Media.net announced on April 23, 2026, a partnership with Fetch, the consumer rewards app, that routes verified purchase data from physical and online retail transactions directly into the sell-side of the programmatic advertising supply chain. The arrangement positions Fetch as the inaugural data partner inside Media.net's curation infrastructure and introduces two distinct product tracks - one for audience activation and one for campaign measurement.

The announcement arrives at a moment when advertisers are pressing hard on measurement quality. Clicks and impressions have long served as the primary performance proxies across the open web, yet neither metric reliably answers the question of whether a campaign influenced an actual sale. Media.net is attempting to address that gap by bringing observed, item-level transaction data into the targeting and measurement layer on the supply side rather than relying on inferred intent signals assembled downstream.

What Fetch brings to the table

Fetch operates as a rewards platform where consumers scan grocery and retail receipts in exchange for points redeemable for gift cards and other incentives. That mechanic generates a dataset with specific characteristics that distinguish it from other commerce data sources. According to the announcement, the platform processes more than 13 million receipts every day, accumulating a gross merchandise value of $212 billion annually.

Because Fetch captures receipts rather than card transactions, the data spans payment methods - debit, credit, cash, buy-now-pay-later - and covers both online and in-store purchases. It is also retailer-agnostic, meaning a single consumer profile can reflect purchasing behavior across grocery chains, drug stores, mass merchandisers, and specialty retailers without requiring any direct data relationship with those retailers. That cross-retailer, cross-category view is what Media.net is describing as commerce intelligence layered on top of contextual signals already present in the supply chain.

SELECT for Commerce: activation through curation

The first product track is SELECT for Commerce, Media.net's curation platform. Curation in programmatic advertising refers to the practice of enriching inventory with data and packaging it into curated deal IDs at the supply-side layer, which buyers can then access through their demand-side platforms without requiring separate bilateral data integrations. The approach has gained significant traction across the industry as match rate concerns at the DSP level have pushed more data activation upstream toward publishers and SSPs.

Through SELECT for Commerce, Media.net is integrating Fetch's audience segments - built from verified transaction histories - into the curation platform. Advertisers and curators can then access those audiences as targeting inputs when building deals. The distinction being drawn here is between audiences constructed from inferred purchase intent and audiences constructed from observed purchase behavior. Browsing a product page suggests interest; scanning a receipt after buying the product confirms it.

Combined with Media.net's SearchSignals product, which surfaces user intent derived from search activity, the system is designed to let a buyer stack two different signal types inside a single curated deal: what someone has already purchased and what they are actively looking for. The combination is particularly relevant for categories with high purchase frequency - consumer packaged goods, household products, personal care - where recency of the last purchase is a meaningful predictor of when the next purchase cycle begins.

According to Karan Dalal, COO of Media.net, "Advertisers are moving beyond proxies and looking for signals that reflect real consumer behavior. What makes this partnership with Fetch especially compelling is the ability to bring observed purchase data into both activation and measurement, lighting up a clearer connection between media exposure and business outcomes on the open web."

The architecture here places Fetch's data on the sell side rather than the buy side, which has a technical implication worth noting. As documented across the programmatic curation space, applying audience data at the SSP layer means the match operation happens once, at the point of inventory packaging, rather than being re-attempted each time a bid request passes through a new intermediary. Every sync between platforms introduces match rate degradation - industry analyses have put those losses at between 40% and 70% per hop. Keeping the data on the sell side and packaging it into a deal ID is one way to limit that attrition.

The CTV channel is explicitly called out in the announcement as a target use case. That matters because CTV has long struggled with closing the attribution loop, with cross-device identity and the absence of click-based conversion signals making it difficult to connect impressions on a television screen to purchases made later through other channels. Bringing receipt-level purchase data into CTV targeting at the supply side is one approach to that problem, allowing advertisers to reach audiences whose prior purchasing behavior matches a campaign's target profile even when online behavioral signals are absent or restricted.

ELEVATE for Measurement: clean-room attribution

The second product track is ELEVATE for Measurement, Media.net's sell-side measurement offering. Where SELECT concerns the activation side - who gets targeted - ELEVATE concerns the outcome side: did the impression lead to a purchase?

The mechanism involves Fetch's transaction data being processed inside a privacy-safe clean-room environment. Media.net can then compare campaign exposure records against purchase activity without either party obtaining user-level transaction data from the other. The clean-room model - which has proliferated across the advertising industry as a response to third-party cookie deprecation and tightening privacy regulation - allows aggregated analysis of the relationship between ad exposure and subsequent purchase while maintaining privacy controls at the individual record level.

