STUMP BEZOS
Shopify’s revenue for fees and services will hit almost $20 billion this year, up 32%. How much does that equate to in Gross Merchandise Volume on the platform?
[ Answer at bottom of email ]
💰 SELLER CENTRAL JUST HIRED YOU AN INTERN
Amazon just put a full-time intern inside your Seller Central account.
It doesn't take lunch. It doesn't forget. And it won't touch anything important without asking you first.
At Accelerate in Seattle last month, Amazon rolled out Seller Assistant Workflows. It's now landing in US accounts. Most sellers haven't clicked it yet. Here's what it does and how to put it to work this week.
Where to find it
Click Seller Assistant at the top right of Seller Central. A chat panel opens on the left. Type in the box at the bottom.
That's it. No setup wizard. No onboarding call.
How it works
You describe a task in plain words. The assistant turns it into a workflow, lays out every step, and shows you the plan.
Nothing runs until you approve it.
Once it's live, a workflow can run on a schedule or on demand. It keeps watching even when you're logged out. Every action goes into a history you can review. You can list your workflows, check past runs, kick one off manually, or archive it, all from the chat.
The intern never goes rogue.
The five templates live today
Each one replaces a task that usually lives in someone's head or a forgotten browser tab.
1. Orders & Returns Digest. One snapshot of recent orders and returns. It flags seller-fulfilled orders getting close to the ship-by deadline. It spots any product with 3+ returns in 30 days. That's your early warning on a quality or listing problem.
2. Pricing Analyzer. Shows where you're losing the Featured Offer, how big the price gap is, and what your fees look like at each price point. It will not tell you what to charge. That call is still yours.
3. Product Expansion Finder. Starts from your existing catalog and surfaces related products. For each one you get your approval status plus the competition and fee picture. Good for planning your next launch.
4. Account Health Monitor. Ranks your defects by severity and marks which ones have an appeal path. It won't write the appeal. But it tells you where to look first, which is half the battle.
5. Review & Feedback Requestor. Automatically requests reviews and seller feedback on eligible orders. Your social proof stops depending on somebody remembering to do it.
Build your own
The templates are just the starting point.
One seller asked it to build a buyer message responder. It mapped every step. It flagged A-to-Z claims and safety issues for the seller to handle personally. It read past replies so the drafts sounded like him. Then it asked one question: drafts only, or send each one after I approve?
That's the right instinct. Start in drafts-only mode. Graduate to send-after-approval once you trust it.
The part that changes everything: the Knowledge Base
You can upload up to 100 documents about how you run your business. Return policy. Shipping preferences. Reply rules. Product FAQs. SKU guidelines. SOPs.
Then attach them to any workflow.
Workflows search those docs at run time and act on your rules instead of generic Amazon answers. That's the difference between an assistant that sounds smart and one that actually knows your business.
On top of that, Seller Assistant now keeps a persistent memory of your pricing patterns, inventory cycles, and growth goals. The more you use it, the more personal it gets.
Three things to try in the chat today
You don't need a workflow to get value. The assistant is useful on demand.
Check a listing for compliance risk. One brand ran its electrician tool bag listing through and got flags on gift phrases and repeated keywords, on a listing they had already reviewed.
Paste this:
Check ASIN [your ASIN] for potential wording issues in its visible listing and any backend fields you can access. Show the exact wording, explain the concern, and cite the relevant Amazon policy. Tell me which fields you could not inspect.
Treat these as flags to review, not confirmed violations. Ask for the policy before you change anything.
Mine your category's reviews. Ask for the top positive and negative review themes in your category. You may need to supply a browse node (Amazon's category ID) if your permissions don't allow a direct catalog search. Watch the scope. Browse nodes can be broad. That same tool bag search pulled in grilling products.
Go head to head with competitors. Once the category tells you where to look, narrow it down:
Compare [our ASIN] with [competitor ASINs] on the review themes relevant to [your product]. Separate product strengths, recurring complaints, and opportunities. Show supporting evidence and note any missing data.
Keep pushing until the answers are specific enough to act on. Are your dimensions clear? Do your images show what fits inside? Do you explain care and cleaning?
Meet Amazon Quick: the intern's back office
Seller Assistant runs your Amazon account. Amazon Quick runs everything around it.
Quick is Amazon's AI companion for the work that happens outside Seller Central. Planning. Analysis. Content. Staying organized across the whole business.
What it does
Turns a question into finished work: reports, spreadsheets, decks, a reorder plan, a business review you can hand to your team.
