Instacart Data Scraping Services

Retailer is a dimension, not the platform

Every record on Instacart belongs to a specific retailer's storefront inside the platform. Kroger on Instacart, Costco on Instacart and a regional chain on Instacart are three different price sets on the same app.

• Assortment differs by retailer and by the specific store fulfilling that zip.
• Pricing is retailer-set, so a competitor comparison across retailers is comparing retailer decisions rather than platform decisions.
• Availability is per store, driven by that store's actual shelf.
• Fee structures differ by retailer and by membership status.

We put retailer and store_id on every record alongside zip. Aggregating across retailers into a single "Instacart price" produces a number that no shopper ever saw.

Platform markup is the signal clients come for

An item on Instacart frequently costs more than the same item on the retailer's own site or shelf. The markup is generally set by the retailer to cover the cost of the channel, and it varies by retailer, category and sometimes by item.

Measuring it requires collecting both sides in the same window: the Instacart storefront and the retailer's own site, then matching items across them. That matching is the hard part, because retailers do not always use identical product naming or pack descriptions across their own channels.

We deliver price_instacart, price_retailer_direct where we also collect the retailer, a computed markup_pct, and match_confidence on the cross-channel link. Where an item cannot be matched confidently, markup is null with a reason rather than estimated.

For brands, this answers a question they usually cannot: whether their products are being priced above their intended shelf price in a channel they do not control.

The fee stack often exceeds the markup

What a shopper pays is item prices plus delivery fee, service fee, possible priority fee, taxes and a tip. On a small basket those components can exceed the item markup entirely.

A price comparison against a conventional grocer using item prices alone understates the difference substantially — and it is the comparison most brands and retailers actually want to make.

• Fees vary by retailer and by whether the shopper holds a membership.
• Membership pricing is displayed publicly on many items and changes the effective basket materially.
• Fee structures change more often than item prices, so a fee assumption captured once ages fast.

We capture each fee component as displayed at observation time on every run, plus price_member as its own field. We do not fold them into one figure, because fee structure changes are their own signal and merging them hides both.