeight, imageUrl
Online-only fields	description, sku, averageRating, totalReviews, shippingInfo
1,000+ results scale	Automatic grocery staple & category expansion when maxItems > 150 — delivers 1,000+ unique deals with 0 duplicates
Authentication	None required — no account, login, or API key needed
Proxy requirement	Standard Apify Proxy (Datacenter enabled by default — fast and low-cost)
Export formats	JSON, CSV, Excel (XLSX), HTML, XML, RSS, Key-Value Store OUTPUT, and REST API

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🔎 Why scrape Flipp grocery & flyer deals?

Flipp is North America's largest digital weekly-flyer and circular platform, aggregating weekly promotions and online deals from thousands of grocery chains, pharmacies, hardware stores, and big-box retailers across every US ZIP code and Canadian postal code. That makes it one of the richest public sources of localized retail pricing intelligence — showing current promotional prices, pre-sale "was" prices, loyalty-card requirements, multi-buy offers, and exact validity dates by store.

However, the web interface is designed for browsing one circular or one item at a time. There is no bulk CSV export, no way to compare the price of milk, eggs, coffee, chicken, and detergent across 40 local retailers simultaneously, and no historical archive once a weekly flyer expires.

This Flipp scraper automates the entire extraction pipeline. Supply your search terms and a postal/ZIP code, and the actor returns every matching named flyer item and online deal as a normalized, de-duplicated dataset ready for Excel, SQL, Power BI, or your application backend. Request maxItems: 1000+ and the scraper automatically expands across 40+ high-volume grocery and household staples to deliver 1,000+ unique deals in under a minute.

Common reasons teams use this Flipp data extractor:

• Retail & CPG competitive price monitoring — track weekly promotional pricing, discount depth, and feature frequency across competing supermarket chains by ZIP code.
• Consumer grocery price-comparison apps — power mobile or web apps that show shoppers the lowest local price for their weekly shopping list.
• Deal-aggregation, coupon & savings portals — populate localized deal feeds and email digests with verified weekly circular promotions and validity windows.
• Promotional & trade-spend intelligence — analyze saleStory, prePriceText, and postPriceText to measure loyalty-club discounts, BOGO offers, and digital coupons by brand (brandIds).
• Macroeconomic & food-inflation tracking — schedule weekly runs across representative US and Canadian postal codes to build longitudinal CPI and staple food price indices.

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✨ What this Flipp scraper does

• ✅ Search by product, brand, or category — pass any list of searchTerms (milk, eggs, coffee, chicken breast, diapers, laundry detergent, laptop, etc.). Leave searchTerms empty and the actor automatically runs a curated grocery staples sample so empty runs always succeed.
• ✅ Unlocked 1,000+ deals automatic expansion — because a single search term returns roughly 50–180 local deals, setting maxItems above 150 (e.g. 500 or 1,000+) automatically expands your query list across 40+ core grocery, produce, meat, dairy, beverage, and household categories until your target count is reached.
• ✅ Weekly flyer + online e-commerce deals — extracts both printed circular promotions (type: "flyer") and online retailer deals (type: "online"). Both streams are interleaved per search term so capped runs always include a balanced mix of local flyers and online offers.
• ✅ Image-only clipping filter — raw weekly circulars often contain unnamed visual clippings; the actor automatically filters out unnamed graphic slices so 100% of returned records have a clean product name.
• ✅ Computed discount percentages & sale stories — automatically calculates discountPercent whenever both currentPrice and originalPrice are available, while preserving promotional copy in saleStory (e.g. "SAVE 46%", "- $1.00 Digital Savings"), prePriceText, and postPriceText.
• ✅ Full merchant & circular provenance — includes merchant, merchantId, merchantLogo, flyerId, validFrom, and validTo ISO timestamps on every flyer deal.
• ✅ Zero duplicates — every deal is de-duplicated across search terms using a composite type:itemId key (resolving item_id, global_id, and sku for online listings).
• ✅ Bulk export JSON, CSV, Excel & sync API — writes records to the default Apify Dataset and mirrors { count, deals } to the Key-Value Store OUTPUT key for instant run-sync API consumers.

