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Welcome back to the Retail Roundup, your monthly recap of the biggest developments shaping retail media, marketplaces, and eCommerce strategy.
This month, the defining theme is clear: control. Amazon is systematically positioning AI as a permanent intermediary layer between shoppers and brands, on both the frontend discovery and backend campaign levels.
Meanwhile, Walmart is taking the opposite approach, partnering on the open web to tie off-site streaming ad exposure directly to its physical and digital checkouts.
Here are the highlights:
- AWS Sells Amazon's Shopping-Assistant Tech to Competitors: The Agentic Shopping Assistant packages Alexa for Shopping's architecture for outside retailers - Kate Spade is the first one live.
- “Researched by Alexa” Reshapes On-Site Search: A new AI research module is pushing shoppers toward specific, attribute-driven queries instead of generic keywords.
- Full Funnel Campaigns Roll Out: Amazon's AI now coordinates budget and bidding across Sponsored Products, Sponsored Brands, and Sponsored Display under one business goal.
- Product Titles Capped at 75 Characters: Amazon's AI will auto-rewrite non-compliant titles starting July 27 unless brands act first.
- AMC's Paid Tables Go Free: Amazon removed the paywall on premium first-party tables like Amazon Insights through December 31.
- Multi-Touch Attribution Arrives Outside AMC: A new reporting toggle credits every ad touchpoint in the path to purchase, not just the last click.
- Sparky Goes Web-Wide, Walmart Connect Links Up With YouTube: Walmart's assistant leaves the app, and first-party purchase data can now measure YouTube ad impact.
- Amazon Tightens the Reins on Resellers and Reviews: New policies restrict who can create ASINs or contact customers after a negative review.
Let's dive in.
1. AI Redefines the Shopper Discovery Journey
Amazon is making a distinct bet that how consumers search for, discover, and purchase products is fundamentally changing. Traditional keyword search and raw catalog browsing are increasingly being replaced by conversational discovery experiences.
AWS Packages its Agentic Shopping Assistant (ASA)
Amazon Web Services (AWS) has launched the Agentic Shopping Assistant (ASA), allowing outside retailers to license the underlying technology that powers Amazon's Rufus and Alexa for Shopping. Built on Amazon Bedrock and Anthropic's Haiku model, Tapestry's Kate Spade Gift Concierge was the first live production deployment. Amazon's pitch is compelling: conversational shopping sessions convert at approximately 3.5 times the rate of traditional keyword search.
"Researched by Alexa" Impacts Keyword Discovery
Shoppers searching on Amazon are increasingly encountering a "Researched by Alexa" module at the top of search result pages. When a user searches for a broad category like "running shoes," Alexa pulls data from external blogs and review sites to summarize the options, such as explaining the differences between cushioned daily trainers, stability shoes, and carbon-plated racing models, and guides the user to click a refined search query. This structural change actively steers users away from broad, high-volume keywords.
The Strategic Core
- The Infrastructure Masquerade: Amazon has always operated as a technology infrastructure company masquerading as a retailer, similar to how it scaled AWS, FBA, and Amazon Retail Ad Services. There's a useful historical parallel here: when Amazon first opened its Marketplace to third-party sellers, many assumed the company was handing its business to competitors. Instead, it grew total selection so shoppers had even more reason to start (and stay) on Amazon. The same logic is playing out with ASA — Amazon isn't trying to be the AI agent for everything, but it is betting that if shoppers want to use an AI agent wherever they search, Amazon should be that agent, even on competitors' sites. Licensing the assistant to other retailers generates a new revenue stream and gives Amazon visibility into search intent happening off its own platform, which feeds back into training its commerce models.
- The Transition to Semantic Search: For brands, this changes the foundation of organic discovery. Shoppers are transitioning from keyword-matching to natural language, semantic queries. Instead of searching for "running shoes," users are asking, "What are the best running shoes for someone with flat feet who runs on concrete?" PDP optimization must focus on the problems a product solves, rather than simple feature lists or keyword stuffing.
