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Amazon Issues Reports

Latest outage, problems and issue reports in social media:

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  Sushil Joharapurkar 🏹 🚜 (@sushiljain269) reported 5 minutes ago

  @AmazonHelp Well, we have played this game before. Please understand that you need to have someone technical to resolve the issue. As I stated, this is the 3rd time I have faced similar issues within a year. If you are really not ready to be ethical and empathetic, you should shut business.

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  Deity Demeter - Findom 🏛️🏺🌾 (@itsdeitydemeter) reported 8 minutes ago

  just spent $378 on Amazon for my move lol your problem now

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  Omid Malekan (@malekanoms) reported 8 minutes ago

  I hate to burst everyone's bubble, but this explainer of how credit cards work by Rain is inaccurate, almost misleading. For the record, I like that team and think stablecoin-backed cards are a great product, but if we are going to be disruptive as an industry we need to get key facts right. So let's get to it: First, the claim that without interchange "no business would take on the risk and costs associated with issuing your card" is absurd. Interchange is capped in many places to a fraction of the US (most notable the EU) and cards there work just fine. Nobody has exited the market. The credit/debit blend might be different, and there are less rewards, but cards persist. Similar story in the US with debit cards where the fee is capped by the Durbin amendment. If you don't believe me, as your favorite LLM how much profit the largest issuers take home from interchange. It's definitely not "recouping operating costs." Second, the claim that delays in settlement lead to a very high cost of capital ("idle capital") for issuers is mostly wrong. The largest issuers all have access to real-time payment systems like same-day ACH, RTP, and FedNow (hell they own the private-sector solutions like TCH that offer some of these). If they don't settle cards in real-time, it's because they choose to, not because they can't. First, delayed settlement = netting = lower cost of capital. The longer the delay, the more capital efficient the netting. Also, in the weekend example, there is almost no money actually sitting idle earning nothing waiting for Monday settlement. The largest issuers settle out of their Fed reserve balances which earn IORB (currently 3.6%). And the funds ******* in credit card settlement are relatively tiny compared to their massive balance sheets, which suffer from excess reserves. There probably is no other place they'd want to park this money anyway. Even if non-weekend settlement did impose some cost, it is small compared to what is recouped via interchange (for credit and Durbin-exempt debit) or the insane interest rate charged on revolving balances (on credit). Lastly, stablecoin-backed cards also have an idle balance problem. It's just transferred from an issuer (like JPM) to the user (like you). If you don't believe me, ask your favorite LLM to cross-reference the largest card issuers with a list of the banks most aggressively trying to kill stablecoins in DC. Why would the likes of JPM and BoA be so opposed to something that supposedly reduces their costs? Third, the cross-border example is both oversimplified and convoluted. As a general rule of thumb, cross-border card swipes are more profitable than domestic ones for issuers. They are exempt from domestic caps and also earn the F/X conversion fee (at least 1%, if not higher). This is one reason why so many American credit cards give such great travel perks. They want you to go to Europe and use your card there - they'll make more oney. Now, this doesn't apply in the example given (a Colombia-issued card being used for a Claud subscription) but I am confident LatAm card issuers make money off the F/X leg - it's not a burden. As a general rule of thumb, any argument or explainer that acts like credit card issuers or networks are doing us some kind of favor by existing should not be taken seriously. Issuing a card and running a card network are among the most profitable businesses out there. The gross-margins are fat, the sector is growing, and the network effects are strong. So why do I care enough to issue this correction? The fact that Rain—an otherwise succesful and even admirable company—would issue this tortured account of how cards work is a great teaching moment as to why cards and their related fees persist, despite being a regressive tax on small business. Rain's business model is primarily interchange. They can't exactly come out and say "stablecoins on public blockchains will kill swipe fees" because then they'd have to go find a new business model. Something similar has happened to every pre-crypto attempt to disrupt cards. Those in the position to change it all got coopted to benefit from it. My favorite example are the largest merchants (like Amazon) who used to be the largest victims of swipe fees, until they realized they can negotiate much lower fees for them, then issue a branded card that sticks it to smaller competitors. My own view is that stablecoins will ultimately disrupt this model and collapse swipe fees. First, because the card industry's margins (including Rain's) are their opportunity. Second, because unlike the credit card networks, public blockchains are censorship-resistant. They allow far more competition, particularly from startups. The process will take decades to play out, but ironically stablecoin-backed cards like the ones issued by Rain will help us get there. To break down network effects, you need to target one side of the market first. Get millions of people comfortable with paying with stablecoins (by way of a card), then go to the merchants and convince them to accept stables directly. I'm sure a savvy startup like Rain will be able to evolve. The big banks who are the biggest issuers will struggle.

