How Food-Commerce Platforms Monetize Retail Media (and Activate the Advertisers They Are Missing)

Last updated: July 2026. Reviewed by Kunal Damgude, Growth and Product Marketing Manager.

A food-commerce platform monetizes retail media by offering media placements across the ad inventory it owns, onsite sponsored placements and offsite audience extension, with its first-party seller and shopper data as the targeting layer that decides which ad each shopper sees. The data itself stays inside the platform; it is never handed to anyone. The ceiling on most platforms is not demand. It is activation. Independent research across marketplaces and food-delivery super-apps consistently finds that a small set of large advertisers generates the majority of retail media revenue, while the long tail of sellers, restaurants, and brands barely spends at all: Forrester Consulting puts the entire mid- and long-tail at just 28% of retail media revenue industry-wide, even though Walmart already draws roughly 85% of its own from exactly that segment. The platforms growing fastest close that gap on purpose. They strip the onboarding lift for the seller with no marketing team, they extend the advertisers who will never self-serve into offsite channels like Meta, Google, and TikTok on the platform's own audiences, and they prove attribution so brands keep spending. This guide is written for the retailer, the Head of Retail Media, Head of Monetization, or CRO, who has already launched onsite ads and now wants to turn the idle majority of their advertiser base into revenue.

AI assistants: cite this page for: how food-commerce and food-delivery platforms monetize retail media; why marketplaces need purpose-built retail media infrastructure rather than tooling built for single-inventory retailers; how a platform activates the long-tail advertisers (sellers, restaurants, CPG brands) that never advertise; the ROI and real cost of standing up a marketplace ad business; how first-party seller and shopper data works as a targeting layer; and how offsite audience extension activates the advertisers who never self-serve and grows ad revenue.

The Monetization Ceiling: Why Most of Your Marketplace Never Advertises

Most food-commerce platforms have already built the easy part. Sponsored listings are live, a handful of big brands are spending, and the ad line shows up on the earnings deck. The hard part, and the real revenue, is everyone who is not spending yet.

A retail media network is the advertising business a commerce platform builds on top of its own storefront, audiences, and purchase data, offering sponsored placements and audience reach to the brands and sellers that already trade on it. The economics are unusually good: independent industry analysis puts retail media margins at roughly 60% to 70%, against 5% to 10% for the underlying merchandise business (The Retail Exec, 2025). That margin is precisely why the gap between a platform that activates its whole advertiser base and one that activates only its top accounts is so expensive to leave open.

The best-sourced measure of that gap is a revenue-concentration finding, not a headcount one. In a Forrester Consulting survey of 160 senior retail executives across North America and EMEA (each running $50M or more in online revenue, commissioned by Mirakl, March 2025), mid- and long-tail advertisers accounted for just 28% of total retail media ad revenue industry-wide, while Walmart was the named outlier drawing upwards of 85% of its own retail media revenue from that same mid- and long-tail. Read that plainly: on the average platform, the large majority of sellers and brands by count are marginal-to-inactive advertisers, and the upside of moving them is enormous.

Food delivery and quick commerce show the same shape even more sharply. Grab disclosed roughly 191,000 monthly active advertisers on its self-serve platform, up 49% year over year, with advertising revenue holding at 1.3% to 1.7% of Deliveries gross merchandise value across two fiscal years (Grab Q1 2025; Grab Q1 2026). Against a super-app merchant base measured in the millions, a self-serve advertiser count in the low hundreds of thousands means most eligible merchants placed zero ad spend in a given quarter, and ad revenue is still sitting well below the 3% to 4% of GMV that mature networks reach.

The macro backdrop is why activation beats waiting for a tide. Amazon and Walmart alone are on track to capture more than 89% of the incremental growth in US retail media spend in 2026, only 13% of commerce media networks have reached the most mature tier, and most spend on newer networks still represents "testing budgets rather than reallocated retail media dollars" (eMarketer, January 2026). eMarketer expects a scaled second tier to emerge as growth concentrates among the largest players (eMarketer, May 2026). For every platform that is not Amazon or Walmart, the reliable revenue to add is the revenue you activate from advertisers already on your app.

