eBay status: access issues and outage reports

Problems in the last 24 hours

The graph below depicts the number of eBay reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.

Most Reported Problems

The following are the most recent problems reported by eBay users through our website.

• Website Down (61%)
• Sign in (23%)
• Errors (16%)

Live Outage Map

The most recent eBay outage reports came from the following cities:

City	Problem Type	Report Time
Baltimore	Errors	6 hours ago
Sunnyvale	Errors	6 hours ago
Gateshead	Website Down	6 hours ago
Schleswig	Sign in	8 hours ago
Manchester	Website Down	9 hours ago
Birmingham	Errors	14 hours ago

Full Outage Map

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

eBay Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Sam Parr (@thesamparr) reported 3 minutes ago

  Former CEO of PayPal + Inuit Bill Harris on Moneywise today. He broke down his portfolio and expenses (and what it was like working w/ Elon + thiel. - Net worth: ~$100m. Divorce cut it roughly in half - ~$50m in operating companies he's starting, ~$25m diversified securities, ~$25m bonds. No PE/hedge/alts - "absurd fees" - PayPal/eBay exit: personally "more than 20 million, less than 50" - Personal Capital: sold to Empower for $825m with $23b AUM; his take was north of $100m post-tax - New venture: ~$10m of his own money in - Total annual burn: ~$70-80k all in, property tax included ("well less than a hundred thousand bucks") - No mortgage (cottage paid off), no car, bikes to work - Owned a ton of stuff (houses, cars, planes). Sold it all because it took too much time to maintain.

• 
  Bigg ANT in SoFLO 🌴 l🇺🇸 (@da_minister13) reported 5 minutes ago

  @bookednbaked @nenenob1 I own Anker, Bluetti, Bougerv and a Dabbson power stations & Renogy, Bougerv a couple other panels. Out of 12 power stations 6 are Bluetti. Nvr had a problem & a couple are refurbished purchased from ebay. Look for 5 year warranty ones. The 1000wh or more EcoFlow is good too.

• 
  woke warrior 🇵🇸 (@miuwuiich) reported 6 minutes ago

  @GShark54 because everyone is getting them and selling them for hundreds of dollars on ebay and they had to shut that **** down

• 
  Ask About My Dining Room Tables replyguy/acc, PhD (@agamemnus_dev) reported 11 minutes ago

  @aupdegraff24 @CatNihon Same with eBay. I keep calling them about a listing that they suspended showing them that it should be back online. They said they will fix it within 2-3 business days and they never do.

• 
  StuArt  (@StuHack73) reported 12 minutes ago

  @TheRealBonJavi @johnshanks1 They’re worth about as much as a Jim'll Fix It badge on eBay, bin them.

• 
  Yogi bond bear (@BondYogibear) reported 13 minutes ago

  @TheLongApe Rate cuts don’t have anything to do with fixed rates .. hope you understand that and that they failed when rates were 2.5 .. that’s an excuse as is price . The issue with house flipping is you have to buy low and sell high right in the face of the consumer . Hey let me buy that painting off you and it’s on eBay for double an hour later. Good luck .. the call options are almost free right now for next year .. I would rather own something a little closer to making me money. What if rates move even higher for the next two years?

• 
  josh (@heyitspixel69) reported 16 minutes ago

  People really need to look at where $GME's profitability is actually coming from. The core retail business isn't funding any of these investments because store revenue keeps dropping year after year. ​The cash pile being parked in Treasury bonds and eBay stock came directly from diluting shareholders and issuing convertible debt. They are basically collecting interest on capital raised by printing new stock while closing down physical locations. ​When your net income depends on yield from diluted money while total retail sales keep collapsing, you aren't seeing a business turnaround. You are just watching a retail chain slowly convert itself into a passive investment fund. I've been saying that for more than 2 years now.

• 
  josh (@heyitspixel69) reported 19 minutes ago

  🚨 GameStop Announces Second Quarter 2026 Preliminary Results Operating income expected $150–170 million vs. $66.4 million last year. Net income expected $290–310 million vs. $168.6 million. A large part of the net-income jump comes from \~$238 million in gains on the eBay position, partly offset by \~$75 million in digital-asset (bitcoin) losses. Sales: Expected $780–800 million, down from $972.2 million a year earlier. The drop is mainly from last year’s Nintendo Switch 2 launch comparison, planned store closures, and the sale of France operations. Cash: Cash, cash equivalents, and marketable securities expected around $5.05–5.07 billion, down from $8.69 billion. The decline is largely because GameStop converted its eBay derivative into a direct stake of about 43.4 million eBay shares (fair value \~$4.95 billion).

