# DoorDash opens interest and retailer targeting to CPG brands, claiming 30% lift on targeted campaigns

*The delivery platform now lets brands target by shopping behavior and retail chain, closing the gap between intent and checkout.*

By **Jenny Huang Goodman MPA MSc MHSA, Principal** — The Stash Edge, Hako Shikin LLC.
Published 2026-06-04.

Canonical: https://www.pops4.com/stash/articles/doordash-2026-06-04t01-3
Subject: DoorDash
Tags: doordash, cpg, interest targeting, retailer targeting, ad precision, distribution

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DoorDash Ads launched three new capabilities for CPG brands in January 2025: interest targeting, retailer targeting, and category share insights, according to the company's announcement. The platform claims brands using interest targeting see an average **30%** increase in return on ad spend compared to broad campaigns, though DoorDash supplied that figure and no independent audit is available.

The mechanics are straightforward. Interest targeting surfaces ads based on past cart behavior—shoppers who bought protein bars see ads for granola, shoppers who bought oat milk see ads for coffee. Retailer targeting lets a brand promote only at specific chains, so a product stocked at Albertsons can suppress ads to Safeway shoppers. Category share insights show a brand's slice of spending within its category on DoorDash, updated weekly.

This works because DoorDash sits at the junction of intent and transaction. A shopper opening the app has decided to buy groceries in the next fifteen minutes, not browse. The platform knows purchase history, live inventory, and which retailer the shopper prefers. Interest targeting turns that data into ad placement without the brand needing to guess keywords or demographics. Retailer targeting solves a basic distribution problem: if your protein bar is only in **500** stores, you stop wasting impressions on the other **5,000**.

The steal for a small physical-product brand is to apply the same precision to the channels you already control. Start with email: segment your list by past purchase category, then send product recommendations that mirror DoorDash's interest model. If someone bought a candle, email them a room spray. If they bought a notebook, email them a pen set. Keep the window tight—send within **48 hours** of delivery, while the product is still tactile.

Next, apply retailer-style targeting to your retail partners. If you're in **20** independent shops, create **20** geo-targeted Meta ads with store locators in the creative. Spend **$5** per day per store, radius set to **3 miles**. The shopper sees your product and the nearest place to buy it in one unit. Track conversion by asking each retailer for weekly sell-through and match it to ad spend by location. Kill the bottom quartile, double down on the top.

For category share insights, build a simple tracker in a spreadsheet. Pull your Shopify or Amazon sales by SKU and compare them to your closest competitor's estimated volume—use Jungle Scout for Amazon, call your retailers for shelf data. Update it monthly. If your share is falling, your price or placement is wrong. If it's rising, you've found a wedge to push.

The broader lesson is that DoorDash isn't inventing new marketing science—it's automating what direct-to-consumer brands already do manually. Interest targeting is email segmentation at scale. Retailer targeting is local awareness ads with an inventory filter. Category share is your monthly P&L broken out by competitor. The platform advantage is speed and closed-loop attribution, but a small brand with clean data and a willingness to segment can run the same play in **72 hours** for under **$500**.

## The takeaway

DoorDash's new targeting tools automate segmentation and local spend, but any brand can copy the logic with email, geo ads, and a tracking sheet.

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## Publisher

**Hako Shikin LLC** — Virginia Beach, Virginia. Founded 1997. ASI 217876 · DUNS 18-204-6339.
Principal and author: **Jenny Huang Goodman MPA MSc MHSA**.

- Author: https://www.huanggoodman.com/about
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