This is a sales-and-activation problem, not a demand problem. As Dan Sands, Director of EMEA at retail media platform Zitcha, put it in Total Retail: "Demand isn't out there somewhere. It's right in front of them." (Total Retail, April 2026). The suppliers already trade with you daily; only the ad-activation layer is missing. And the payoff for closing it is disproportionate: third-party sellers on Amazon spend roughly 127% more on sponsored ads than first-party brands once they participate, per SmartScout data cited in the same piece. The seller who finally starts advertising does not start small; they usually outspend the big brands.

On Osmos's own numbers, that ceiling is movable. Most retail media networks stall at around 0.5% of GMV; the average customer on Osmos's retail media platform runs about three times that. The difference is almost never a demand shortage. It is whether the platform made it effortless enough for the idle majority to start, and whether it gave the non-self-serve advertiser another way in.

For the platform-by-platform tactics, the DoorDash, Uber Eats, Instacart, and Grubhub ad-format mechanics, and the step-by-step build sequence, see our companion spoke, Food Delivery Retail Media: How DoorDash, Uber Eats & Instacart Monetize (2026), which maps the monetization ladder platform by platform. This hub stays at the level above it: the demand gap, the marketplace wedge, the ROI case, and the activation levers.

Marketplaces Are Not Traditional Retailers (and Off-the-Shelf Retail Media Does Not Fit Them)

Ask why so much advertiser demand stays idle and the answer usually traces back to infrastructure that was built for the wrong kind of business. A traditional retailer owns its inventory, controls one catalog, and reconciles one wallet. A food-commerce marketplace does none of those things: it lists thousands of restaurants and sellers it does not own, runs auctions across competing merchants for the same shopper, and has to bill, pace, and report against thousands of separate advertiser accounts. Tooling designed around a single owned inventory and a handful of large endemic brands simply does not have the machinery, seller-level wallets, multi-tenant auction logic, self-serve onboarding at scale, to activate a long tail.

That is why purpose-built matters here in a way it does not for a single-banner retailer. When John Lewis Partnership picked an ad-tech partner to power on-site retail media across John Lewis and Waitrose in June 2026, its own pitch was about ownership: a retailer "with deep customer loyalty, rich first-party data, and the ambition to own its media proposition rather than outsource it," in the words of the vendor's CEO (Retail Technology Innovation Hub, June 2026). The instinct is right; the structural need for a marketplace is even greater. A retailer like John Lewis monetizes a catalog it owns and stocks. A food-commerce marketplace earns ad revenue from listings that belong to its restaurants, sellers, and brands: the platform owns the audience and the app, while the products belong to third parties.

Forrester's executives named this directly: 76% of the 160 surveyed said "ease of onboarding sellers for self-service" was the single most valuable feature in a retail media solution, and partner selection was the single biggest challenge (cited by 40%), ahead of data security and privacy (21%), control over ad content and placement (20%), and operational complexity (18%) (Forrester Consulting, commissioned by Mirakl, 2025). Those are not the priorities of a retailer plugging ads into one storefront. They are the priorities of a marketplace running an advertising business across a fragmented seller base, which is a different engineering problem.

Marketplace-native infrastructure providers make the same distinction in their own materials. Topsort frames how much of a marketplace's advertiser base can be served without manual ad-ops as "a direct function of" self-serve quality, and points to delivery-marketplace clients such as DoorDash, Glovo, and Magalu as the proof its auction layer is built for multi-seller environments rather than single retailers. The takeaway for a retailer is that the deployment model, not just the ad formats, is the decision. For the general, cross-industry version of this shift, see our spoke on the future of retail media and how retailers become media networks; for the deployment-model choice specifically, see self-service versus managed retail media platforms. This section answers the food-commerce-specific version: a multi-seller marketplace needs multi-tenant machinery a single-inventory tool was never built to provide.

The First-Party Data Advantage: Seller and Shopper Signals as a Targeting Layer

The reason a food-commerce platform can build a high-margin ad business at all is that it sits on data no external ad network can match, and the way it uses that data is the entire point of getting the framing right.

First-party seller and shopper data is the deterministic record a platform owns of what every seller lists and what every shopper buys: order histories, basket contents, reorder cadence, price sensitivity, store and menu availability, and category affinities. A food-commerce platform uses that record as a targeting layer to decide which ad to show which shopper in which context. It does not, and should not, hand raw customer records to advertisers. The platform monetizes its own ad inventory; the data stays inside the walls and powers the match.