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🎯 Use cases

Industry / Team	How they leverage Flipp deal data
CPG Brand & Revenue Management	Monitor how regional grocers promote your SKUs (brandIds) versus rival brands across US & Canadian metro areas every week.
Supermarket & Retail Pricing Teams	Benchmark weekly circular loss-leaders (milk, eggs, meat, coffee, produce) against local competitors in specific ZIP codes.
Savings Apps & FinTech	Build automated "cheapest basket near you" calculators by matching user grocery lists against live currentPrice and merchant records.
Affiliate & Deal Publishers	Filter deals with discountPercent >= 30 and valid validTo dates to publish daily localized deal roundups.
Economic & Academic Researchers	Schedule weekly Monday runs across 50 US ZIP codes and Canadian forward sortation areas (FSAs) to track regional food price dispersion.

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📥 Input

All parameters are optional and prefilled with sensible defaults (milk, eggs, coffee in New York 10001).

Field	Type	Default / Prefill	Description
searchTerms	array<string>	Prefill: ["milk", "eggs", "coffee"]	Products, brands, or categories to search. Leave empty for a built-in grocery sample, or set maxItems: 1000+ to auto-expand across 40+ grocery staples.
postalCode	string	"10001"	5-digit US ZIP code (e.g. 10001, 90210, 60601) or 6-character Canadian postal code (e.g. M5V2T6, H2X1Y4).
locale	string (select)	"en-us"	en-us (United States) or en-ca (Canada). Match this to your postalCode country.
includeEcom	boolean	true	Include online/e-commerce deals (type: "online" with SKU, ratings, reviews, and shipping) alongside weekly flyer deals.
maxItems	integer	Default: 0 (Prefill: 100)	Maximum total deals to collect across all search terms (0 = unlimited). Setting > 150 enables automatic grocery category expansion.
proxyConfiguration	object	{ "useApifyProxy": true }	Apify Proxy configuration. Standard Datacenter proxy is enabled by default and works at full speed.

Example input — local US grocery price check

{
  "searchTerms": ["milk", "eggs", "coffee", "chicken", "cheese"],
  "postalCode": "10001",
  "locale": "en-us",
  "includeEcom": true,
  "maxItems": 250,
  "proxyConfiguration": { "useApifyProxy": true }
}

Example input — Canadian flyer sweep (1,000+ deals)

{
  "searchTerms": ["milk", "bread", "butter", "salmon", "apples"],
  "postalCode": "M5V2T6",
  "locale": "en-ca",
  "includeEcom": true,
  "maxItems": 1000,
  "proxyConfiguration": { "useApifyProxy": true }
}

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📤 Output

Each deal is saved as one structured JSON object in the dataset. Below are two real records from a verified run — one printed weekly flyer deal and one online e-commerce deal:

Sample flyer deal record

{
  "type": "flyer",
  "itemId": "1050023770",
  "name": "Horizon Organic Milk",
  "currentPrice": 4.49,
  "originalPrice": 5.49,
  "prePriceText": "",
  "postPriceText": "with weis preferred SHOPPERS CLUB",
  "saleStory": "- $1.00 Digital Savings",
  "discountPercent": 18,
  "brandIds": ["3645"],
  "itemWeight": "0.729",
  "merchant": "Weis Markets",
  "merchantId": "2455",
  "merchantLogo": "http://images.wishabi.net/merchants/2455/1528840420/storefront_logo",
  "flyerId": "8195063",
  "validFrom": "2026-10-29T05:00:00+00:00",
  "validTo": "2026-11-27T04:59:59+00:00",
  "imageUrl": "https://f.wishabi.net/page_items/438671201/1792748190/extra_large.jpg",
  "searchTerm": "milk",
  "postalCode": "10001",
  "scrapedAt": "2026-11-01T23:47:21.385Z"
}

