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Welcome to the October edition of the Retail Roundup, your go-to recap of the biggest developments in retail media and marketplace news.
This month, we’re seeing refinement, not reinvention: Amazon is tightening its fulfillment economics, expanding shoppable media surfaces, and advancing AI tools.
This Month’s Highlights:
- FBA Fees 2025: Refinement Year for Sellers
- Twitch Shoppable Ads & Spotify Partnership
- Amazon’s New AI Storefront Builder
- AI Commerce Convergence: ChatGPT Integrations & Amazon’s Response
- Prime Exclusive Deal Fees & Price History Tracking
Let’s dive in.
FBA Fees 2025: Survival of the Fittest
After two years of sweeping structural changes, Amazon’s 2025 FBA fee update represents a period of refinement rather than reinvention.
This year’s announcement, positioned by Amazon as a modest $0.08 per-unit increase on average, conceals significant variation beneath the surface.
The changes are far from uniform as they selectively target product sizes, fulfillment speeds, and storage durations, creating clear winners and losers depending on how well sellers have adapted to Amazon’s evolving regional fulfillment model.
The context for this year’s adjustments goes back to 2022, when Amazon began shifting from a national to a regional fulfillment model. By 2023, that model was fully deployed, and in 2024, Amazon aggressively monetized it with inbound placement fees, new size tiers, low-level inventory fees, and return processing charges. These changes were designed to reward operational efficiency and penalize logistical friction.
Now, in 2025, Amazon is fine-tuning the system, not overhauling it, marking “the icing on the cake” for sellers who have optimized, and “the last drop that spills the glass” for those who haven’t.
Several key takeaways stand out this year:
- Standard-size products priced above $50 are seeing outsized fee increases - as much as $0.51 per unit, far exceeding the “average” increase.
- Sellers who continue to send all inventory to a single fulfillment center will also face higher inbound placement fees, especially for standard-size items over five pounds.
- Programs like Buy with Prime and Multichannel Fulfillment, which were previously incentivized through discounts, are becoming more expensive unless sellers ship multiple units per order.
- Amazon’s pricing structure increasingly favors basket building and operational sophistication.
Overall, the 2025 FBA changes reinforce Amazon’s “perform well and be rewarded” principle.
Sellers with strong operational maturity, optimized fulfillment routing, and healthy logistics data will see little disruption, while those that haven’t evolved face mounting pressure to catch up.
Pros
- Rewards operationally efficient sellers who have adapted to Amazon’s regional fulfillment model.
- Encourages better inventory distribution and smarter shipment routing.
- Creates opportunities for cost savings through optimized splits and well-managed logistics networks.
- Provides greater predictability for mature sellers after several volatile fee cycles.
Cons
- Sellers relying on outdated one-location fulfillment will see steep cost increases.
- High-ticket standard-size products face disproportionately higher per-unit fees.
- “Buy with Prime” and Multichannel Fulfillment programs lose some of their cost advantage.
- Overall complexity continues to rise, demanding more sophisticated operations and data management.
💡 Tips
- Treat each SKU like its own P&L: Calculate unit economics, including inbound, storage, and fulfillment costs to protect margins.
- Revisit fulfillment strategy: Use Amazon’s recommended splits or test regional optimization to reduce inbound placement fees.
- Audit participation in Amazon logistics programs: Reevaluate whether Amazon Global Logistics or Amazon Warehousing and Distribution (AWD) still provides savings under the new structure.
- Plan for volatility: While 2025 may feel like a refinement year, future fee cycles are likely to continue Amazon’s pattern of incremental monetization.
Related Resource: Amazon Hikes US Fees in 2026: What Sellers Need to Know
Media Buying Updates: Twitch Shoppable Ads & Spotify Partnership
TWITCH SHOPPABLE ADS: MERGING LIVESTREAMING AND COMMERCE
Amazon introduced shoppable ads on Twitch, allowing viewers to purchase products directly within live streams. The move revives Amazon’s push into livestream commerce, using Twitch’s massive, engaged audience to succeed where Amazon Live struggled.
By merging entertainment with instant buying options, Amazon aims to replicate the social shopping success seen on platforms like TikTok. Early adoption remains experimental, but it opens a new channel for high-attention, creator-led commerce.