What ELEVATE adds beyond a standard exposure-to-purchase match is the sell-side context. According to the announcement, the system evaluates which signals surrounding an impression - context, placement, publisher, and intent - are actually influencing performance. That produces a different kind of output than simple attribution. Rather than confirming that a campaign reached purchasers, it begins to identify which inventory environments and signal combinations are most associated with conversion activity. Over time that feedback can inform future curation and targeting decisions.

According to Daniel Block, GM, Data Revenue and Partnerships at Fetch, "As one of the most robust sources of verified purchase behavior data, we know how powerful real purchase signals can be for marketers. This partnership with Media.net brings those signals into the open web to make targeting and measurement more grounded, actionable, and reflective of actual consumer behavior."

The privacy architecture is notable because receipt data is among the more sensitive types of consumer information available. A receipt captures not just what category someone buys in but the specific products, quantities, prices, and store locations involved. Managing that data inside a clean room - where Media.net cannot directly access individual transaction records and where the output is restricted to aggregated measurement results - is the mechanism by which the partnership claims to preserve consumer privacy while still generating actionable campaign intelligence.

Where this sits in the broader market

The Media.net-Fetch arrangement is one of a wave of commerce data partnerships now moving through the programmatic supply chain. Retail media networks have been expanding off-site programmatic access through similar structures, using purchase data from retailer loyalty programs and transaction records to enrich inventory sold through SSPs and curation layers. Expedia's recent deal with Magnite, announced on April 16, 2026, follows the same architectural logic: a data-rich company makes its signals available through supply-side infrastructure in a DSP-agnostic structure, accessible via curated deal IDs.

What distinguishes the Fetch partnership is its breadth. Retail media programs typically deliver purchase signals from a single retailer's customers, and travel-platform data reflects a single category. Fetch's cross-retailer, cross-category receipt data covers consumer spending patterns across dozens of retail environments simultaneously. That horizontal view of purchasing behavior is harder to replicate through a single-retailer data relationship, and it extends the relevance of the signal beyond advertisers whose products are sold primarily through any one chain.

The announcement also describes Fetch as the "inaugural partner" in a broader commerce-data strategy for Media.net, signaling that the SELECT for Commerce framework is designed as a repeatable structure for onboarding additional commerce data providers rather than a one-off integration. That framing positions Media.net not simply as a publisher monetization platform but as a marketplace for verified purchase signals accessible to advertisers operating across the open web.

The demand-side context for this kind of infrastructure is clear. Brands that previously relied on third-party behavioral data for audience construction are now navigating an environment where that data is less available, less accurate, and under greater regulatory scrutiny. First-party data from retailers and rewards platforms represents one of the few remaining sources of directly observed purchase behavior at scale, and its migration into programmatic infrastructure - through curation, clean rooms, and sell-side measurement - is an active area of development across the industry.

The open web dimension is significant because much of the momentum in commerce data integration has concentrated inside closed ecosystems - Amazon Marketing Cloud, retailer clean rooms, and walled-garden measurement tools. Moving verified purchase signals into open web targeting through an SSP-adjacent curation layer addresses a gap that has made it difficult for advertisers to apply commerce intelligence outside of retail media network environments. Whether this produces measurably different campaign performance from existing targeting approaches is a question that ELEVATE's measurement capabilities will presumably be designed to answer over time.

Timeline

Summary

Who: Media.net, the digital advertising and contextual technology company, and Fetch, a consumer rewards app and outcomes-based advertising platform with item-level purchase data across online and in-store retail.

What: A data partnership that integrates Fetch's verified purchase signals into two Media.net products - SELECT for Commerce, a curation platform enabling sell-side audience activation built from real transaction behavior, and ELEVATE for Measurement, a sell-side measurement offering that connects campaign exposure to actual purchase outcomes through a privacy-safe clean-room environment. Fetch is named as the inaugural partner in a broader commerce-data strategy for Media.net.

When: Announced April 23, 2026.

Where: The integration operates across the open web through Media.net's programmatic infrastructure, covering display, video, connected television, and audio inventory. Fetch's data reflects purchases made across online and in-store retail channels, agnostic to retailer and payment method.

Why: Advertisers across the open web have limited access to verified purchase behavior at the level of targeting and measurement, with most commerce data concentrated inside closed retail media network environments. Media.net's stated aim is to bring observed transaction signals - rather than inferred behavioral proxies - into the sell-side supply chain, giving advertisers a more direct path from impression to measurable purchase outcome without depending on walled-garden infrastructure.

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