Welcome to the July 2026 edition of the Retail Roundup, your go-to recap of the most significant developments shaping retail media, marketplaces, and e-commerce strategy.
This month brought a concentrated wave of updates across Amazon, Instacart, and Walmart Connect.
Here are the highlights:
- Amazon Mandates Labels for AI-Generated People: Brands must now tag photorealistic synthetic models in listings and A+ content using hidden IPTC metadata.
- Amazon DSP Unlocks Omnichannel Metrics: Always-on, retailer-level attribution reveals how Amazon ad spend drives off-Amazon sales at Walmart, Target, and beyond.
- Featured Offer Pre-Screening Criteria Removed: Amazon eliminates seller eligibility gates for the Buy Box, opening consideration to all sellers as agentic AI search evolves.
- Returnless Resolutions Target Low-ASP Returns: Automated instant refunds let FBA sellers curb profit loss on cheap items.
- Instacart Debuts "Immersive Feed": Shoppable vertical video comes to grocery to drive cross-aisle discovery and co-branding.
- Instacart Acquires Arpalus for Real-Time Shelf Intelligence: Computer vision and 600,000 gig workers map physical store inventory to tackle out-of-stock issues.
- Walmart Acquires Vibe.co & Adds Negative Keywords: CTV access expands for SMBs while Sponsored Products search finally gains negative keyword targeting.
Let's dive in.
1. Amazon Mandates Disclosure for AI-Generated People
Amazon has introduced strict new requirements around labeling photorealistic AI-generated human models in product imagery and A+ Content. Driven largely by maturing global AI governance and state-level legislation like New York's commercial advertising disclosure laws, Amazon is putting compliance guardrails directly on sellers.
Under the new policy, if your creative team uses AI to create completely fake, photorealistic humans, you must disclose it prior to uploading. The requirement involves using an IPTC-compatible metadata editor to add the keyword "contains-synthetic-performer" into the dc: subject (XMP) field of the image or video file.
There are notable exceptions. If you use a real human model and apply AI tools to swap the background or adjust lighting, no tagging is required. The rule also excludes cartoons, 3D renders, movie or video game characters, and images with no people at all.
While adding metadata introduces operational friction for design teams, Amazon has simplified the process for A+ Content by adding a quick "AI-generated people" checkbox directly inside the A+ Content Manager.
Pros
- Protects customer trust by ensuring transparency around photorealistic synthetic images.
- Clear policy exceptions safeguard standard workflow enhancements like background swaps on real human models.
- The A+ Content Manager checkbox offers a low-lift workaround compared to editing file-level metadata manually.
Cons
- Creates operational bottlenecks and extra SOP steps for design teams using generative AI models.
- Amazon places enforcement liability entirely on the seller if compliance issues or audits arise.
💡 Tips
- Audit your catalog immediately: Identify every active listing and asset that uses full AI-generated human models.
- Update creative SOPs: Train design and content teams to embed the "contains-synthetic-performer" IPTC tag during asset export.
- Use the A+ Content shortcut: Skip manual metadata editing for A+ Content by checking the native AI-generated box during upload.
2. Amazon DSP Unlocks Granular Omnichannel Metrics
In what is being hailed as a major breakthrough for omnichannel brands, Amazon Ads has expanded its Omnichannel Metrics (OCM) reporting inside Amazon DSP. For the first time, Hardlines and Fashion & Lifestyle advertisers can see exact, named retailer-level breakouts showing where their Amazon DSP investments drive off-Amazon sales.
Instead of receiving a generic off-Amazon sales aggregate, brands can now view granular metrics, including sales volume, unit counts, market share, and average selling prices (ASP), across specific competitors such as Walmart, Target, Home Depot, Best Buy, and Nordstrom. Amazon powers this always-on capability by combining its first-party Amazon Shopper Panel data with third-party exposure signals to match ad-exposed shoppers with their real-world purchases.
This solves a long-standing "white whale" for advertisers who previously spent hundreds of thousands of dollars on custom Media Mix Modeling (MMM). By demonstrating incremental cross-channel lift directly inside the Ad Console for free, brands can reshape budget conversations with CFOs and alleviate channel conflict with retail partners. Furthermore, it positions Amazon DSP as a unified, one-stop shop for off-site media consolidation.
Pros
- Provides free, always-on attribution across major retail competitors without expensive third-party modeling.
- Gives clear proof of upper-funnel media incrementality to defend ad budgets to finance leadership.
- Lays the groundwork for future Amazon Marketing Cloud (AMC) integration to build custom audiences based on off-Amazon shopping habits.
Cons
- Exposure-based panel attribution is directionally powerful, but relies on sample matching rather than 100% deterministic tracking.