SPOTIFY PARTNERSHIP: EXPANDING AMAZON DSP’S REACH
Amazon Ads confirmed a new partnership with Spotify, enabling audio and video ad buys through the Amazon DSP. This extends Amazon’s programmatic reach beyond its own platforms, joining partnerships with Roku, Netflix, and Disney.
Despite Spotify being a rival to Amazon Music, the move reflects Amazon’s broader goal to make its DSP a full-scale, cross-channel media platform that connects ad exposure to retail behavior.
Related Resource: Making Sense of Amazon DSP's Integrations with Roku, Disney, Netflix, and the Open Internet
Though very different in scope, both updates feed into the same strategic ambition: strengthening Amazon’s DSP as a dominant player in the programmatic media buying landscape.
Pros:
- Expands Amazon DSP’s reach across high-engagement platforms
- Bridges media formats (audio, video, live content) under one buying platform.
- Enables more precise targeting by linking entertainment engagement to retail data.
- Provides new, immersive ad experiences that can drive both awareness and conversion.
Cons:
- Both initiatives are still early-stage, with limited performance benchmarks.
- Internal competition between Amazon Music and Spotify could create pricing or placement conflicts.
💡 Tips:
- Reevaluate your DSP mix: Compare Amazon DSP’s new reach to platforms like DV360 and The Trade Desk.
- Pilot thoughtfully: Start with small Twitch and Spotify test campaigns to gauge engagement and ROI before scaling.
Amazon’s New AI Storefront Builder
A new AI-powered storefront builder has been introduced, designed to speed up the creation and updating of Amazon Storefronts.
The tool allows three starting options:
- Generate a new storefront version based on your current live store
- Build a store from scratch
- Copy a storefront layout from another country market
It works through conversational prompts: describe what you want, and it produces a storefront draft.
Many of the early templates center around seasonal events like Black Friday and Cyber Monday, and it’s expected that templates will continue to shift alongside retail calendars (e.g., Valentine’s Day themes, spring promotions, etc.).
Right now, this tool appears to be an extension of the broader push toward agentic, conversational seller tools that support faster merchandising and assortment deployment.
Pros
- Allows brands without design resources to set up a storefront quickly.
- Good for generating the initial framework or “skeleton” of a page.
- Can help spark inspiration for layout, headlines, or themed campaign messaging.
- Useful for new brands that simply need to get something published vs. nothing live.
Cons
- The current output is still quite basic and lacks the strategic nuance needed for brand-forward storefronts.
- Designs and copy often require significant manual refinement to meet quality and storytelling standards.
- Not yet suited for brands that already have strong creative direction or advanced merchandising needs.
- Doesn’t replace the need for intentional UX structure.
Tips
- Use the tool to draft layout structure, not final visuals.
- Let AI handle first-pass headlines and then rewrite them for tone, positioning, and conversion.
- Consider testing it for seasonal refreshes, where speed matters more than precision.
- For brands with an established storefront strategy: treat this like a starting canvas, not a final product.
- Watch out for new potential developments (e.g., A+ Page Builder, AI tools that replicate your DTC site experience on Amazon, or a possible integration of the search bar with Rufus).
AI Commerce Convergence: ChatGPT Integrations & Amazon’s Response
In the past month, we’ve also seen three related developments that signal a shift in how product discovery may evolve within conversational AI:
- Amazon has received less traffic from ChatGPT over the last 3 months, based on recent SimilarWeb data. This suggests that early “chat → marketplace” referral behavior may not be stabilizing into a durable habit yet.
- OpenAI released the Agentic Commerce Protocol, which allows ChatGPT to not only recommend products but also complete transactions directly inside the chat experience.
- Major commerce platforms moved quickly to adopt the protocol, including Shopify, Etsy, Walmart, and Salesforce, which is now embedding it into its ecommerce and order management systems.
This creates a strategic fork in the market:
- Integrating with ChatGPT: Walmart, Instacart, Shopify, Etsy, Salesforce
- Staying Closed / Internal AI Ecosystem: Amazon (using Rufus + internal retail AI infrastructure)
Platforms opting in are trading some control of merchant-of-record data for broader reach and adoption speed. Amazon, meanwhile, appears highly intentional about protecting transaction data as a core competitive asset and is instead investing in on-platform AI shopping behaviors.