Sample online deal record

{
  "type": "online",
  "itemId": "712127",
  "name": "Well Market Milk Choc Waffle Cones",
  "currentPrice": 3.99,
  "originalPrice": 5.99,
  "discountPercent": 33,
  "description": "Well Market Milk Choc Waffle Cones",
  "merchant": "CVS Pharmacy",
  "merchantId": "2264",
  "merchantLogo": "https://images.wishabi.net/merchants/2264/1507308958/2264.jpg",
  "sku": "712127",
  "averageRating": 4.61,
  "totalReviews": 128,
  "shippingInfo": "Free shipping",
  "imageUrl": "https://flipp-image-retrieval.flipp.com/api/...",
  "searchTerm": "milk",
  "postalCode": "10001",
  "scrapedAt": "2026-11-01T23:47:22.779Z"
}

---

📋 Output fields & coverage reference

🏷️ Deal Identity & Pricing

Field	Type	Coverage	Description
type	string	🟢 High (100%)	Deal channel: "flyer" (weekly store circular) or "online" (e-commerce listing).
itemId	string	🟢 High (100%)	Unique deal or item identifier (used with type for strict de-duplication).
name	string	🟢 High (100%)	Clean product or deal headline (unnamed flyer image clippings are automatically filtered out).
currentPrice	number / null	🟢 High (~92%)	Active promotional or sale price in local currency (USD for en-us, CAD for en-ca).
originalPrice	number / null	🟡 Conditional (~25%)	Pre-sale "was" price when advertised by the merchant.
discountPercent	integer / null	🟡 Conditional (~25%)	Computed percentage off (Math.round((1 - currentPrice / originalPrice) * 100)) when both prices exist.
saleStory	string	🟡 Conditional (~35%)	Promotional callout on flyer items (e.g. "SAVE 46%", "Digital Coupon", "Buy 1 Get 1 Free").
prePriceText	string	🟡 Conditional (~20%)	Qualifier printed before the price on the flyer.
postPriceText	string	🟡 Conditional (~42%)	Unit, limit, or loyalty-card requirement printed after the price (e.g. "lb. Limit 2", "with Club Card").
itemWeight	string	🟢 High (~99% flyer)	Package weight, volume, or unit size reported on flyer deals.
brandIds	array<string>	🟡 Conditional (~60% flyer)	Brand identifier codes associated with the flyer item.

🏪 Merchant, Validity & Provenance

Field	Type	Coverage	Description
merchant	string	🟢 High (100%)	Store or retailer name (e.g. Walmart, Kroger, Target, Shoppers Drug Mart, Loblaws).
merchantId	string	🟢 High (100%)	Unique merchant identifier.
merchantLogo	string	🟢 High (100%)	URL to the retailer's storefront logo image.
flyerId	string	🟢 High (100% flyer)	Circular / flyer identifier ("" on online-only deals).
validFrom	string	🟢 High (~99% flyer)	ISO 8601 start timestamp of the flyer promotion window.
validTo	string	🟢 High (~99% flyer)	ISO 8601 expiration timestamp of the flyer promotion window.
imageUrl	string	🟢 High (100%)	Direct URL to the product or flyer clipping image.
searchTerm	string	🟢 High (100%)	The search query that matched this deal.
postalCode	string	🟢 High (100%)	The US ZIP or Canadian postal code queried.
scrapedAt	string	🟢 High (100%)	ISO 8601 timestamp when the record was collected.

🛒 Online / E-Commerce Enrichment (type: "online")

Field	Type	Coverage	Description
description	string	🟢 High (99% online)	Product description snippet (up to 300 chars) on online deals.
sku	string	🟢 High (99% online)	Retailer SKU identifier on online deals.
averageRating	number / null	🟡 Conditional (~85% online)	Average customer star rating (1–5) on online deals.
totalReviews	integer / null	🟡 Conditional (~85% online)	Total customer review count on online deals.
shippingInfo	string	🟡 Conditional (~50% online)	Shipping badge text (e.g. "Free shipping") when provided by the retailer.