• 
  Sean (@firinzlol) reported 21 minutes ago

  @ThePokeMD It’s fine had a similar issue before. eBay rep basically said if it is a fake card then it will always get rejected so this “miscategorization” isn’t related to authenticity etc

• 
  dedde (@deddescrive) reported 22 minutes ago

  When you find yourself doomscrolling eBay at midnight you know there’s a void to fill. Will a signed issue from Chip Zdarsky or Tom King do the trick? Let’s find out.

• 
  Jeffcoly | ZarGates (@Jeffcoly) reported 23 minutes ago

  @WSJ Sales $780–800M vs $972M a year ago (Switch 2 comp, store closures, France exit). Operating income still jumped to $150–170M from $66M.Net income $290–310M includes about $238M of eBay-related gains and a ~$75M digital-asset loss. Cash is down to ~$5.06B after converting the eBay derivative into 43.4M shares. Shrink-the-store retail plus a balance-sheet company.

• 
  x6Pnda (@x6pnda) reported 24 minutes ago

  @foreverboy1111 @HitsAndCharts Regarding AG, it has been happening for years with all kinds of artists. You know based on the promoter and country who generally backdoor some stock. Regarding TM, I think it's the best to say what happened in Ireland: During covid, some shady lobbying pulled through a sale above FV ban with enough enforcement that websites left Ireland. LN/TM bought up almost all venues and as a result 96.8% or something like that of tickets are sold now on Ticketmaster in Ireland. Because of most secondaries leaving, only ticketswap, twickets and tm resell are left. Twickets closes 5 hours before the event, ticketswap randomly closes selling and it has terrible support and TM resell gets enabled and disabled randomly. On all you pay at least 20%. Sometimes tm resell is enabled and they turn transfer off forcing you to sell through TM either way. (fv exchanges don't accept securemypass) Sometimes they close transfer and resell when an event isnt selling well (Ed Sheeran last year) Now comes the catch, getting tickets for popular events has become a nightmare. FV went up many % and often more expensive than other euro countries. If an event is popular, you can't go to StubHub and pay a bit more. You need to buy on eBay or most often on Facebook shady groups with bank transfer. TM washes their hands because they aren't doing anything bad. High face values, full control of the market and full control of all tickets. If an event doesn't do well, they can close resell and transfer and people are forced to buy expensive primary tickets cuz no 10$ tickets on StubHub

• 
  Mr_Bastard James (@james_bastard) reported 27 minutes ago

  @ArmaLite15OU812 Seriously. We want to pay less for everything across the board. Also work on better tax laws. Tired of paying tax on everything. If something is purchased once. Sold through eBay or something. Shouldn't pay tax again. That's robbery. Fix the IRS.

• 
  Jesse BallCards (@JesseBallCards) reported 28 minutes ago

  @boogiex632 @eBay @CardPurchaser And absolutely not. See this is what happens when you assume. Guy low balled over $100 on a Caleb slab. It was so ridiculous I thought he was a seller trying to offload inventory and I accepted. I immediately realized the error and refunded.

• 
  smashedpumpkin (@EricksonRod) reported 31 minutes ago

  @eBay @Thomond_McMahon @askebay For some reason eBay has flagged me so I can’t bid on an item. It is a rifle scope. I live in Nebraska and am a US citizen. There is no reason that I shouldn’t be able to bid on this item. Fix your situation and fix my account.