📌 SEO on Amazon is no longer a copy-paste job from a keyword tool. We are actively auditing and rewriting PDPs to ensure that when an AI agent summarizes a category, our clients' products are the ones being recommended. No matter how much the algorithms change, success still comes back to driving the right shopper to a page engineered to convert.
Pros
- Conversational interfaces drastically shorten the path to purchase, driving conversion rates up to 3.5 times higher than keyword search.
- Off-Amazon PR, product blogs, and external reviews are now directly indexable by Alexa, helping brands influence on-Amazon discovery from the outside.
Cons
- Broad, high-volume keyword campaigns will experience declining efficiency as Amazon’s frontend actively pushes users toward long-tail, filtered queries.
💡 Tips
- Stop Stuffing, Start Tagging: Populate your backend product attributes and PDP copy with precise, concrete tags ("arch support," "shock absorption," "breathable mesh") rather than generic fluff like "high quality". AI models require these exact facts to place your products into the new frontend filter buttons.
- Audit Your Brand’s Off-Amazon PR: Because "Researched by Alexa" draws details from external blogs and review sites, your off-platform digital footprint is now directly feeding Amazon's on-site search results.
2. Automation Takes Over the Seller’s Operational Levers
On the flip side of shopper discovery, Amazon is increasingly using AI to automate decisions that brand managers, advertisers, and catalog teams used to make themselves.
Full Funnel Campaigns Continue Their Rollout
Amazon continues to roll out Full Funnel Campaigns - an AI-powered campaign type, first previewed at Unboxed 2025, designed to automatically shift budgets and coordinate bidding across Sponsored Products, Sponsored Brands, and Sponsored Display under a single, unified business objective. Rather than managing separate campaigns and bids, advertisers set a high-level goal and let Amazon's AI determine placement across the customer journey.
Product Titles Get Capped at 75 Characters
Effective July 27, 2026, non-media product titles on Amazon must be 75 characters or fewer. To offset the loss of title space, Amazon is introducing "Item Highlights," which provides an additional 125 searchable characters to display product features and materials - enough, if structured well, that brands shouldn't see a meaningful drop in keyword coverage. If titles are not updated by the deadline, Amazon's AI will automatically rewrite them after a 14-day review window.
The Strategic Core
- The "Easy Button" Illusion: Amazon's product updates historically lean on simplicity and ease of use to lower the barrier to entry for smaller brands. However, there is no magic campaign structure that unlocks growth on its own. Ad automation is excellent for handling tedious tasks like real-time bid adjustments, but human strategists are still required to manage consumer psychology, target audiences, and protect conversion rates.
- The Risk of Search Homogenization: If Amazon’s AI is left to rewrite every title to fit a tight 75-character limit, search results pages will look incredibly homogenized. By ceding catalog control, brands risk losing the exact conversion triggers—such as a specific size, ingredient, or compatibility feature—that make a shopper click their listing over a competitor's.
📌 Amazon’s AI is a fantastic co-pilot, but it is not a CMO. It is designed to optimize for Amazon’s efficiency, not necessarily your brand's equity-and those goals are not always aligned. If you let Amazon automate your entire business, your brand will become invisible.
Pros
- Automated full-funnel budget shifting reduces the daily operational overhead of managing separate campaign budgets.
- Item Highlights offer a structured, clean way to display product features without cluttering the main listing title.
Cons
- Early signals suggest Amazon's automated title rewrites can make basic, logic-defying mistakes, such as breaking up critical multi-word search phrases - though the sample size so far is still too small to fully judge the AI's reliability. Human review remains essential in the meantime.
💡 Tips
- Manually Shorten Your Titles Now: Do not wait for Amazon's automated rewrites. Audit your listings and prioritize your top-selling and highly advertised ASINs. Structure shortened titles to preserve whole phrases (e.g., keeping "dried tomato powder" intact rather than letting the AI separate the words) and push secondary specs to Item Highlights.