- Rollout is currently focused on eligible hardlines, fashion, and lifestyle categories running DSP campaigns.
💡 Tips
- Review your Insights tab: Access your OCM report directly inside the Amazon Ad Console under the DSP study section with zero setup required.
- Leverage data for retailer conversations: Use retailer breakouts to prove to retail partners that Amazon DSP spend actively drives foot traffic and sales to their stores.
- Prepare for AMC capabilities: Stay ready to build retargeting and suppression audiences once cross-retailer signals land natively in AMC.
3. Amazon Removes Pre-Screening Checks for Featured Offer Eligibility
Amazon is eliminating seller account performance pre-screening criteria for Featured Offer (Buy Box) eligibility. The global rollout began in July 2026 and will be completed by the end of the year.
Previously, Amazon used a two-step system where sellers had to pass strict account metrics checks, such as order volume, chargeback rates, and Voice of the Customer (VOTC), just to earn the right to compete for the Buy Box.
Under the new policy, every seller listing a product is automatically eligible and considered. However, the winning algorithm itself has not changed: competitive pricing, fast fulfillment speed, and solid performance remain mandatory to actually win the placement.
This update signals a deeper architectural refactoring of Amazon’s backend database. Amazon is transitioning away from a system designed for human curation toward an architecture optimized for agentic commerce. In an agentic framework, API queries from AI agents searching for the "best price" need to evaluate the entire marketplace instantaneously rather than querying a pre-approved seller list.
Pros
- Removes administrative pre-screening hurdles and gated barriers for compliant sellers.
- Prepares marketplace architecture for the rise of AI shopping agents and conversational commerce.
- Ensures true marketplace price discovery across all active listings.
Cons
- Expands the pool of eligible offers, increasing competitive density for the Buy Box.
- Automatic eligibility does not guarantee Buy Box impression share if price or ship speeds lag.
💡 Tips
- Double down on core execution: Maintain sharp competitive pricing and fast fulfillment, as algorithm selection rules remain strictly performance-based.
- Optimize for agentic AI: Ensure backend SKU data and real-time pricing feeds are pristine so automated AI buying agents evaluate your offers favorably.
4. FBA Launches Returnless Resolutions to Save Margins on Cheap Returns
Logistics costs on cheap returns have long quietly eroded seller margins, as paying $8 to $12 to ship back a $5 item makes little financial sense. Amazon has addressed this with Returnless Resolutions, a free program for Professional FBA sellers.
Returnless Resolutions allows sellers to set automated refund rules in Seller Central based on price thresholds, product categories, or specific return reasons. When a return request meets the established criteria, the customer receives an immediate refund and keeps the item.
This eliminates return shipping, inspection, and restocking overhead while resolving customer disputes instantly, often preventing negative 1-star reviews that harm organic rank. However, the program requires strategic management. Broadly defined rules invite customer exploitation, transforming a cost-saving tool into a profit leak.
Pros
- Eliminates wasteful return shipping and processing fees on low-ASP items.
- Delivers instant customer satisfaction, curbing negative reviews and protecting organic rank.
- Gives sellers full control to adjust thresholds, categories, and return reasons as margins shift.
Cons
- Not a set-and-forget scenario. If you leave your rules too broad, scam-savvy shoppers will find the loophole, and a cost-saving tool can quickly become a profit leak.
- Requires active, ongoing monitoring at the ASIN level to prevent sudden spikes in claims.
💡 Tips
- Be Selective: Don't turn this on for your entire catalog. Use it strictly for low-ticket items, consumables, or products where return shipping wipes out your profit margin.
- Filter by Return Reason: Don't rely only on a dollar threshold. Differentiate between a shopper who 'changed their mind' versus received a 'defective' product.
- Monitor Abuse by ASIN: Keep an eye on your return metrics weekly. If one product suddenly sees a spike in claims, tweak the rules immediately before your catalog turns into a free sample station!
5. Instacart Expands into Vertical Video and Physical Shelf Tech
Instacart made two major strategic moves this past month spanning ad formats and in-store technology:
1. Instacart Debuts "Immersive Feed" for Shoppable Vertical Video
Instacart debuted "Immersive Feed," a shoppable vertical video ad unit designed to mirror the mobile-first experience of Instagram Reels or TikTok.
Recognizing that search is highly efficient for lower-funnel intent (e.g., searching for a protein bar returns a protein bar), Instacart is introducing video formats to drive mid- and upper-funnel discovery across aisles.
For example, a shopper searching for ice cream might see an inspiring vertical video showing a protein yogurt frozen onto a popsicle stick, persuading them to shop in a new category. The unit also facilitates brand co-branding opportunities.
Pros
- Lowers asset creation barriers by allowing brands to repurpose existing social media vertical video content.