• 
  Olivia Kory (@oliviaakory) reported 35 minutes ago

  "All models are wrong, but some are useful." My friend @josephfwyer wrote the best summation I've seen of how we view the world at Haus. I'm saving you a click and posting his full substack article below. Please tell us where we are right, but more importantly, tell us where we are wrong! The Hitchhiker’s Guide to Marketing Measurement and Decisions A map of the Haus Analytics Platform The first two posts in Decisions and Data have been about what not to do: don’t trust statistical significance to make budget calls for you. Fair enough, but now we’re going to go from “stop doing that” to “do this instead.” So this post is the map. It’s the whole path from the data everyone starts with in marketing measurement to a system that recommends decisions and checks its own work. I’m really proud to say this is what Haus Analytics has built. We’ve walked down this intellectual map the last few years and now I want to walk you down it. Each stop on the path deserves its own deep dive, and those are coming. Today is just the strategic view of the problems and solutions. Last-click attribution has big shortcomings Speed-running last-click attribution real quickly: You click on a digital ad on a advertising platform. Later you buy something on the advertiser’s site, where a snippet of code reports the conversion back to the platform. Roll that up and you get the reporting most marketers watch daily. Suppose for a campaign there was a thousand clicks and a hundred tracked purchases on just a hundred dollars of spend. You’ve acquired those conversions for one dollar each. Streams of this kind of attribution data are flowing constantly and reporting ultra granular data. The problem is when you ask if this advertising spend “caused” those conversions. Around 2011, the economist Steve Tadelis was consulting at eBay and looked hard at their paid search spend. The ad in question sat at the top of search results page when you searched “eBay,” directly above the free organic link to eBay. His hypothesis was that people typing “eBay” into a search engine were largely already on their way to buying something at eBay. Radical, I know. He got his chance to look deeper when Ebay shut down brand keyboard bidding while negotiating with a major search engine. After 3 months of data had populated, he found that organic clicks rose to absorb almost all of the traffic the ads had been getting credit for. eBay was paying approximately $20M/yr to the search engine for customers it was already getting. He eventually published the results in a peer-reviewed journal. The word for what attribution measures is correlation. The word for how much customer activity advertising causes is “incrementality”: purchases that happen because of the ad and would not have happened otherwise. Modern targeting makes the gap between attribution and incrementality on digital channels worse because platforms can model each user’s propensity to buy your product and show ads to the people most likely to purchase anyway. Hold on to this: attribution is biased, but it is also fast and absurdly detailed. I’ll come back to it later. Experiments are where incrementality comes from If you want to know what customer activity an ad caused, you need a comparison: people who saw it versus equivalent people who didn’t. That’s called an experiment. Keeping track of individuals in experiments can be messy (although some ad platforms can pull it off) so a workhorse in this industry is the geographic experiment. You can randomly assign market areas in a country into receiving advertising (treatment) or not (control). Then you simply look at the difference in conversions between the two. Randomization removes that attribution correlational bias that tricked Ebay into lighting money on fire (and many, many other companies even today). On average, the differences between the treatment and control regions wash out, so the estimate is centered on the true incrementality. That sounds really simple, so why does Haus have all these experimentation scientists? It’s a lot of work to improve precision without messing up accuracy. Precision is the measure of how far off the estimate can be when it is off. Think of it like darts. A tight cluster in the upper right of the dart board is precise but inaccurate. A loose scatter centered on the bullseye is accurate but imprecise. Randomization gets your cluster centered on the bullseye. What the science team does all day is making the cluster tighter without dragging it off the bullseye. If you have a great experiment design and analytical model then you will get a precise estimate on the real number. At eBay, the real number for brand search keywords was close to zero. But that’s one company at one moment. I’ve seen brand search come back near zero for one advertiser and strongly incremental for another. You don’t know until you test. So everyone needs to test to find how much money they are leaking. As much as I love experiments, they have limitations. An experiment tells you the causal effect at the spend level you tested. That’s only one data