• 
  Alpha Oracle (@therogueoracle) reported 9 minutes ago

  @SayNoToTrading @RentYourStocks Amazon grocery prices have gone down, I think it’s cheaper than Costco now for many things, and it’s delivered to your house

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  R Radhakrishnan✒️📖 (@RRadhak68429866) reported 10 minutes ago

  @AmazonHelp This does not really help. It takes me back to the same old customer service and different people come and say the same stuff on a loop. Today I was was cut off while explaining my issue. #amazon

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  Singh Anuraj (@SINGH_ANURAJ) reported 19 minutes ago

  @amazonIN 5/6 Every time I contact Amazon, I get a new timeline — first wait until 14 Aug, then another 48 hours. The issue is extremely simple: both packages were taken by the delivery agent, the replacement was marked delivered, and my refund is still pending.

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  Surendra Koutarapu (@SurKopu) reported 21 minutes ago

  Your local coffee shop can now watch its staff the way Amazon watches warehouse workers. Nothing new was installed. Just AI pointed at the cameras already there. Regular CCTV, suddenly a live scoreboard. Cups made per barista. Who's fast, who's lagging. How long each customer has waited. Movement, patterns, all streaming to a dashboard in real time. The camera used to just record. Now it judges. And the honest truth is that both things are true at once. For the owner, it's a gift. A single tiny shop can now run the operations analytics that used to need a corporate budget and an IT team. The little guy gets big-chain superpowers. For the barista, it's a shift where a machine grades every pour, logs every slow minute, and never blinks. Here's the pattern under it, and it's bigger than coffee. Every wave of cheap AI hands power to the small player and hands surveillance to everyone at the same time. The exact same tool does both. You don't get one without the other. In a country like India, full of small shops and service jobs, this spreads quietly and fast. The camera can finally understand what it's looking at. The real question now is what we agree it's allowed to do with that.

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  Scott Oliver (@SAOliver_Atty) reported 25 minutes ago

  @SMB_Attorney Smart alarms have always given us problems too. Nothing like a 3am false alarm to make you smash that Amazon buy button for a new one.