- Test Full Funnel Campaigns Natively: If you choose to test the new Full Funnel campaign types, do not jump in with your entire budget. Set up a structured, limited-budget test on a subset of products and let performance data prove its viability before scaling.
3. The Democratization of Advanced Attribution
Advanced measurement and multi-touch modeling, once the exclusive domain of enterprise brands with dedicated data science budgets, are now being made accessible to the broader market.
AMC Paid Tables Are Temporarily Free
Through December 31, 2026, Amazon has removed the paywall on its first-party paid-feature tables within Amazon Marketing Cloud (AMC), including Amazon Insights. This unlocks access to organic customer metrics, such as repeat purchase cycles, subscription behaviors, and customer lifetime value (LTV) paths, without incremental query costs.
Native Multi-Touch Attribution (MTA) Reporting
Amazon has added an "Attribution" toggle inside the standard reporting console, allowing advertisers to view multi-touch attribution columns directly in the ad manager. This feature distributes conversion credit across every ad format that a shopper clicked along their purchase path, moving away from the default, last-touch model.
The Strategic Core
- The Moat is Moving: By making AMC tables free and integrating MTA natively, Amazon is standardizing advanced measurement. Data availability is no longer the competitive advantage; the advantage belongs to brands with the strategic agility to translate these multi-touch insights into campaign execution.
- Everyone can now see that a customer clicked a Sponsored Display ad, watched a Video ad, and then finally converted on a Sponsored Product ad. But the question is: what do you actually do with that information? The differentiator moves from measurement to creative and execution. If you know it takes three touchpoints to convert a shopper, your top-of-funnel creative needs to sequence perfectly into your bottom-of-funnel messaging. This is the proof that full-funnel strategy isn't just a buzzword; it's a mathematical requirement to win.
- Mitigating the Last-Touch Bias: Last-touch models have historically penalized upper-funnel and awareness placements, making Sponsored Brands and Sponsored Display appear inefficient. The native MTA columns provide clear visibility into the assist chain, showing which keywords open the customer journey and preventing advertisers from cutting the campaigns that fuel their lower-funnel Sponsored Products conversions.
📌 We've been building full-funnel campaigns based on multi-touch data for our enterprise clients for years. Now that the curtain is pulled back for everyone, we're seeing a lot of brands paralyzed by the amount of data in front of them. The brands that win will be the ones with an agency partner who knows how to translate those MTA columns into actual, real-time campaign restructuring.
Pros
- Native MTA columns allow brands to clearly evaluate how Sponsored Brands and Sponsored Display ads assist overall conversion volume.
- Free access to Amazon Insights tables enables brands to calculate their real customer LTV and return on ad spend (ROAS) beyond standard 7-day windows.
Cons
- Multi-touch data introduces reporting complexity that requires significant analytical resources to utilize effectively.
- Knowing that a conversion requires three touchpoints is only actionable if a brand has the creative resources to sequence its messaging accordingly.
💡 Tips
- Perform a Last-Touch vs. Multi-Touch Audit: Pull a standard 30-day performance report and toggle on the MTA columns. Identify the gap between the two models—this variance represents the ad placements that are acting as critical assists.
- Map Organic Customer Cohort LTV: Leverage the free AMC paid tables before December 31. Analyze how many purchases it takes before a customer subscribes, and evaluate whether low-cost entry-size products are successfully acting as a gateway to your larger variations.
4. Walmart Is Building A Full-stack Commerce Media Flywheel
Amazon spent the last decade building an incredibly lucrative walled garden. Walmart looked at that and decided to build a toll road on the open web instead. This captures the throughline of everything Walmart announced this month - two moves that look like consolidation on one side and expansion on the other, but are really the same strategy: turn first-party data into a flywheel that pulls shoppers back into Walmart's ecosystem, wherever they happen to be.