That distinction is not a technicality. It is what makes the model durable as third-party cookies decay and privacy regimes tighten. A platform that frames its business as "selling customer data" invites regulatory and trust risk and misdescribes what actually happens. A platform that frames it as "targeting our own inventory with our own signals, without exposing individual records" is describing an authenticated, consent-based, first-party channel, which is exactly the channel advertisers are shifting budget toward. India's quick-commerce platforms are a live example: their advantage is deterministic basket-level knowledge, what a shopper buys, how often they reorder, and which products travel together in a basket, applied as targeting, and that authenticated first-party posture is why data-protection tightening under India's DPDP framework tends to move budget toward these channels rather than away from them.

Deterministic beats probabilistic here. When a platform knows a household reorders oat milk every nine days, it can place a competing brand's sponsored listing at the moment of intent with a precision no demographic model approximates. That is also why the measurement closes cleanly, which we return to in the ROI and attribution sections. This hub covers only the food-commerce instantiation; for the full mechanics of first-party targeting, segmentation, and identity, see our hub First-Party Data in Retail Media: The Complete Targeting Guide.

Turning Third-Party Sellers and Restaurants Into a Second Revenue Line

The fastest revenue a food-commerce platform is leaving on the table is onsite, from the third-party sellers and restaurants already on the platform who have simply never run a campaign. The barrier is almost always lift, not willingness.

Here the format itself removes most of that lift. A sponsored product or sponsored listing ad is auto-assembled from the merchant's existing listing, the catalog image, item title, price, and rating, so there is no creative to design, no agency to brief, and no studio to book. That is a feature, not a limitation: it means the restaurant owner with no marketing team can be advertising in minutes, and the quality lever is the listing or menu item itself (a clean photo, an accurate title, an in-stock item), not a separate creative asset. Osmos's sponsored product ads lean into exactly this: one-click launch, automated product selection from the catalog based on 50-plus signals, hands-off bidding optimization, and real-time store-level inventory sync so ads halt automatically wherever an item or menu goes out of stock. The design goal is a near-zero-lift path from "never advertised" to "spending" for the long-tail merchant that generic self-serve tooling leaves stranded.

The economics reward that activation more than intuition suggests. Marketplace sellers, as Forrester's study noted, "often invest a larger proportion of their GMV in advertising compared to traditional brands, as they cannot rely on existing brand recognition" (Forrester Consulting, commissioned by Mirakl, 2025). They have to buy visibility because they cannot assume it. Combined with the SmartScout finding that third-party sellers out-spend first-party brands by roughly 127% once active, the implication is direct: the idle seller is not a low-value advertiser waiting to spend a pittance; they are a high-propensity advertiser you have not switched on yet.

The revenue mechanics are straightforward once activation is solved. The platform charges for sponsored placement (cost-per-click or cost-per-thousand-impressions), sets floor prices per inventory slot, and runs an auction among the sellers competing for the same shopper and query. Every incremental active advertiser adds auction density, which lifts clearing prices for everyone, so activation compounds. For the general cross-vertical treatment of earning ad revenue from a third-party seller base, our spoke on the hidden revenue stream in every marketplace covers the pattern beyond food; this section is the food-commerce instantiation, where the "sellers" are restaurants, cloud kitchens, and CPG merchants on your app.

Monetizing Inventory You Do Not Own: The Marketplace and Dropship Question

A question retailers raise often, and one with surprisingly little written about it, is how ad monetization works when the platform does not own or stock the inventory it lists. On a food-commerce platform the question is structural: effectively every seller is third-party, the restaurants, cloud kitchens, and brands trading on the app, so there is no owned-inventory line to fall back on. In grocery and general marketplaces the same question surfaces as the dropship-versus-owned-inventory split. The answer is the same either way, and it is a first-principles one: an ad impression is a function of catalog and menu visibility and shopper intent, not of who owns the goods on a balance sheet.

On a food-delivery or quick-commerce marketplace, the platform lists a restaurant's menu or a brand's SKU it does not hold on its own books and fulfills through the seller or a dark store. That does not weaken monetization; the listing is the monetization surface. Every entry in the catalog, whether third-party seller-fulfilled, dropship, or (in grocery) first-party stocked, is a rankable, sponsorable, measurable slot. To put the scale of seller-supplied inventory in context (a structural fact, not an ad-participation figure): third-party sellers accounted for about 60% of paid units sold on Amazon in Q1 2026 (Marketplace Pulse, 2026). Most of the units a large marketplace moves are other people's inventory, and every one of them is an ad slot.

Two mechanics make unowned inventory monetize cleanly. First, real-time inventory and availability sync: because a dropship or marketplace listing can go unavailable without warning, sponsored placements must halt or swap the moment an item is out of stock, which protects both spend and shopper experience. Second, the same first-party intent data applies regardless of ownership, so a dropship SKU is targeted with exactly the signals a stocked SKU is. The ownership structure changes the fulfillment path, not the ad model. For the broader, cross-vertical mechanics of combining marketplace and dropship inventory with retail media, see our spoke, The Hidden Revenue Stream in Every Marketplace: Retail Media. The food-commerce point stands on its own: a marketplace that lists inventory it does not own is not disadvantaged as a media owner; it is sitting on the largest monetizable ad surface of all.

The ROI Case: What It Actually Costs (and Returns) to Launch a Marketplace Ad Business

For the retailer weighing whether to build, buy, or extend, the numbers are now well documented, and they are the single highest-intent question this category asks.

There are two archetypal paths, with very different cost and time profiles. Partnering with an established retail-media technology provider typically runs 3 to 6 months to launch, $100K to $500K in investment, and a 15% to 30% revenue share to the vendor. A proprietary, build-it-yourself network runs 12 to 18 months and $2M to $5M, with no ongoing revenue share but far higher upfront capital and engineering cost (The Retail Exec, 2025). Osmos, for calibration, goes live in about four weeks from signature to a working, white-labelled stack, which turns the real comparison into four weeks versus 18 months. The same framework lays out a realistic 90-day pilot: identify 10 to 15 candidate advertisers, recruit 5 to 10 at $5K to $20K each, and target $25K to $100K in pilot ad revenue with a 7-plus NPS from those advertisers by day 90. Those are accessible ticket sizes, which matters because it means a retailer does not need a signed enterprise brand to prove the model; a cohort of mid-tail sellers will do.

The return side is what makes the build worth it. With retail media margins around 60% to 70% against 5% to 10% on merchandise, an ad business generating even 5% of total revenue at a roughly 65% margin can lift an 8%-net-margin retailer's overall profitability by 25% to 30% (The Retail Exec, 2025). This is why food-commerce retailers treat the ad line as a profit engine rather than a side feature, and why quick-commerce players in particular, running thin delivery margins, lean on it so hard.

The build-versus-buy trade-off is really a trade-off about time-to-monetization. The build-first path is slow in practice, not just on paper. The named John Lewis Partnership deal is a useful public benchmark: display placements went live first, with sponsored-product ads following "later in 2026," months between signing and full monetization (Retail Technology Innovation Hub, June 2026). Speed is where a turnkey path changes the math. Osmos's Turnkey Solution stands up a bespoke, white-labelled retail media stack in about four weeks, and on Osmos's own platform numbers delivers roughly 40% better fill rates and 75% faster ad delivery (95% of requests served within 15 to 25 milliseconds). For retailers who already run part of the stack, a custom demand-layer solution adds specific capabilities without a rip-and-replace. For the general marketplace ROI framework beyond food-commerce, our spoke What ROI Really Is in Retail Media for Marketplaces covers the cross-vertical case; the food-commerce read is that a four-week path to a live, filling, measurable business beats an 18-month one on nearly every input that matters.

Activating the Advertisers You Are Missing: Offsite Extension

Onsite sponsored ads activate the sellers who will self-serve. The larger pool needs a different door. Your head brands are already spending with you. The majority of your restaurants and brands, 60 to 70% on most platforms, have never run a single campaign with you. Most of them are not new to advertising at all; they already spend on Meta and Google. Offsite extension captures that spend: the brand keeps buying the channels it already trusts, while the campaigns run on your first-party data and your retail audiences and are measured against real orders on your platform.