Runs deep research across your own files and the web.
Connects to your email, calendar, and files, plus apps like Slack, HubSpot, Salesforce, Shopify, Notion, Box, and Zoom.
Builds simple custom apps for your team with no code, and has a desktop app that works with files on your computer.
With the Selling Partner AI plugin (beta), it pulls in your Amazon listings, performance, and analytics. Your selling data lands in your research and reports without exporting a single CSV.
How it's different from Seller Assistant
Seller Assistant lives inside Seller Central and acts on your account: orders, pricing, account health, reviews.
Quick lives outside it and works across the whole business: your inbox, your suppliers, your team docs, your other tools.
The memory Seller Assistant builds about your business follows you into Quick, so you don't start from zero.
Think of it this way. Seller Assistant is the intern on the warehouse floor. Quick is the one in the office writing the reports and answering the supplier emails.
Prompts to try
"Every Monday, check my competitors' pricing and flag where I should adjust."
"Tell me which products will stock out before the holidays and when I should reorder."
"Turn last month's sales into a one-page business review for my team."
"Organize my inbox, show me what needs a reply today, and draft responses to my suppliers."
The deal
Every primary account holder can claim 12 months of Quick Plus free (normally $20 per user per month) for themselves and two users they delegate. Deadline is December 31, 2026. Sign up through Quick and you also get a $1,000 credit toward Meta ads.
Got questions? The Quick team is answering live in Seller Forums on Tuesday, October 20, from 8am to 5pm PT.
🛠️ BDSN SOFTWARE TOOL of the DAY 🛠️
The Guy Who Helped Build Amazon's Ad Engine Wants Sellers to Test His New Optimization Tool (Free)
Most Amazon PPC tools are built by people who've only ever seen the ad platform from the outside.
This one's different.
Q52 Ads was founded by a former Amazon Ads product leader who spent 9+ years inside Amazon building the Sponsored Ads products themselves, including the recommendation systems and Sponsored Products at launch in the US and Canada. He knows how the machine works because he helped build the machine.
Now he's left to build his own startup: an Amazon Ads optimization engine designed as one intelligent command center for your advertising. A few things make it stand out from the usual PPC dashboard clones:
🎯 Goal-driven from the start. You set your advertising goals up front, and every strategy, campaign, and recommendation is built around hitting them.
✅ Approval-based automation. This isn't a black box that hijacks your bids overnight. Q52 proposes the moves, for example "raise bids ~15% on these 12 exact-match keywords converting at 4.6x ROAS but losing impression share" and you decide how much oversight you want. Approve each action, pre-approve a plan, or let it run.
🧠 The "why," not just the "what." Most reports tell you your ACoS moved. Q52 tells you why it moved and what to do next, then turns your ad performance into product-level insight.
🧪 Systematic experimentation. Structured, always-on testing of strategies and settings, so you stop guessing which bid change actually moved the needle.
Here's the opportunity 👇
He's looking for just 3-5 sellers actively advertising on Amazon to be early testing partners. In exchange for honest product feedback, you get:
Free access to the full Q52 Ads optimization platform
Direct access to the founder with hands-on support from someone with 9+ years of product experience inside Amazon Ads (when's the last time your PPC tool gave you that?)
If you're spending real money on Amazon Ads and want an ex-Amazon Ads insider personally looking at your account while you test his tool for free, this is about as good as early-access deals get.
👉 Grab one of the spots at q52ads.com. Scroll down and join the waitlist
🚀 META MUSE is a NEW SHOPPING CHANNEL
Hat tip to Scot Wingo and the team at Retailgentic. They’ve done the best hands-on research yet on how Muse actually chooses products. What follows is a quick, actionable breakdown of their findings.
What Is Muse?
Muse is Meta’s personal AI agent, launched September 8. Think of it as an assistant that lives inside the Facebook/Instagram/WhatsApp universe and can actually do things for you, including shop.
That last part is the big deal. Muse doesn’t just recommend products. It can find them, compare them, and check out on the shopper’s behalf.
And it knows a LOT about its users. Email, calendar, past chats, upcoming trips, preferences. When someone asks Muse for “a dress for my sister’s wedding,” Muse already knows the date, the location, and that she hates polyester.
Your product listing usually knows none of that context. That gap is where sellers win or lose.
What’s Happening Under the Hood
Retailgentic got Muse to reveal its internal “shopping skill” file. Here’s what matters:
Muse leans toward low prices, then filters by what the shopper asked for (size, color, features, location).