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🔁 Pagination & 1,000+ deals scale

Unlike traditional paginated web catalogs, Flipp returns the entire localized result set for a search term in a single response (typically 40–100+ named flyer deals plus up to ~85 online deals per term). To make scaling effortless:

1. Multi-term iteration & interleaving: The scraper iterates through every query in searchTerms, interleaves flyer and online deals 1-for-1 so neither type starves under a cap, and de-duplicates across all terms using type:itemId.
2. Automatic 1,000+ grocery category expansion: When you set maxItems > 150 (for example maxItems: 1000), you do not have to manually type 25 search terms. After processing your custom searchTerms, the actor automatically appends up to 40 high-volume grocery and household staples (milk, eggs, coffee, chicken, beef, salmon, bread, butter, cheese, yogurt, cereal, rice, pasta, apple, banana, orange, potato, tomato, juice, soda, water, chips, pizza, olive oil, laundry detergent, paper towels, etc.) until maxItems unique deals have been saved.
3. Sub-minute execution: Because each term requires only one lightweight HTTP request over Datacenter proxy, collecting 500–1,000+ de-duplicated deals typically finishes in 15–45 seconds at a fraction of a cent in platform usage.

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⚙️ How to use

1. Open the actor in Apify Console and enter your Search terms (or leave the defaults).
2. Set your location: Enter a US Postal / ZIP code (e.g. 10001) with locale: "en-us", or a Canadian postal code (e.g. M5V2T6) with locale: "en-ca".
3. Set your target volume: Use maxItems: 100 for a quick test, maxItems: 1000 for a broad supermarket sweep, or 0 for all deals matching your terms.
4. Click Start and watch flyer and online deals stream into the dataset.
5. Export or automate: Download JSON, CSV, Excel, or HTML, or schedule weekly runs and connect to Google Sheets, Make, Zapier, n8n, Snowflake, BigQuery, or webhooks.

Calling via Python SDK

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run_input = {
    "searchTerms": ["milk", "eggs", "coffee", "chicken", "butter"],
    "postalCode": "60601",
    "locale": "en-us",
    "includeEcom": True,
    "maxItems": 500,
    "proxyConfiguration": {"useApifyProxy": True},
}

run = client.actor("haketa/flipp-scraper").call(run_input=run_input)

for deal in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"[{deal['type']}] {deal['name']} — ${deal['currentPrice']} at {deal['merchant']} ({deal.get('saleStory', '')})")

Finding the lowest local price per item (Python)

run = client.actor("haketa/flipp-scraper").call(run_input={
    "searchTerms": ["milk", "eggs", "ground beef"],
    "postalCode": "10001",
    "locale": "en-us",
    "maxItems": 300,
})

cheapest = {}
for d in client.dataset(run["defaultDatasetId"]).iterate_items():
    price = d.get("currentPrice")
    term = d.get("searchTerm")
    if price is not None and term:
        if term not in cheapest or price < cheapest[term]["currentPrice"]:
            cheapest[term] = d

for term, d in cheapest.items():
    print(f"Lowest '{term}': ${d['currentPrice']} at {d['merchant']} — {d['name']}")

Calling via JavaScript / Node.js SDK

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('haketa/flipp-scraper').call({
    searchTerms: ['milk', 'eggs', 'coffee', 'chicken', 'bread'],
    postalCode: '10001',
    locale: 'en-us',
    includeEcom: true,
    maxItems: 400,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Collected ${items.length} localized Flipp deals.`);

Calling via cURL (REST API)

curl -X POST "https://api.apify.com/v2/acts/haketa~flipp-scraper/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "searchTerms": ["milk", "eggs", "coffee"],
    "postalCode": "M5V2T6",
    "locale": "en-ca",
    "includeEcom": true,
    "maxItems": 200
  }'

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🗺️ Supported regions & sample postal codes