Sparky Expands to the Desktop Web
Walmart’s generative AI shopper assistant, Sparky, is now available to desktop Chrome users. To encourage user engagement, the desktop floating interface highlights "everyday essentials" and Grocery prompt pills (e.g., meal planning, barbecue ideas). This leverages Walmart's market dominance in Grocery to drive customer discovery across other product categories.
Walmart Connect Integrates with Google DV360 and YouTube
On June 11, 2026, Walmart Connect and Google announced a partnership allowing Walmart's first-party, deterministic shopper data to be activated inside Google's Display & Video 360 (DV360) platform, starting with YouTube. Brands can now run top-of-funnel video ads on YouTube and directly measure how those impressions convert into verified online or in-store purchases at Walmart, closing an attribution loop that's historically been out of reach for omnichannel marketers.
Global Media Realignment Under Seth Dallaire
At Cannes Lions, Walmart announced a restructuring of its global advertising ecosystem. Walmart Connect US, Walmart Connect International, and Sam's Club MAP (officially rebranding to Sam's Club Connect) are being brought into closer alignment under Seth Dallaire, Chief Growth Officer of Walmart Inc. The networks will continue operating separately to serve their distinct markets, but will share tech platforms, modeling methodologies, and measurement tools.
The Strategic Core
- The Walmart Advantage: For most brands, Walmart's e-commerce sales are a fraction of their Amazon volume, typically 10–15%. Amazon is the default search engine for products, and Walmart knows it can't win a pure online traffic war against Amazon Prime on its own site. So its philosophy has shifted: if shoppers won't come to Walmart's digital garden, Walmart will put its data all over the open web to intercept shoppers where they already live, and route that traffic back into its own ecosystem.
- Connecting Digital Media to the Physical Moat: This is where Walmart's real advantage kicks in. Amazon rules the internet, but it can't replicate the more than 10,000 brick-and-mortar stores Walmart operates. With the DV360/YouTube partnership, Walmart is directly wiring the open web into that physical moat, connecting digital awareness campaigns to deterministic, offline store transactions.
- A Full-Funnel Validation: This partnership matters beyond Walmart specifically - it's evidence that retail media is graduating from "bottom-of-funnel search ads" into a genuine full-stack media channel. A brand can now run an awareness video on YouTube and attribute it directly to a sale inside a physical Walmart store or on Walmart.com - a level of closed-loop measurement omnichannel marketers have wanted for years.
- The Walmart Catalog Gap: Sparky's conversational search leans heavily on structured catalog attributes - exact ingredients, materials, dimensions, specific use cases. Right now, too many brands (including large, well-resourced ones) have messy, incomplete backend data on Walmart. In our experience, the bigger the brand, the bigger the catalog mess tends to be. And if a data field is missing, Sparky doesn't flag it or guess - it simply ignores the product.
📌 This is incredibly exciting for the brands we work with. It allows us to finally run cohesive, top-of-funnel brand awareness campaigns with actual, closed-loop attribution. We are actively shifting how we advise our clients to allocate their omnichannel budgets because of open ecosystems like this.
Pros
- The YouTube DV360 partnership provides deterministic, transaction-level offline measurement for digital video campaigns.
- Shared tech stacks and experiential playbooks between Walmart and Sam's Club Connect lower transaction costs and improve ad platform efficiency.
Cons
- The mass-market Walmart shopper and warehouse Sam's Club member are demographically distinct groups with different buying behaviors, meaning a unified, standard ad strategy across both banners is limited in effectiveness.
- The technical capabilities of Walmart's self-serve tools are still catching up to the maturity of Amazon's ecosystem.
💡 Tips
- Clean up your Walmart catalog backend. Populate structured data fields - materials, dimensions, ingredients, and specific use cases - completely. Any blank field is a product Sparky won't surface in conversational search, regardless of how strong the listing is otherwise.