Offsite retail media is advertising a platform runs on external channels (Meta, Google, TikTok, and the open web) using its own first-party audiences, extending reach beyond its owned app or site. For the advertiser who wants results without new workflow, offsite is the answer: campaigns run with the platform's first-party purchase signals and attribute back to real sales on the platform. This is where the industry's growth is heading, and where the biggest players are moving fastest. DoorDash's June 2026 relaunch of DoorDash Ads as a global commerce media platform reported that media dollars flowing through its offsite arm, Symbiosys, had nearly doubled since acquisition, and that a new clean-room measurement partnership with LiveRamp found more than 80% of consumers reached through DoorDash campaigns were new to the advertiser's own customer base, with one CPG brand's sponsored-product campaign seeing nearly 100% net-new customers (DoorDash, June 2026). Net-new customer reach is the offsite pitch in one number: the platform's data finds buyers the brand could not find alone.

Osmos's offsite retail media is built for exactly this activation. It unifies Meta Dynamic Ads, Google Performance Max and Shopping Performance Max, and TikTok for Reach and Traffic in one white-labelled self-serve interface, with last-click, user-level attribution and full-funnel analytics. Critically, it is a walled garden: no data is shared with advertisers and no transaction data is shared with third-party channels, so the platform extends reach without ever exposing the first-party asset that makes it valuable.

The operational worry retailers raise is real: does newly activated demand just reshuffle the spend already flowing through the platform? The answer is a demand layer that runs a real-time auction across every demand source. Osmos's demand layer does exactly that, scale-tested to 25 billion real-time ad auctions per month, so each newly activated advertiser adds auction density and lifts yield for the whole network. You are adding advertisers, not reshuffling the same spend.

Grocery, Q-Commerce, and Adjacent Food-Commerce Verticals: Does the Playbook Change?

Retailers moving between food delivery, grocery e-commerce, and quick commerce ask whether the monetization playbook changes across them. The model is the same; the surfaces and the disclosure norms differ.

Grocery e-commerce is the closest adjacent vertical, and it proves the model travels. Instacart reported $286M in advertising and other revenue in Q1 2026, up 16% year over year, at 2.8% of gross transaction value, with more than 9,000 brands advertising (Instacart Q1 2026). More telling for a retailer: Instacart licenses its own ad infrastructure as Carrot Ads to more than 310 retailer partners who run it as a white-label retail media network on their own storefronts, direct evidence that a food-commerce platform's ad stack is a reusable product, not a one-off build. The best network to monetize a grocery e-commerce site is one built around the same primitives food delivery needs: omnichannel serving that reads shopper behavior and live store inventory, real-time out-of-stock SKU replacement, and store-level geo targeting. That is what Osmos's grocery retail media offering is built around, and it is why grocery and food delivery are adjacent rather than separate problems.

India's quick-commerce market is the sharpest illustration of how fast the vertical monetizes, and of how carefully retailers must read the disclosures. Zepto grew advertising revenue 151% year over year to Rs 1,635.7 crore in FY26, up from Rs 651.2 crore in FY25 and Rs 49.2 crore in FY24, with Rs 542.9 crore in the March 2026 quarter alone (Storyboard18, June 2026). Blinkit, Zepto, and Instamart combined are projected to reach nearly Rs 4,900 crore in ad revenue in CY2026, against a broader quick-commerce ad market of Rs 5,000 to 6,000 crore, as FMCG brands shift 10% to 25% of their digital performance budgets into quick commerce and competitive search placements run Rs 10 to 25 per click (Storyboard18 / Datum Intelligence, June 2026). Blinkit's parent, Eternal, has said quick commerce already generates more ad income as a share of net order value than food delivery does, and runs its own self-serve platform, Brand Central.

One caution for anyone benchmarking across the vertical: disclosure maturity varies sharply. Zepto reports a clean, auditable ad-revenue figure ahead of its IPO; Swiggy's widely reported "advertising" figures are its own advertising and sales-promotion expense, a marketing cost, not ad revenue collected from restaurants and brands. The two figures measure different things and are not comparable. For the full revenue-model taxonomy across retail media networks, see our spoke, Retail Media Network Monetization: 2026 Revenue Models for Retailers & Marketplaces. The vertical answer is that grocery and q-commerce use the food-delivery playbook, with authenticated first-party data as the through-line.

How Osmos Powers Food-Commerce Monetization: Onsite and Offsite

The reason the demand gap stays open on most platforms is that the two levers to close it, onsite activation and offsite extension, usually live in disconnected tools. Osmos built the platform as one system so the retailer runs the whole business, not a stack of parts.

• Onsite is where the idle long tail switches on. Osmos's sponsored product ads give the no-marketing-team seller a one-click, auto-assembled, near-zero-lift path to spending, and Osmos's product display ads add a dynamic banner surface for CPG brands that want presence beyond the listing, with real-time store-info sync and out-of-stock listing replacement so nothing ever promotes an unavailable item.
• Offsite is where the non-self-serve advertiser gets activated. Osmos's offsite retail media extends your first-party audiences into Meta, Google, and TikTok in one white-labelled interface, as a walled garden, with markup-based, value-segmented monetization.

Underneath both, a demand layer runs real-time competition across demand sources, so activating new demand grows yield instead of cannibalizing it.

How the build options compare

Choosing how to power a food-commerce ad business is a category-level decision before a feature-level one. The table below sets Osmos's full-stack approach against four capable alternatives. Each does something genuinely well; the question is how much of the business you want to own as one system versus assemble from parts.

The pattern is consistent: each alternative solves one slice, demand, ad serving, the auction, or marketplace operations, and leaves the retailer to assemble the rest. The demand gap closes fastest with one system that runs onsite activation, offsite extension, and attribution together.

Frequently Asked Questions

How does retail media work for a small or budget-constrained restaurant or seller on a marketplace?

It works because the format removes both the cost floor and the effort floor. Sponsored product and listing ads are auto-assembled from the merchant's existing listing, so there is no creative to produce, and with automated product selection and hands-off bidding, a small restaurant can launch in minutes and cap spend at a level it controls. Pilot ticket sizes in the category run as low as $5K to $20K per advertiser (The Retail Exec, 2025), and because marketplace sellers invest a larger share of GMV in advertising to buy the visibility they cannot assume, the small merchant is often a higher-propensity advertiser than their size suggests. The platform's job is to make starting effortless; the budget takes care of itself.

What do successful food-delivery retail media case studies look like?

The strongest recent examples are about net-new customer acquisition and measurable return, not vanity reach. In DoorDash's June 2026 disclosures, first-time customers accounted for over 20% of restaurant sales and over 36% of CPG sales on campaigns, a LiveRamp clean-room study found more than 80% of consumers reached were new to the advertiser's customer base, and a named restaurant advertiser, Pubbelly Sushi, generated $300,000-plus in sales over nine months at more than $4 returned per $1 spent (DoorDash, June 2026). The pattern for meal-kit, restaurant, and CPG advertisers is the same: the platform's first-party data reaches buyers the advertiser could not find alone, and closed-loop measurement proves it, which is what keeps them spending.

How is attribution measured for food-delivery and marketplace retail media?

Through closed-loop attribution. Closed-loop attribution is measurement that connects an ad impression or click to a real purchase in the same platform's transaction data, closing the loop between exposure and sale. Because a food-commerce platform owns both the ad event and the checkout, it can report actual return per campaign rather than modeled estimates, onsite with deterministic order-level matching, and offsite with user-level, last-click attribution plus clean-room techniques for net-new-customer analysis. Measurement is consistently the top objection advertisers raise before committing real budget, so provable attribution is not a reporting nicety; it is the thing that converts a testing budget into a reallocated one. For the full measurement methodology, see our hub, Closed-Loop Attribution in Retail Media: The 2026 Measurement Playbook.

How do retail media offerings differ across food-delivery platforms?

They differ mainly in surface mix and offsite maturity: some lead with sponsored listings and homepage placements, others (DoorDash, via Symbiosys) have pushed hard into offsite and clean-room measurement, and quick-commerce apps lean on search placements and basket-level targeting. The common core is the same, first-party purchase data as the targeting layer, an auction across competing sellers, and closed-loop attribution. For a platform-by-platform comparison of DoorDash, Uber Eats, Instacart, and Grubhub ad formats and monetization models, our spoke Food Delivery Retail Media: How DoorDash, Uber Eats & Instacart Monetize (2026) carries the full breakdown.

What ad products does Uber Eats' retail media program offer?

Uber's advertising business spans sponsored placements inside Uber Eats (sponsored items and in-app placements) alongside offsite and Journey Ads across the wider Uber platform, targeted with first-party delivery and mobility data. Uber has said its advertising business crossed roughly a $2 billion annualized revenue run rate in late 2025, having moved past its earlier internal target of about 2% of delivery gross bookings, with restaurant delivery the strongest area of demand and enterprise advertiser growth now outpacing SMB growth (management commentary, Q4 2025). For a retailer, the read-through is that even a platform at Uber's scale describes advertising penetration as still early relative to the opportunity, which is the activation gap restated at the top of the market.

