How to Scrape Local Grocery Deals by Postal Code with Flipp

Description and use

The actor pulls clean, structured pricing data for specified products or circulars, enabling price comparison, trend tracking, and coupon aggregation without login or proxies.

Problem

Retail analysts and developers struggle to track fragmented grocery pricing across local stores and postal codes.

Outcome

The actor pulls clean, structured pricing data for specified products or circulars, enabling price comparison, trend tracking, and coupon aggregation without login or proxies.

Workflow

• Select mode and location in actor input (e.g., mode=search, postalCode=45202).
• Define product search terms in query field (e.g., "milk").
• Apply filters: set itemType to flyer, sortBy to price_low_to_high, includeCoupons to true if needed.
• Run the actor on Apify and wait for completion.
• Export the dataset in JSON/CSV/Excel for analysis or storage.