• 
  Max | Google Ads (@lifemaximised) reported 26 minutes ago

  You could run 80% of your Google Ads operation inside Claude Opus 5… So here’s our 10-stage prompting workflow to do so: (Save this) Stage 0: Build the project brain Before asking for anything, create a Claude Project and feed it everything. > Product pages > Best sellers > Customer reviews > Objection docs > Competitor URLs > Meta ads > Google Ads Transparency Center links > Search terms reports > Winning ad copy > Offer details > Brand guidelines > Past landing pages > Performance exports Then run this prompt “Act as the Google Ads strategy brain for this brand. Read all uploaded context and create a working brand profile covering: ICP, core pain points, buying triggers, objections, emotional language customers use, top products, strongest offers, competitor positioning, current funnel gaps, and Google Ads opportunities. Do not make recommendations yet. First summarise the context and ask me what is missing.” The quality of the outputs you’ll get from this AI workflow will directly correlate with the quality of the context you give it here. And also the quality of the Claude model you use, since newer models have more context tokens and better reasoning skills. Stage 1: Customer language mining “Search Reddit, YouTube comments, Amazon reviews, TikTok comments, and niche forums for people discussing problems related to [PRODUCT CATEGORY]. Extract the exact words they use when describing the problem, what they have tried, why those solutions failed, what outcome they want, and what would make them buy. Format this as: Quote / Pain Point / Desired Outcome / Funnel Stage / Possible Ad Angle.” This gives you the language that keyword tools would never show you. If someone writes: “I’m tired of wasting money on supplements that do nothing.” That can be a winning ad angle right there. Stage 2: Competitor angle map “Research these competitors: [COMPETITOR 1], [COMPETITOR 2], [COMPETITOR 3]. Use Google Ads Transparency Center, Meta Ad Library, their landing pages, product pages, offers, guarantees, reviews, and email capture flows. Build a table showing: offer, main promise, ad hooks, landing page angle, proof used, objections handled, pricing position, and what they are NOT saying.” Then run: “Based on this competitor research, identify the 5 most validated market angles and the 5 biggest white-space angles we can own. For each angle, explain which funnel stage it belongs to and what campaign type should test it first.” If 3 competitors are all running the same hook, that angle is validated. You don’t even need to be original. Just add your unique spin to what’s already working. Stage 3: Keyword research “Using the customer language, competitor research, product pages, and search intent data, build a full Google Ads keyword universe for [BRAND]. Split it into: branded, competitor, high-intent product, problem-aware, solution-aware, comparison, ingredient/material, use-case, gift/occasion, and negative keywords. For each keyword, include funnel stage, intent level, match type, campaign/ad group recommendation, and landing page angle.” Then run: “Now prioritise this keyword research report into a 30-day launch plan. Separate must-launch keywords from phase 2 tests. Flag any keywords that are high volume but low commercial intent.” This stops the campaign from becoming a messy keyword dump. Stage 4: Campaign architecture “Turn the finalized keyword research report into a complete Google Ads account structure. Include campaign names, ad group names, keyword match types, bidding strategy, starting budget split, exclusions, negative keyword rules, and when each campaign should launch. Use this structure: branded search, branded shopping, non-branded shopping, non-branded search, competitor search, PMax remarketing with brand exclusions, display remarketing, Demand Gen, and TOF search tests.” Then add: “Explain why each campaign exists, what signal it is meant to produce, and what metric decides whether it scales, holds, or gets cut.” Every campaign needs to play a role in your ecosystem. If it doesn’t, you should just stop running it. Stage 5: RSA copy production “Write responsive search ad copy for [PRODUCT] targeting [KEYWORD]. Funnel stage: [BOF/MOF/TOF]. Use the customer language and competitor gap analysis above. Give me 15 headlines under 30 characters and 4 descriptions under 90 characters. Include: benefit-led headlines, problem-led headlines, proof-led headlines, offer-led headlines, and urgency-led headlines. Make sure headline 1 matches the search intent.” Then run: “Create 3 ad variations for this keyword: one direct-response version, one proof-heavy version, and one problem-agitation version. Explain which audience each variation is for.” BOF copy should sound like the product is the obvious answer. MOF copy should make the benefit feel believable. TOF copy should make the problem impossible to ignore. Stage 6: Merchant Center feed optimization “Rewrite this product title for Google Shopping using the structure: Brand + Product Type + Core Keyword + Key Feature + Use Case/Benefit. Stay under 150 characters. Give me 10 variations ranked by likely search intent.” Then: “Write a Merchant Center description for [PRODUCT]. Use up to 5,000 characters. Include all relevant buyer keywords naturally, cover features, benefits, use cases, materials/ingredients, sizing/specs, objections, and reasons to choose this product. Do not include irrelevant keywords or products we do not sell.” Then: “Audit this product feed for missed Google Shopping opportunities. Check title, description, product type, Google product category, images, variants, pricing, promotions, shipping, reviews, and attributes. Tell me exactly what to change.” Stage 7: Landing page angles “Build a landing page brief for [PRODUCT] targeting people searching [KEYWORD]. Awareness stage: [PROBLEM-AWARE/SOLUTION-AWARE/PRODUCT-AWARE]. Structure it as: hero headline, subheadline, proof bar, problem section using customer language, mechanism section, product section, comparison section, reviews, objection handling, FAQ, CTA. Make sure the first screen matches the search query.” Then run: “Create 5 landing page angle variations for this product based on different search intents. For each one, give me the hero, core promise, proof required, objections to handle, and CTA.” Send the best one into Claude Code. Now you have an intent-specific page created instead of 1 generic PDP trying to convert everyone. Stage 8: Creative production Connect Higgsfield MCP inside Claude. Then run: “Create a 9-shot YouTube ad concept for [PRODUCT] based on this angle: [ANGLE]. Style can be claymation / UGC / cinematic product demo. For each shot, include scene description, voiceover, on-screen text. Use GPT Images 2.0 for the statics.” Then: “Create 5 new creative concepts from the strongest customer pain points in the research. Each concept should include hook, visual metaphor, script, image prompts, animation prompts, and CTA.” If you wanna run video ads, animate your statics with Seedance 2.5 Use Opus to write the scripts. Shouldn’t cost more than $3 per ad. Stage 9: Daily campaign audit Connect Google Ads MCP (or just export report CSV) Then run: “Pull the last 7 days of Google Ads performance and compare it to the previous 7 days. For each campaign show spend, revenue, ROAS, conversions, CPA, CPC, CTR, impression share, search lost IS rank, search lost IS budget, and top search terms. Flag: ROAS down 20%+, CPA up 20%+, budget-limited winners, rank-limited campaigns, branded leakage in non-branded campaigns, wasted spend queries, and products spending with no conversions.” Next up: “Turn this audit into an action list. For each action, include the campaign, issue, evidence, recommended change, risk level, and expected impact.” Stage 10: Weekly scaling plan “Compare performance across 7, 14, and 30-day windows. Identify campaigns, products, keywords, ads, and landing pages with consistent green signals. Recommend which budgets to increase by 15-20%, which to hold, which to decrease, and which tests to launch next. Do not recommend scaling anything unless the signal is consistent across multiple windows.” Then: “Create next week’s testing roadmap. Include 3 keyword tests, 3 creative tests, 2 landing page tests, 2 feed tests, and 1 campaign structure test. Rank them by expected impact and implementation difficulty.” And this is how you get your full ecosystem set up: > Research feeds keywords > Keywords feed campaigns > Campaign data feeds landing pages > Landing pages feed creative > Creative feeds new angles > Audits feed the next week of tests If you want me to build this full AI Google Ads production system for your brand btw, DM me “OPUS” and I’ll show you what it’d look like

