Advertiser performance is retail media revenue

Advertisers allocate budgets to channels that prove results. If your platform can't demonstrate measurable ROI, budgets go elsewhere. This isn't a sales problem. It's a performance infrastructure problem.

Many retail media platforms lead with a list of ad formats. But advertisers buy results, not formats. Having Sponsored Products, Sponsored Brands, and Display only matters if the campaigns running on them perform.

Many platforms stay below 1% A2G. The difference between those that break through and those that don't isn't inventory or ad load. It’s whether the underlying technology can turn shopper signals into outcomes advertisers can measure and reinvest in. {[data-attribute="init-tooltip"][tooltip-content="<p>Source:<br><br>Moloco internal data, as of April 2026. A2G (advertising spend as a percentage of gross merchandise value, "GMV") is measured as total ad spend / total GMV during weeks 3-6 following each customer's commercial launch on Moloco MCM (their first billing date), excluding the first two weeks to remove soft-launch ramp. Sample: 24 MCM customers, measured at the contractual-customer level, that had completed six weeks of activity by April 2026. The substantial majority began below 1% initial A2G.</p>"]}

Enterprise brand deals don't run through self-serve auctions. They're sold on insertion orders with committed placements. Reserved Display brings that business onto the same platform as your auction demand, unifying impression-guaranteed buys, Cost-Per-Time sponsorships, and performance campaigns under shared infrastructure and measurement.

Guaranteed reach for committed budgets

Offer Impression-guaranteed and time-based (CPT) buying for the brands that plan quarters ahead and pay for certainty.

Direct sales and auction demand, one system

Your ad sales team sells sponsorships; your long tail self-serves performance campaigns. Both run on shared infrastructure, measurement, and controls.

Moloco Commerce Media closes the loop from impression to purchase: SKU-level attribution over a configurable window, direct and total ROAS across an advertiser’s catalog, and reporting broken out by the dimensions buyers actually plan against. For the platforms and brands that demand more, our holdout-based incrementality framework can help quantify the effectiveness of ads for the platform and for advertisers.



SKU-level details

Attribution at the item level captures direct conversions and same-account halo purchases so ROAS claims hold up to a brand's own analytics team.

Forecasts before the commitment

Pre-launch estimates of impressions, clicks, and purchases, plus guidance on budgets and targets, reduce abandoned setups and misconfigured campaigns.

Reporting that builds advertiser confidence

Reporting is broken out by the dimensions advertisers actually plan against — SKU, campaign, audience, and time period — so performance conversations move from "trust us" to "here's the data."



Your dedicated models update every two hours, learning from actual results to stay accurate as shopper behavior shifts. The system makes over 190 billion real-time predictions a day across the platform, delivering personalized ads with a response time under 100ms for 95% of requests. That’s fast enough that you don't have to sacrifice load time for monetization. And it’s built entirely on first-party data: no third-party cookies, without pooling data across retailer environments. Just your data, working only for you. {[data-attribute="init-tooltip"][tooltip-content="<p>Source:<br><br>Moloco internal data. Analysis of machine learning (ML) model predictions executed in real time while serving ad requests during the week of June 1 to June 7, 2026. ML prediction counts are derived from auction records rather than measured directly: each ad request invokes one user-context model inference, and each ad evaluated in an auction invokes a fixed number of scoring inferences determined by its ad format. Sponsored Product ads invoke two scoring inferences per ad evaluated, one click-through-rate (CTR) and one conversion-rate (CVR) prediction; all other ad formats are counted with one inference per ad candidate, the most conservative estimate. Only inferences executed in real time at request serving are counted; computations performed in advance of ad requests are excluded. Figures are based on sampled internal auction logs (10% sample, scaled accordingly) and averaged to a daily figure.</p>"]}

Optimization without the ops burden

Our AI automates keyword targeting, product selection, bid management, and campaign optimization — continuously, without manual intervention. As your catalog changes, categories launch, or seasonal dynamics shift, the system adapts automatically.



Serving that protects the shopper

Ad quality algorithms throttle low-relevance ads and filter weak matches out of search results, so yield can grow while protecting the shopper experience.

Scale you don’t have to manage

Our infrastructure scales automatically with inventory growth, catalog expansion, and traffic spikes, including high-concurrency events — all without manual management.