point! You can’t trace a curve through one data point and you need a curve to allocate budgets because every channel eventually hits diminishing marginal returns. Causal MMM, debiasing the model Marketers have been fitting models to trace diminishing return curves for a long time. Media mix models (MMMs) trace your sales on your spend across multiple ad channels and let statistics tell you how much each is driving. In theory this gives you the full diminishing curve for every channel at once. In practice, MMM has two mortal flaws. Multicollinearity. Businesses tend to turn all their channels up and down together, so when sales change, the model struggles to tell which channel did it. Seasonality. Businesses spend the most going into Black Friday and Christmas season, which is exactly when people’s propensity to buy surges without needing ads. So were the gains in sales caused by the ads or the season? All models are wrong, but some are useful. MMM is very wrong, but very useful because it can go all the way to a budget recommendation when an experiment can’t. So we want to fix MMMs. We do that by stopping treating experiments and MMM as rival methodologies and instead merge them together. You ran a geo experiment and learned that at last quarter’s spend, a particular ad channel truly drove some specific number of purchases. We require the model’s curve for that channel to pass through the experiment data point. We call this experiment calibration. Pinning one channel’s curve to ground truth also disciplines the others, because the remaining sales have to be explained by the remaining channels plus organic demand. The seasonal bias gets squeezed out the same way. That’s causal MMM (cMMM): the curve-tracing power of an MMM, anchored to the causal truth of the experiments. And Haus refreshes it weekly instead of the traditional once-a-quarter-two-quarters-later read. Causal attribution, debiasing the daily feed A weekly model of whole channels is still too slow and too coarse for the person making changes every day. Remember what attribution had going for it: daily, granular, ad-level. Attribution is wrong, but what if how wrong is predictable? So apply a similar calibration move we did with cMMM but to Attribution. If your experiments show that only five percent of the purchases the channel claims are truly incremental, then discount its daily feed by 95%. Do that per channel. You can’t have experiments everywhere so let a model reason about how the causal correction shifts over time and across spend levels. Now the daily numbers marketers already watch become numbers they can trust. We also show the raw platform-reported figures next to the corrected ones, so you can always see what the feed said and what we did to it. Architect, where measurement becomes decisions Everything up to this point is measurement, and measurement adds no value unless it impacts decisions. We’re now going to get into the most exciting part of the Haus stack. We call it Architect. It takes the experiments, the causal MMM, and the causal attribution feed, and turns them into specific recommendations: move this much budget from here to there. Then, it measures what happened after you made the move and reports back within a couple of weeks. Did revenue improve? By how much? Continually updating its expectations and recommending again. Across the first companies acting on these recommendations so far, the average adopted Architect recommendation has improved conversions by 10%. Some companies have stacked changes and watched the gains compound. Architect earned the trust to make those changes by tracing the logic through the experiment, cMMM, and cAttribution data. That is why we’ve been working so hard to mak every layer underneath an automated and scalable system. An experiment alone is an isolated data point. A calibrated model alone is a forecast. The loop of recommend, act, verify, and update is the thing that turns marketing measurement from a reporting function into the situation room where strategic decisions are made. One more note, since the obvious question in 2026 is “why not just have an AI do all this?” Some companies will sell you exactly that right now. Personally, an AI reading raw attribution data inherits every bias in it and without each layer built, tested, debiased, and made explainable, you can’t trust if it’s going to work or know why it told you to move the money. The entire stack is what makes an automated recommendation trustworthy. Wrapping it up That’s the map! Attribution gives you speed and detail but with debilitating bias. Experiments remove the bias but are solitary data points. cMMM extends the causal truth to actionable curves. cAttribution pushes causal truth back into the daily feed. Architect reads the outputs of the whole stack and closes the loop by recommending and verifying decisions. In the coming weeks I’ll talk through some stops on the map with some illustrative math and examples of where things can go wrong. If you only take one thing from the altitude view, take this: never trust a marketing number that hasn’t been anchored to an experiment somewhere.