- Test omnichannel video campaigns. Align your media planning with Walmart's open-data strategy. Work with your agency to test budget against Google DV360/YouTube campaigns, and use Walmart's closed-loop attribution to measure true offline sales lift rather than relying on view-through proxies alone.
5. Amazon Tightening Control Over Who Gets To Touch The Customer/Brand Relationship
Two seemingly unrelated policy updates from Amazon reflect a unified operational objective: tightening control over catalog governance and the post-purchase customer relationship.
ASIN Creation Restricts Non-Authorized Resellers
Effective June 1, 2026, Amazon expanded its ASIN creation policy for US Vendors and Sellers. Partners trying to create new listings, variations, or duplicate pages for products enrolled in Amazon Brand Registry must have an official "reseller role" assigned by the brand administrator. Unauthorized attempts will trigger Error Code 5467.
"Contact Customer" Review Option Removed
Amazon has disabled the "Contact Customer" button on the Customer Reviews dashboard. Sellers can no longer proactively initiate contact with customers who leave critical reviews; post-purchase communication is now limited to customer-initiated Buyer Messages.
The Strategic Core
- Enforcing Catalog Hygiene for AI: Resellers typically don't care about content - brands do, and so do the resellers a brand actually authorizes. In the AI commerce era, clean, accurate catalogs are the foundation of discoverability, so Amazon is pushing listing-creation rights toward the parties that have a reason to keep the data right.
- Direct Custody of Customer Support: The "Contact Customer" button never really worked. Customers who want help already reach out on their own, and the ones who aren't happy generally aren't going to be talked back into happiness through a seller-initiated message. Amazon is formalizing what was already true: resolution runs through its own customer service team.
📌 Managing brands with too many resellers is one of the biggest headaches in the ops world — rogue listings, incorrect variations, imagery that's flat-out wrong. Pushing ASIN creation control to brands and their authorized resellers is a welcome change that should mean far fewer listings created the wrong way. The one gap: Amazon isn't addressing the millions of problem listings that already exist, so brands should expect this to require manual cleanup on their end.
Pros
- Brand owners gain a robust mechanism to prevent unauthorized bundles, duplicate listings, and inaccurate catalog changes going forward.
- Catalog consolidation supports cleaner product search indexing and improves the listing experience for buyers.
Cons
- Established brands with large distributor networks will face a high volume of setup requests for Brand Registry reseller roles.
- Sellers lose a proactive tool for resolving customer complaints, even if that tool's real-world impact was already limited.
- The policy only governs new listings - existing rogue ASINs created before June 1 aren't automatically cleaned up.
💡 Tips
- Assign a Dedicated Brand Registry Owner: At larger brands especially, ownership of the reseller relationship is often unclear - it can bounce between sales, legal, and marketing with no single owner. Designate one person to manage Brand Registry permissions and reseller role approvals so requests don't stall in email chains.
- Audit Your Reseller Network Now: If you don't sell through resellers, this change doesn't affect you much. If you do, expect a wave of requests for reseller roles - use this as an opportunity to review who should actually be authorized to list your products, rather than approving requests reflexively.
- Set Expectations for Customer Service: Some product-issue messages may now come directly from buyers instead of being intercepted earlier. That said, expect the bulk of review-related customer contact to still be handled by Amazon's own CS team, so the practical impact on your support volume may end up being minor.
Final Thoughts
June has solidified a fundamental divergence in how the major commerce networks view their roles.
Amazon is doubling down on its position as the ultimate, walled-garden intelligence layer; Walmart, conversely, is demonstrating that its path to scale lies in a highly collaborative, open web.
As the technical barriers to advanced attribution fall and automation takes over the tedious mechanics of ad buying, the ultimate differentiator will no longer be simple data access. It will be your brand's strategic agility, creative execution, and baseline catalog quality.
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