Amazon started rolling out its Delivery Date + 7 (DD+7) reserve policy across U.S. accounts this month. If you sell in Europe, this already hit in September 2025. Either way, it changes how fast you get paid, and not in your favor.

How it works: Amazon now holds your funds for 7 days after the customer receives their order before those funds become eligible for disbursement. Factor in Amazon's payout cycle and bank clearing times, and you're looking at 10–12 days from delivery to cash in hand. Under the old system, payouts were tied to a more predictable two-week cycle based on shipment, not delivery.

Why it matters: Seven extra days of float might not sound like much, but across thousands of orders it stacks up fast. For high-volume sellers, that's tens or even hundreds of thousands of dollars sitting in Amazon's pocket at any given time. If you run lean, and most of us do, that gap can mean delayed restocks, paused ad spend, or missed payroll.

The hidden danger: Cash crunches from DD+7 can trigger a nasty domino effect. Late shipments, canceled orders, and refund spikes all ding your account health metrics. Amazon's automated systems don't care why your metrics slipped. They just flag you. Worst case, you end up in a Section 3 review and lose account access entirely.

What to do now:

Run a cash flow analysis layering in the 7-day delay against your current payout schedule. Build a 10–14 day cash buffer if you don't already have one. Negotiate extended payment terms with suppliers.

Consider Amazon Lending or short-term working capital (but avoid high-interest debt as a permanent fix). Use automation tools that track delivery confirmations so you can forecast disbursement dates. Monitor your Account Health Dashboard weekly includingLate Shipment Rate, Order Defect Rate, and Cancellation Rate are the metrics to watch.

What NOT to do: Don't switch bank accounts, manually withdraw funds, or manipulate order processes to try to speed things up. Amazon's systems will flag it. Don't open a second seller account to work around the delays (instant suspension risk). And don't slash ad spend overnight, you'll tank your rankings and spend weeks rebuilding momentum.

Bottom line: DD+7 isn't optional and exemptions are basically nonexistent. The sellers who come out fine will be the ones who adjusted their cash flow model before the squeeze hit, not after.

Read the complete details in this Riverbend blog post here.

Want to reverse-engineer a high-converting landing page from a brand doing $300M/year? Here's how to do it in about four minutes using Claude AI.

Step 1: Find a winning page. Go to Facebook Ad Library, search for a top brand in your niche, and click through one of their ads to land on their sales page.

Step 2: Prompt Claude. Paste this into Claude (using the Opus model): "I want to create a Shopify landing page modeled after [their URL]. Use the exact layout, sections, offer structure, but swap in my product branding and content from [your Shopify product page URL]. Create a single self-contained HTML file with vanilla CSS and JavaScript."

Step 3: Prep Shopify while Claude works. Go to your Shopify admin, click Themes, then Edit Theme. Hit the dropdown at the top, go to Pages, and click Create Template.

Name it whatever you want. Hide the default page content, then click Add Section and search for "Custom Liquid." Save it. Then go to Online Store > Pages, create a new page, and assign your new template. Save that too. The page will be blank for now.

Step 4: Paste and publish. Once Claude finishes generating the code, copy it all, paste it into the Custom Liquid section in your theme editor, and hit Save. Refresh your page. Change the layout to full width if it looks tight. Done.

You just cloned a multimillion-dollar brand's landing page structure with your own branding, no developer needed, no third-party page builder fees.

The key is using Facebook Ad Library to find pages that are already proven to convert, then letting AI handle the heavy lifting of recreating the layout.

Amazon just added "Saved Opportunities" to Product Opportunity Explorer. You can now save niches and ASINs with one click, track them over time, and access them across global marketplaces. Everything lives in a new "Your Saved & Recent Views" tab inside Seller Central. Will Haire posted about this on Linkedin.

Why this matters: Product Opportunity Explorer is becoming a legit research workspace, not just a one-off lookup tool. You're getting first-party Amazon demand data with persistence, something that used to require Helium 10, Data Dive, or Jungle Scout to approximate.

What to do now: Start saving niches for any SKUs or product extensions you're evaluating. Build a running shortlist inside the tool so your team can revisit opportunities as demand shifts instead of restarting research from scratch every time.

The bigger signal: Amazon keeps pulling product discovery and demand validation inside its own ecosystem. They want these decisions happening in Seller Central, not third-party tools. Worth paying attention to where this trend goes.

New research out of Shanghai University (December 2025) confirms what smart sellers already suspected: telling customers your product was "designed by AI" tanks purchase intent by up to 29%.

Across nine experiments on physical products (perfumes, snacks, accessories), the pattern held. When products carried an "AI-designed" label versus "human-designed," shoppers showed up to 28.8% lower purchase intentions. They also perceived 75% less human involvement in the process, which made them feel disconnected from the product.

But here's where it gets interesting.

When the product was described as a human-AI collaboration (something like "our designer used AI to brainstorm color combinations"), purchase intent actually rose 3.5% above human-only designs. And it beat AI-only labels by nearly 13%.

Why do people react this way?

It comes down to identity. We buy from people and brands we feel aligned with. A dog lover buys the grooming tool because they assume the person who designed it probably loves dogs too. When AI is the sole designer, that connection disappears. There's nobody on the other end to relate to.

But when a human is in the loop, even partially, that sense of alignment comes back. People can still picture a real person behind the product.

One more twist worth knowing: this effect reverses for rentals. People were actually 14% more willing to rent AI-designed products (like camping gear) than human-designed ones. When you're renting, you care about utility, not identity. The designer's story matters less.

What this means for your brand:

If you're using AI to develop products (and you probably should be), don't lead with it. Frame AI as a tool your team uses, not as the creator. "Our designer Alex used AI to develop this feature" works. "AI-created delight" does not.

The AI did the work. Let the human take the credit.

✌🏼 See you again Thursday …

The answer to today’s STUMP BEZOS is
Walmart generated $6.4 billion in ad revenue in 2025.