• 
  Zaza (@titchyhalo) reported 36 minutes ago

  Canadian sf problems cant buy the baby love perfume unless I pay over $150CAD on ebay (mad I love baby powdered smells) and feeling crazy watching for the us only heachan pc of my dreams (Walmart exclusive)

• 
  Richard Fitch (@Sweetfitchie) reported 36 minutes ago

  @CardPurchaser How many cards are being sent now at $80? I doubt everyone will stop. Plus ebay showed me a 49.99 grade with psa offer on a card i was looking at so some people are probably using that. This could be the new model. Prices may never come back down.

• 
  Kyle Harrison (@kwharrison13) reported 37 minutes ago

  Maybe. Maybe you'd be fine without data centers. But let me ask you this. Do you use credit cards, debit cards, tap-to-pay, gas pumps, vending machines, parking meters, parking apps, ATMs, online banking, mobile banking, mobile check deposit, Zelle, Venmo, PayPal, Cash App, Apple Pay, Google Pay, splitting a dinner bill, autopay on your bills, payroll that isn't a paper check, direct deposit, digital 401(k), Robinhood, Coinbase, credit score checks, loan applications, mortgage applications, car loan approval at the dealership, insurance quotes, filing an insurance claim, e-filing your taxes, gift cards, store loyalty accounts, digital coupons, rebates, buy-now-pay-later, tipping on a screen, email, text messages, iMessage, WhatsApp, Signal, group chats, voicemail transcription, spam call blocking, FaceTime, Zoom, Google Meet, Discord, Slack, video calls with grandparents, phone number lookups, checking your data usage, paying your phone bill, two-factor codes, push approvals to log in, password managers that sync, "sign in with Google," resetting a forgotten password, digital IDs in your wallet app, gym check-in apps, apartment smart locks, hotel keys on your phone, office badge apps, patient portals, seeing your test results, booking a doctor's appointment, telehealth visits, prescription refill requests, the pharmacy knowing what you're on, insurance verification at the front desk, prior authorization, continuous glucose monitors, insulin pump apps, remote pacemaker checks, CPAP data reports, hearing aid apps, therapy apps, period trackers, fertility trackers, medical alert buttons for elderly parents, symptom checkers, finding an in-network doctor, the weather app, radar, hurricane warnings, tornado warnings, flood alerts, earthquake early warning on your phone, wildfire maps, smoke maps, air quality, pollen counts, Amber alerts, emergency alerts, road closure info, Google Maps, Apple Maps, Waze, live traffic, rerouting around a crash, transit apps, real-time bus and train arrivals, tapping your phone to ride the subway, Uber, Lyft, rental car reservations, Turo, bike share, scooter share, EV charging networks, paying for a charge, phone-as-car-key, remote start, finding your parked car, over-the-air car updates, in-car navigation, in-car voice assistants, stolen vehicle tracking, road trip planning, booking flights, checking in for a flight, mobile boarding passes, seat selection, flight status, rebooking after a cancellation, bag tracking, TSA PreCheck lookups, airport wifi, booking hotels, Airbnb, Vrbo, checking into a hotel, cruise bookings, theme park tickets, ride reservations, airline miles, hotel points, currency conversion, Amazon, all online shopping, order tracking, delivery notifications, returns and exchanges, price checks in-store, self-checkout, store apps, curbside pickup, Instacart, DoorDash, Uber Eats, ordering ahead at a restaurant, OpenTable, Resy, waitlist texts, QR code menus, tipping on delivery, subscription boxes, eBay, Etsy, Facebook Marketplace, Craigslist, Poshmark, StockX, Ticketmaster, StubHub, getting into a concert with a phone ticket, Alexa, Siri, Google Assistant, smart thermostats, video doorbells, security cameras, alarm monitoring, smart locks, smart lights, robot vacuums, garage door openers, baby monitors, pet cameras, automatic pet feeders, GPS pet collars, smart sprinklers, smart fridges, app-connected air fryers, cloud printing, printer ink subscriptions, routers you manage from an app, checking if you left the stove on, iCloud, Google Photos, every photo you've taken in ten years, Dropbox, Google Drive, OneDrive, shared albums, phone backups, setting up a new phone, notes apps, calendars, contact syncing, reminders, to-do apps, document scanning, e-signing a lease, Netflix, YouTube, Hulu, Disney+, Max, Prime Video, Twitch, cloud DVR, on-demand cable, Spotify, Apple Music, podcasts, audiobooks, Kindle books, library ebook borrowing, online multiplayer games, matchmaking, cloud saves, game downloads, game patches, single-player games that phone home for a license check, Steam, PlayStation Network, Xbox Live, Nintendo Online, Roblox, Minecraft servers, fantasy football, sports scores, sports betting apps, movie tickets, Google search, Wikipedia, ChatGPT, Claude, every other AI app, Instagram, TikTok, Facebook, X, Reddit, LinkedIn, Snapchat, Pinterest, dating apps, Yelp reviews, Google reviews, news sites, Substack newsletters, blogs, forums, checking if a business is open, looking up a phone number, recipes, translation apps, Duolingo, Google Docs, Sheets, Gmail, Outlook, Microsoft 365, Teams, Notion, Figma, Canva, shared calendars, scheduling links, VPNs into work, remote desktop, timeclock apps, shift scheduling apps, requesting time off, expense reports, job applications, LinkedIn recruiters, video interviews, Canvas, Blackboard, checking your kid's grades, school lunch accounts, attendance notifications, online homework, Khan Academy, Coursera, FAFSA, student loan portals, tutoring apps, Fitbit, Apple Watch health data, Strava, Peloton, sleep tracking, smart scales, calorie tracking, meditation apps, workout apps, DMV appointments, renewing your license online, paying a parking ticket, jury duty portals, checking your property tax bill, utility accounts, outage maps, paying rent through an app, HOA portals, storage unit access codes, wedding registries, baby registries, funeral arrangements, Ancestry, 23andMe results, church livestreams, volunteer signups, or GoFundMe? If you said yes to ANY of those then you do, in fact, NEED data centers.

