Target's profits doubled in its latest quarterly results, and the retailer is crediting two specific businesses for the streak: Roundel, its retail media network, and same-day delivery. That's the headline out of Target's own accounting of its growth.

The detail worth sitting with here isn't the topline number — it's the mix. A big-box retailer whose core business is groceries and general merchandise is now pointing to an advertising unit and a logistics capability as its profit engines. Neither of those exists without heavy investment in software and, increasingly, AI-driven systems.

According to Adweek, Roundel and same-day delivery are the two levers Target is naming as it extends its growth streak. That combination — ad revenue plus fulfillment speed — is becoming the standard playbook across retail, and it's worth unpacking why.

Retail media is now a profit center, not a side project

Roundel launched as Target's answer to Amazon Advertising: a way to sell ad placements on Target.com, in-app, and increasingly off-platform, using the retailer's first-party purchase data. What makes retail media attractive to a company like Target is margin — selling ad inventory built on data you already own costs far less than selling another unit of inventory off a shelf.

• Retail media networks monetize first-party shopper data that retailers already collect at checkout and online.
• Margins on ad revenue typically run well above margins on physical merchandise sales.
• Roundel's growth mirrors a broader industry shift: Amazon, Walmart, Kroger, and Instacart have all built comparable ad businesses in the past five years.

None of this runs on manual ad-ops. Retail media at scale depends on automated bidding, audience segmentation, and real-time inventory allocation — the same category of machine learning infrastructure that powers programmatic advertising generally. The mechanics of any retail media network at Roundel's scale are, in our estimation, likely leaning harder on automated targeting and measurement each year, simply because manual ad placement doesn't scale to millions of SKUs and shoppers.

Same-day delivery as the other half of the equation

The second driver Target names is same-day delivery, which for Target runs primarily through Shipt and its Drive Up curbside service. Pairing an ad business with same-day fulfillment is not incidental — advertisers pay more for placements that can be tied to a purchase within hours, and same-day logistics is what makes that closed loop measurable.

That pairing also explains why Target frames these two businesses together rather than separately. An ad impression that converts into a same-day pickup order is easier to attribute and easier to sell to a CPG brand's marketing budget than a display ad with a vague, multi-week attribution window.

What this means for teams building on top of retail data

For AI builders and marketing technologists, the practical signal isn't about Target specifically — it's about where retail budgets are heading. A handful of implications follow directly from the growth pattern Adweek is describing:

• Retail media ad-tech (bidding, creative optimization, measurement) is a growing budget line, which means demand for teams that can build or integrate targeting and attribution tooling.
• First-party data monetization is becoming a core retail strategy, raising the bar for privacy-safe data infrastructure and clean-room style measurement.
• Fulfillment-linked attribution — connecting an ad exposure to a same-day order — is a harder measurement problem than standard e-commerce attribution, and it's an open space for better tooling.

Any vendor selling into retail media — from ad servers to recommendation engines to measurement platforms — should read a "profits double" headline attached to Roundel as a signal that retailers are willing to keep funding this category, not cut it.

AiiN's takeaway

The story Adweek is telling isn't primarily an AI story — it's an earnings story. But it's a useful reminder that the businesses retailers now lean on for profit growth, advertising and fast fulfillment, are both fundamentally software problems that reward automation at scale. Target didn't double its profits by selling more T-shirts; it did it by getting better at selling ad placements and getting orders to doorsteps faster. Both of those are engineering problems before they're retail problems, and that's exactly the kind of shift worth tracking if you build tools for either side of that stack.