The key nuance? This is not a clear “right vs. wrong” strategy split. Both paths have rational benefits depending on a platform’s business model, margin structure, and view of long-term user behavior.
Pros
- Conversational shopping is better for shoppers who need guidance, not just choices; shining in categories where the buyer is new or uncertain (e.g., baby shoes, hobby gear, specialized sizing, gift discovery).
- Allows the customer journey to occur in one environment: question → product suggestions → purchase — which could remove friction around comparison shopping.
- Gives participating retailers new discovery surfaces outside traditional search and marketplace ads.
- Could expand the role of AI in top-of-funnel product education, which has historically been difficult to influence at scale.
Cons
- Participating platforms are sharing transactional data with an external AI layer, which could erode differentiation and customer understanding long-term.
Recommendation effectiveness is currently mixed:- Some reports show unusually high conversion rates.
- Others show a significant drop-off when shoppers attempt to move from conversation to intent.
- There is a tendency toward hype: new modalities do not automatically replace entrenched behaviors. In a few years, search may still be responsible for 90%+ of ecommerce product discovery.
- The assumption that consumers want to shop entirely through chat may be overstated - convenience only matters if context and clarity are truly better than search.
Tips
- Treat chat-based commerce as a new modality, not a replacement. It will likely coexist alongside search, retail media, and storefront experiences, not overwrite them.
- If experimenting here, start with categories where shoppers require help deciding. Conversational recommendation works best where education is part of the buying journey.
- Make product data structured, specific, and comparison-friendly. AI systems perform best when they can explain why an option is right for the user.
- Avoid making premature strategic bets. The ecosystem is still forming; complete certainty is the biggest red flag in an ever-evolving industry.
Prime Exclusive Deal Fees & Price History Tracking
Prime Exclusive Deals (PEDs) for the holiday period now carry an updated promotional fee structure. Notably, the fee is the same whether a brand participates in the full 12-day event, or only for Black Friday, or only for Cyber Monday. The cost does not scale based on the length of participation.
At the same time, Amazon is testing a visible historical price tracker (currently spotted in the mobile app). This feature shows shoppers the product’s previous pricing trends, helping them determine whether a discount is genuinely meaningful.
Pros:
- Flexible participation: Brands that historically see larger performance spikes during only Cyber Monday (or only Black Friday) can choose shorter participation without sacrificing promotional eligibility.
- Fee efficiency: Because up to 500 products can be grouped under one PED, the per-unit impact of the fee remains low when strategically bundled.
- Improved shopper trust: Displaying historical prices helps justify discounts and reduce skepticism around holiday sale claims.
- Reduced comparison friction: Shoppers no longer need to leave Amazon to check pricing history on third-party tools.
- The new price history feature may expose inflated list price tactics, removing the ability to rely on “fake markdown” anchor pricing.
Cons:
- PEDs still require a minimum 20% price drop to be featured during tentpole events, which may challenge brands with tighter margins, especially after recent fulfillment and operational cost increases.
- Brands that spread out holiday discounting or frequently change list prices may appear inconsistent or manipulative once history is visible.
- If shoppers use price history to wait for better deals, it may compress revenue into narrower sale windows.
💡 Tips:
- If your brand historically experiences peak lift only on Cyber Monday, consider avoiding the full 12-day discount window to preserve margins. The promotional fee will be the same either way.
- Bundle strategically: group multiple SKUs under a single PED to spread the fee across more unit volume.
- Review list price strategy now; assume price transparency becomes the default.
- Plan messaging and promotional timing more intentionally; pricing tactics that rely on “inflated before / discounted now” will be less effective.
- Track how this affects algorithmic deal ranking. Amazon may begin rewarding stable, credible pricing behavior.
The Bottom Line
Refinement is the theme. Costs are tightening. Media is expanding. AI is accelerating.
The brands that will win next are the ones that treat Amazon like a performance engine: tuned, tested, and always evolving.
The playbook is out. Now it’s about execution.
Give It a Listen
You can tune in for the full interview with Armin Alispahic and Pat Petriello on the Ecommerce Braintrust hosted by Julie Spear and Jordan Ripley.
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