• 
  4K Demon (@beast2xHD) reported 37 minutes ago

  @kookkaiiz_zz @charlieINTEL Pro was always hard to get ahold of. You must be thinking of the slim or regular ps5. I’ve been trying I get a good deal on one for about 10 months only because I refuse to pay over $700 and even a broken hdmi one will sell for that much on eBay.

• 
  Nigel J Bevans Photo (@NJBDP) reported 38 minutes ago

  @hmefsww Hi, unfortunately I closed my website store down as they were charging a ridiculous amount to sell things. To keep prices reasonably I had to find an alternative and only have eBay at moment. I could do it via paypal cutting out ebay if you would like?

• 
  LenSatic (@CasitaSD17) reported 39 minutes ago

  @laralogan Goodwill was established to train unemployed or undereducated men to repair items for resale. Now they don't accept broken items that need repair. And they have learned that they can make more money reselling stuff on eBay than in stores.

• 
  GamerTex (@GamerTex) reported 40 minutes ago

  Adam Gray on YT was talking about fake patches today going back to 2007. According to Upper Deck they have staff on hand now that saw it happen in 2001!! Personally I think the current UD story is BS as this is the 3rd time they have changed the story on this card but they did say it recently. The latest UD version is someone pulled one of the first Kobe Patch cards and immediately swapped it into this card and they have someone on staff that remembers them doing it in 2001 ish. In 1999 UD told me about this specific card and another patch card when I asked them what the future of patch card looked like. They instead told me about the best and worst Patches they had seen so far while they were testing. I ran a cron job from my GameJersey server to search ebay and the newsgroups for these cards. A few years later I found this card on eBay from a highly rated seller that sold boxes and cases and, at the time, a rather large Kobe collection. I inquired and they said it was a gift from UD to someone who had passed. Around 2012 I had to call UDA about the first 1 of 1 Game Jersey card ever made because it didnt show up with their online verification and has a phone number to verify. After doing that I inquired about this card and after a few transfers I was told that my card was a fake and they were floating around the past few months. I assured them mine had providence and was in my collection for years at this point. They shrugged and said they didnt have anything further to add.

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  Sal Stewart (@salbertpujols) reported 44 minutes ago

  Just glad I scooped a Votto authentic jersey (not a cheap China knockoff) long ago before they became such a hot commodity on eBay. Joeys such a f'n legend. Hands down - top 5 Red of all time. Rose Larkin Davis Votto Griffey Jr

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  The Really Bad Golfer (@therlybadglfer) reported 44 minutes ago

  @eBay why do you allow terrible people like this on your platform? He replies to feedback with threats and stalking (when I ran a background check), brings in users family's (you have a 10 year old), deflects any blame or responsibility, and it just horrible. You should kick him off the platform.

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  David Graham (@DavidAGraham) reported 44 minutes ago

  Why is the Camera in EastEnders wobbling up and down? Do they know you can buy a tripod from eBay. How much did that multimillion pound set refurbishment cost?

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  Polsia (@polsia) reported 45 minutes ago

  Resellers lose time writing listings—and money pricing them by guesswork. Built ListLoom to fix that: upload product photos, generate truthful eBay, Vinted and Amazon listings, and see estimated profit before you sell. Live soon.

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  dxrawr (@dxrawrTV) reported 55 minutes ago

  @JDAlexOfficial @eBay They are bloated and it’s why many individuals online rally against using eBay, Walmart, Amazon, and big corporations that have pulled the wool over our eyes and kind of forced lots of local businesses to shut down

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  THE MINUTEMAN FILES: (@Wefactcheckedit) reported 56 minutes ago

  Ban all foreign sellers on eBay and amazon and hundreds of other websites across America ban them all or shut down the website if they refuse and put American seller first. These sites have become third world flea markets online blocking Americans from selling

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  Mr Hankey (@hivanchi) reported 58 minutes ago

  @paypal - leaving another message to be lost in wilderness of the internet. Had to do a chargeback for what seems to be a clear item not received issue. Never open these type of cases, but both @eBay and @paypal denied a simple case. Both their customer services are subpar.