• 
  Nate Ginsburg (@NateGinsburg) reported 27 minutes ago

  Took an Amazon PPC account from 50% ACOS to 22% in 3 weeks. It was a housewares brand, totally disorganized. We started by cutting massive ad spend waste: negating, pausing, shifting budgets to profitable areas. Then, we doubled down on winners. More spend on existing strong areas, and expanding winners into new placements/match types in isolated groups. It's all about layered strategy and consistent weekly optimization. Don't just set it and forget it.

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  Harish Sharma (@hrshshrm854) reported 32 minutes ago

  Honestly the worst customer experiences I’ve had. social media support is completely useless, full of people who seem incapable of resolving even a simple issue. I regret buying this product from Flipkart. Next time, I’ll make sure to buy from Amazon.@Flipkart @flipkartsupport

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  Amber Puga (@amber_puga) reported 32 minutes ago

  @AmazonHelp I wanted to buy a Peloton bike and have it delivered to my address & have the bike out together by specialist. The problem you lot are saying you can deliver to my apartment where you delivered to my place as late as this past Friday. Don't you want a $1,400 sale???

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  Gabe (@GanjoKazooie) reported 34 minutes ago

  @Hyperkin Will the Amazon preorders yet to ship out come with the adapter for the M64 connection issue, or will they come fixed already?

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  Polsia (@polsia) reported 35 minutes ago

  SMB webshops run Bol, Amazon and Shopify across five dashboards and a spreadsheet full of broken formulas. Built Vendoorn to fold all of it into one 24/7 AI agent — margin, stock, returns and reviews, handled. Live soon.

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  Joby R J Wheatley (@jobygunner1987) reported 36 minutes ago

  Amazon Prime delivery is getting Slack nowadays @AmazonUK fix up