It pulls products from three places:
The Meta.ai product catalog (the big one)
Shopify’s catalog via UCP (Universal Commerce Protocol)
A web crawler to fill gaps
Facebook Marketplace shows up for used, local, and collectible items. Not relevant for most brands.
The key finding: when a product showed up in Meta.ai’s top three results, Muse showed it 89% of the time. And 73% of prompts returned at least one identical listing on both.
Translation: Meta.ai is the front door to Muse.
The 5 Moves to Optimize for Muse
1. Get Into the Meta.ai Catalog
This is the single highest-leverage move. Meta has taken product feeds through Meta Commerce Manager for years. That feed flows straight into Meta.ai, and from there into Muse.
Not on Shopify? Make sure your catalog is live and clean in Commerce Manager.
On Shopify? You’re largely covered through the Shopify/Meta deal, but verify.
Bonus: make sure your site is crawlable so the backup crawler can find you too.
2. Enrich Your Product Data
Basic attributes (size, color, material) are table stakes. Muse needs to match your product to a shopper’s real-life situation. Feed it:
Who it’s for and the main use case
The occasion it’s perfect for
Why people love it (pull from your best reviews)
Answers to common FAQs
Your side of negative reviews (new formula, sizing notes, usage tips)
Sensory details like scent, texture, fit
The more context in your listing, the better Muse can connect it to a shopper’s context.
3. Monitor Through Meta.ai
Muse is hard to test repeatedly because it remembers everything about you. No clean-slate mode.
The workaround: since Muse mostly pulls from Meta.ai, test there. Check:
Do your products show up for product, feature, and category prompts?
Is the price, image, and variant info correct?
Does the link land on the right page?
Save your Muse testing for spot checks.
4. Make Sure Muse Can Check Out
Discovery means nothing if the agent can’t complete the sale.
Shopify sellers: Muse checks out via UCP. Confirm Shop Pay and Link are working.
Everyone else: Muse uses your guest checkout with Link. Periodically have Muse run through your checkout and look for anything that blocks it (forced account creation, popups, captchas).
5. Look Into UCP
Muse already speaks UCP, mainly for Shopify stores right now. Retailgentic expects it to open up more broadly, possibly through a Muse connector program. Bonus: UCP also works with Google Gemini, so one integration covers two AI shopping channels.
This one is a forward bet, not a must-do today.
Quick Action Checklist
Confirm your catalog is live in Meta Commerce Manager
Add use cases, occasions, and FAQs to your product data
Run test prompts in Meta.ai for your top SKUs
Test your guest checkout with Muse
Put UCP on your roadmap
The Bottom Line
AI agents are becoming the new shelf. Muse is Meta’s version, and it’s built on top of a catalog you can already feed today. The sellers who give these agents the richest context will get recommended. Everyone else gets skipped.
Survive Peak Season. Get the shirt to prove it.
Q4 is when overselling, split stock and manual order processing hurt most. Linnworks runs Amazon, TikTok Shop and Shopify from one system, so more volume doesn’t mean more hiring.
The average seller runs 15 disconnected tools. Linnworks sits between where you sell and how you fulfill, and makes them behave like one system.
Book and attend a demo and pick a tote, shirt or hat on us. For US and UK sellers doing 300+ orders a month across two or more channels.
Get your demo (and merch) here
📺 YOU GOTTA SEE THIS
Most brands completely fail on TikTok Shop because they treat it like an Amazon PPC campaign. They throw money at ads, send out a few samples, and give up when it doesn't immediately work.
But the top 1% of sellers, the ones driving 60% of all TikTok Shop revenue are using a completely different playbook.
In this episode of the Marketing Misfits podcast, Norm Farrar and Kevin King talk with Sohun Sanka, an e-commerce growth expert and the founder of Clankers. Sohun breaks down the exact strategies top brands use to find, recruit, and coach high-performing TikTok affiliates.
He also reveals how to use AI tools like Claude to automate the grueling process of creator prospecting, track competitors' content, and run hyper-personalized affiliate marketing campaigns.
If you are a brand owner wondering why your TikTok Shop isn't scaling, or you're a creator trying to figure out how the top 1% make millions in commissions, this episode is a masterclass in social commerce strategy.
🌎 INTERESTING STATS
🔥 MORE HOT PICKS 🔥
🥃 PARTING SHOT
“It’s fine to celebrate success but it is more important to heed the lessons of failure.”
✌🏼 Here’s to your success …
The answer to today’s STUMP BEZOS is
Shopify’s GMV will be about $645 billion in 2026.