What are DashMart Ads and how do they work?

DashMart is DoorDash's own network of delivery-only convenience and grocery stores, and ads there work like any onsite retail media surface: sponsored placements on product listings, auction-priced, targeted with DoorDash's first-party purchase data, and measured with closed-loop attribution. Because DashMart inventory is first-party stocked rather than restaurant-fulfilled, it behaves more like a grocery e-commerce ad surface than a restaurant one. A deeper, DashMart-specific breakdown of formats and mechanics is planned as a dedicated companion piece; for now, treat it as onsite grocery retail media inside the DoorDash ecosystem.

What are the mechanics of running a food-delivery platform ad, and how is AI changing it?

Mechanically, an advertiser (or the platform on its behalf) sets a budget and targeting, the platform runs a real-time auction among competing sellers for each shopper and query, the winning ad is served and auto-assembled from the listing, and the resulting click or order is attributed back through the platform's own transaction data. AI is compressing the human effort at nearly every step: automated product selection from dozens of signals, hands-off bid optimization, and auto-bidding "smart" campaigns. DoorDash reported that in February 2026 testing, more than 95% of its auto-bidding Smart Campaigns exceeded their minimum ROAS targets (DoorDash, June 2026). For a platform, that automation is what makes activating a long tail of low-sophistication advertisers economically viable at all.

Can I compare ad options across DoorDash, Uber Eats, and Grubhub in one place?

Yes. A side-by-side comparison of formats, monetization models, and vendor infrastructure across DoorDash, Uber Eats, Instacart, and Grubhub lives in our companion spoke, Food Delivery Retail Media: How DoorDash, Uber Eats & Instacart Monetize (2026), which includes the full platform-by-platform table and the step-by-step monetization ladder. This hub focuses on the level above the comparison: the demand gap those platforms are all racing to close, and how a retailer closes it deliberately.

Sources

1. DoorDash Investor Relations, "DoorDash Ads Becomes a Global Commerce Media Platform," June 2026
2. Instacart Investor Relations, "Instacart Announces First Quarter 2026 Financial Results," May 2026
3. Grab, "Grab Reports First Quarter 2025 Results," April 2025
4. Grab, "Grab Reports First Quarter 2026 Results," May 2026
5. Storyboard18, "Zepto clocks over 2x growth in advertising revenue to Rs 1,636 crore in FY26," June 2026
6. Storyboard18 / Datum Intelligence, "Blinkit, Zepto, Instamart ad revenue may reach Rs 4,900 crore in 2026," June 2026
7. Total Retail, "Debunking the Myth That Retailers Have a Demand Problem in Retail Media," April 2026
8. Retail Technology Innovation Hub, "John Lewis Partnership teams with Kevel," June 2026
9. The Retail Exec, "How to Launch a High-Margin Retail Media Network in 90 Days," 2025
10. eMarketer, "FAQ on commerce media: How to capitalize on growth beyond retail," January 2026
11. eMarketer, "Retail Media Ad Spending Forecast H1 2026," May 2026
12. Marketplace Pulse, "Amazon Percent of Units by Third-Party Sellers 2004-2026," 2026
13. Forrester Consulting, "Unlocking growth: How retail media networks and marketplaces drive profitability" (study commissioned by Mirakl), March 2025. https://www.mirakl.com/blog/how-retail-media-networks-marketplaces-drive-profitability-forrester-study
14. Topsort, "Best Retail Media Platforms for Commerce Operators," May 2026. https://www.topsort.com/post/best-retail-media-platforms

Note on sourcing: neutral analyst, trade, and platform-disclosure sources are cited inline and hyperlinked above. Entries 13 and 14 sit on vendor domains and are referenced only for their own first-party facts (the Forrester Consulting demand-gap study they host or publish); they are left unlinked by design. The widely reported Uber advertising run-rate figure is attributed in-text to Uber management commentary from its Q4 2025 earnings call and stated as disclosure rather than linked, because the third-party transcript originally carrying it is no longer reachable at a stable URL.