Country	locale setting	Sample postalCode	Metro Area	Currency
United States	"en-us"	10001	New York, NY	USD ($)
United States	"en-us"	90001	Los Angeles, CA	USD ($)
United States	"en-us"	60601	Chicago, IL	USD ($)
United States	"en-us"	77001	Houston, TX	USD ($)
United States	"en-us"	33101	Miami, FL	USD ($)
Canada	"en-ca"	M5V2T6	Toronto, ON	CAD ($)
Canada	"en-ca"	H2X1Y4	Montreal, QC	CAD ($)
Canada	"en-ca"	V6B1A1	Vancouver, BC	CAD ($)
Canada	"en-ca"	T2P1J9	Calgary, AB	CAD ($)

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💡 Pro tips for best results

• Always pair postalCode and locale: Use en-us with 5-digit US ZIP codes (10001, 90001, 77001) and en-ca with 6-character Canadian postal codes (M5V2T6, V6B1A1, T2P1J9).
• Flyer-only competitive intelligence: Set includeEcom: false when you only want printed weekly store circulars (type: "flyer") with flyerId, validFrom, and validTo windows.
• Schedule weekly snapshots: Most North American grocers publish new weekly flyers between Wednesday and Friday; schedule a weekly run to build a time-series database of promotional pricing.
• Keep Datacenter proxy enabled: Flipp works smoothly with standard Apify Datacenter proxies (useApifyProxy: true), keeping run costs ultra-low (~$0.01–$0.02 per 1,000 deals).

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⚠️ Honest limitations

• Printed flyers often omit "was" prices: Roughly 75–90% of weekly grocery circular items advertise a promotional currentPrice or multi-buy saleStory without stating a pre-sale originalPrice; for those items, originalPrice and discountPercent are null.
• Percentage-off / BOGO callouts: A small fraction (~5–10%) of flyer items advertise "Buy 1 Get 1 Free" or "25% Off Entire Line" in saleStory without a single numeric currentPrice.
• Single-location per run: Each run queries one postalCode. To compare 10 different cities or ZIP codes, trigger parallel runs via the API or an Apify task schedule.

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❓ FAQ

Do I need a Flipp account or API key? No. The actor requires no login, no cookies, and no API key.

How do I collect 1,000+ deals if one search term only returns ~150 items? Simply set maxItems: 1000 (or higher). Whenever maxItems > 150, the actor automatically expands your search list across 40+ staple grocery and household terms, de-duplicating every item so you receive 1,000+ unique deals in a single run.

What happens if I run the actor with empty searchTerms? It automatically falls back to a curated list of popular grocery staples (milk, eggs, coffee, chicken, beef, pork) and returns a 100-deal sample so empty runs never fail.

Does this support Canadian grocery stores like Loblaws, No Frills, Metro, and Sobeys? Yes. Set locale: "en-ca" and provide a Canadian postal code (e.g. "M5V2T6" for Toronto or "V6B1A1" for Vancouver) to pull Canadian weekly flyers in CAD.

Can I fetch the output synchronously via a single HTTP call? Yes. In addition to pushing every item to the default Dataset, the actor writes { count, deals } to the OUTPUT record in the default Key-Value Store so run-sync API calls receive the full payload immediately.

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📋 Changelog

• v1.2 (2026-11) — Added automatic 40-term grocery category expansion when maxItems > 150 so users requesting 1,000+ deals receive 1,000+ unique, de-duplicated records in a single run; added empty-run default grocery sample fallback; expanded README with coverage tables and SDK recipes.
• v1.1 (2026-11) — Fixed online deal ID resolution (item_id / global_id / sku) for 100% accurate online de-duplication; added 1-for-1 flyer/online interleaving and brandIds extraction.
• v1.0 (2026-09) — Initial release with US (en-us) and Canada (en-ca) weekly flyer + e-commerce deal extraction and Key-Value Store OUTPUT mirroring.

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This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Flipp Operations Inc. or any retailer. All trademarks belong to their respective owners and are used only to describe the publicly available data source.