- Expands brand reach beyond saturated search categories into cross-aisle discovery.
- Creates collaborative co-branding opportunities across complementary products.
💡 Tips
- Repurpose social creative: Leverage high-performing TikTok or Reel assets on Instacart to test Immersive Feed with minimal upfront production cost.
- Focus on cross-aisle usage: Show creative product applications (like recipe hacks or frozen treats) to pull shoppers into non-traditional search categories.
2. Instacart Acquires Arpalus for Real-Time Shelf Intelligence
On the physical retail side, Instacart acquired computer-vision startup Arpalus to solve online grocery’s biggest pain point: out-of-stock substitutions. There is nothing worse than ordering a favorite snack only to receive a text that it was replaced with an unwanted alternative.
Using advanced computer vision, Instacart’s network of over 600,000 gig workers and camera-equipped Caper Carts scan store shelves in real time while picking orders or navigating aisles.
This essentially creates an army of inventory robots mapping physical store stock, closing the long-standing disconnect between physical shelves and digital catalogs
Pros
- Real-time shelf visibility reduces out-of-stock substitutions, preserving customer trust.
- Gives brands granular visibility into localized stockouts to fix supply chain bottlenecks.
Cons
- Computer vision algorithms can struggle on crowded or dark shelves if packaging lacks visual distinction.
- When all of this data becomes available, you can't hide behind slow inventory updates anymore, but that is a massive opportunity for prepared brands.
💡 Tips
- Design packaging for AI vision: You need to think about your packaging for AI, not just for humans. If your product looks exactly like your competitor's on a crowded, dark shelf, the computer vision might struggle. Make your branding and colors stand out boldly so the camera catches it easily.
- Act on inventory data: Once this real-time shelf data becomes available, you must use it! Don't just look at it. If the data shows your product is always out of stock by Friday afternoon, you need to talk to the retailer and fix your supply chain.
6. Walmart Connect Gets a Makeover: Vibe.co Acquisition & Negative Keyword Controls
Walmart Connect is executing a major digital makeover to close the gap with Amazon Ads and differentiate itself from rival retail media networks.
First, Walmart agreed to acquire French startup Vibe.co for a reported $1.4 billion to expand Connected TV (CTV) ad access to mid-market advertisers and SMBs. Vibe, often called the "Google Ads of streaming", allows marketers to launch CTV campaigns in under five minutes with access to 500+ premium channels and live sports leagues.
Crucially, Vibe Studio uses AI to generate on-brand video ads from a URL or prompt in under two minutes, eliminating high production cost barriers for smaller advertisers.
Second, Walmart Connect officially rolled out negative keyword targeting for Sponsored Products partners. Advertisers can now utilize exact and phrase negative match types across Auto and Manual campaigns. Marketers no longer have to perform complex account "backflips" to ensure ad spend isn't wasted on irrelevant or non-branded queries.
Pros
- Vibe.co Acquisition: Democratizes CTV advertising by solving high production costs and complex setup hurdles through instant AI video creation.
- Negative Keywords: Brings long-overdue keyword precision to Walmart search, reducing wasted ad spend and preventing self-cannibalization on non-branded terms.
- Signal of Walmart’s commitment to building a modern, competitive, and accessible digital ad tech stack.
Cons
- Negative keywords were table stakes across other major ad platforms for years. While this is a welcome change, the gap is still wide when compared to Amazon.
💡 Tips
- Implement negative match types immediately: Audit Sponsored Products campaigns and negate irrelevancies to instantly optimize ad efficiency.
- Test CTV for mid-market portfolios: Leverage Vibe’s automated AI video generation to test streaming TV placements without traditional six-figure production overhead.
Final Thoughts
July highlighted a distinct divergence in platform focus. While Walmart Connect is modernizing foundational search capabilities such as negative keywords, Amazon is advancing into next-generation capabilities such as omnichannel DSP attribution and agentic database architecture.
Meanwhile, Instacart is demonstrating how physical shelf computer vision and vertical video discovery can converge to transform the grocery journey.
Our advice for brands is to try to stay nimble - adapt creative workflows for AI transparency, harness new cross-channel DSP signals, and maintain tight operational standards as these retail ecosystems evolve.
Subscribe for More!
We publish a new Retail Roundup every month. Stay in touch on LinkedIn to keep track of the most important changes in the Retail media landscape.
Give It a Listen
You can tune in for the full interview with Armin Alispahic and Damiano Ciarrocchi next week on the Ecommerce Braintrust hosted by Julie Spear and Jordan Ripley.
This show gives you access to the world's best brains when it comes to building momentum online for established consumer brands. Join in and listen to discussions with expert guests about e-commerce strategies, trends, and innovations.
Read more from this author: