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 (62%)
• Sign in (23%)
• Errors (15%)

Live Outage Map

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

City	Problem Type	Report Time
Manchester	Website Down	7 hours ago
Manchester	Website Down	12 hours ago
Gateshead	Website Down	20 hours ago
Manchester	Website Down	1 day ago
Manchester	Website Down	2 days ago
Manchester	Website Down	2 days 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:

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  T-Bob Hebert (@TBob53) reported 3 minutes ago

  I remember getting this issue in a giant haul from eBay when I was younger

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  Terence Smith (@SocialistTerry) reported 3 minutes ago

  So I made a complaint, got auto response saying no regulations broken. Appealed, response 12 hours later saying same 😯😳 @eBay_UK @eBay Why do you allow sellers to defraud buyers by letting them cancel the order, change the price, ask them to reorder, & hope they won't notice?

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  Brent Wendland (@BrentWendland) reported 4 minutes ago

  @packaddictsnw Yeah eBay needs to do something with the tracking on these. I’ve gotten way more “buyer didn’t receive item” and have to issue a refund.

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  Mr8000 (@mr8mil) reported 5 minutes ago

  A few weeks back I bought this card from a tip on @enzo_tcg discrod. This card comes from the Blue Trial Deck of FW from 2023, basically one of the first leader cards of all FW. Hard to find in EN, this is the only version I could get my hands on EBay. Even if this card does not meet expectations down the road, I love the “vintagy” look of it. Source and user name: dissociated, thanks for bringing this into attention. Appreciate it!

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  Pokémon Deals, Restock and Alerts (@PokemonRestockr) reported 14 minutes ago

  @J_Vetter14 @Stassibaby12 @Pacho9_3 I assume it was ebay to took the seller down, keep me updated on what happens. Wild times

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  Richard Thomas (@BayleySportCard) reported 15 minutes ago

  Anyone know how to fix the Ebay app to send offers?

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  Driftbound - Father Son Card Slinging (@dRIFTBOUNDtcg) reported 16 minutes ago

  35 T1 box transactions on ebay yesterday. One sale for a raw Miss Fortune as the auction ended at $7k Is this higher or lower than you expected? I think it will settle down significantly as more supply hits the market. By next week we might have 30 auctions going on at once, and inevitably some will fall between the cracks, going for well below the established market.

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  marqix ☆ (@fwmarqix) reported 18 minutes ago

  My librarian Janet was running a book laundering scheme where she checked out books under dead people's names, reported them lost, pocketed the replacement fees, then resold the "lost" books online. Discovered this when my dead grandmother's library card got a overdue notice. "Grandma's been dead for three years." "Oh no, our system must have glitched," Janet said. But the book was real. Someone checked out "The Goldfinch" under her name last week. I checked records. Grandma's card had been active for three years. 47 books checked out. All "lost." All replacement fees paid from a account I'd never seen. Confronted Janet. "You're running a fraud scheme with dead people's library cards." "I'm maintaining circulation metrics for funding purposes." "You're stealing." She showed me the books budget. Cut by 40% over three years. "I'm keeping this library alive. The replacement fees fund new books. The 'lost' books get resold. Money goes back into the system." "Through your pocket." "Some administrative costs are involved, yes." She'd been doing it for five years. 200 dead people's cards. $180,000 in replacement fees. Books resold on eBay for another $90,000. All money went back into library programs. Story time. Teen literacy. Computer access. "You're Robin Hood but make it books?" "I prefer Marian the Librarian but yes." I should've reported it. But the library was thriving. Programs everywhere. New books weekly. Then an auditor noticed the pattern. Investigated. Found everything. Janet was fired. Police got involved. Community rallied. "Janet saved this library." Petition to drop charges: 4,000 signatures. Charges dropped. Janet was rehired with "enhanced oversight." She's not allowed to handle money anymore. But circulation is down 30%. Programs are being cut. Janet started a nonprofit. "Friends of the Library Foundation." Runs fundraisers. All legal now. Raised $200,000 last year. Library is thriving again. I asked if she missed the scheme. "Every day. It was elegant. But this is better. Harder, but better." My grandmother's library card finally got deactivated. Last book checked out under her name: "How to Get Away With Murder." Janet swears it wasn't her. I believe her but I also don't.

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  Mike Palmer (シネフィル) 🎬 (@MikePalmerYT) reported 21 minutes ago

  Since July this year there are severe problems with orders from Japan and delivered from Japan Post in the European Union. I had three cases so far, and every parcel has been send back to Japan. A few days ago I ordered something very expensive of eBay.

• 
  Olivia Kory (@oliviaakory) reported 24 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.

• 
  dxrawr (@dxrawrTV) reported 24 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

• 
  Kiro (@KiroIkigai) reported 25 minutes ago

  The most reliable way to misread an earnings report is to start at the bottom line. $GME just posted preliminary net income up roughly 78% on net sales down roughly 19%. Both numbers are real. Only one of them is about the business. The quarter, company figures: -net sales: $780M to $800M, vs $972.2M a year ago -net income: $290M to $310M, vs $168.6M -operating income: $150M to $170M, vs $66.4M The bridge from falling sales to rising profit is one line. Roughly $238M of gains on an eBay derivative asset and an equity investment, less roughly $75M of digital-asset losses. about $163M of pre-tax marks. For scale: that eBay exposure is carried at about $4.947B. the company books about $790M of sales in a quarter. when the portfolio is that big, the income statement is partly a report on the portfolio. Credit where due: operating income more than doubled. that is a bigger percentage jump than the net income line everyone quotes. smaller, tighter, better-run retailer. real progress. not the headline story. Keep this part: -net income up while revenue is down: find the non-operating line first. it is usually one line, and it is usually named -size the securities book against the operating result. a $5B position swamps a sub-$200M quarter, in both directions -falling sales with improving operating income is a cost story. real, but a different story from the headline I am fully invested, and none of this changes that. guidance direction and price reaction have been disagreeing all earnings season. last Thursday five of seven reporters raised guidance and four of the seven closed lower. reading the price as the verdict on the numbers is the error. The case against: I may be underselling the operating turn, which more than doubled at every point of the guided range. and these are preliminary figures. no call is scheduled, and complete results are due September 8. $GME $EBAY

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  Eric the Red / Kelenic Collector (@FatherBreaks) reported 27 minutes ago

  @eBay when a seller chooses your ESE option and pays for it, it should come out at that time just like any other service one chooses to ship with. It’s annoying as hell to see my balance go down 2-3 day later and have to track which fee it was for

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  Clazziquai (@Clazziquai_Nico) reported 28 minutes ago

  @TheNTDOfan Might have to hunt one down on ebay or Vinted

• 
  EverydayReseller (@EverydayResell) reported 33 minutes ago

  Day 206 Total sales: $1,148.99 eBay earnings: $854.40 Buy cost (COG): $296.57 Net profit: $557.83 ROI: 188% Items sold: Home protection equipment, pressure washer part, automotive part, battery charger, carburetor, & sports training equipment. Another $1K+ sales day. 🔥 The key is having enough quality inventory listed to make these days possible. Today's sales also came from several completely different categories, which continues to reinforce the importance of diversifying inventory rather than relying on one type of product. The work continues behind the scenes too. Refresh old listings Fix listings that aren't getting attention Adjust pricing on stale inventory Keep sourcing Keep listing 206 days in & I'm still pushing forward. Some days are small. Some days are big. But the goal is the same every day, keep moving the business forward. On to Day 207. 📦💪🚀

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  Eric (@GhostRunnerCard) reported 37 minutes ago

  @CCCollectorTCG I ship via eBay to third-party shipping companies almost daily. I've never had any concerns or issues with them. All the orders work out fine.

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  🦊 (@whatthefox___) reported 42 minutes ago

  @kaetoceros Only people on eBay are paying that much and the sales are slowing down. People at my locals were selling them for 150

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  Mr Hankey (@hivanchi) reported 46 minutes ago

  @eBay and sellers game the feedback removal. Removed negative feedback that was left after legitimate issue with an order.

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  Mike Boysen (JTBD/acc) (@mikeboysen) reported 46 minutes ago

  Most people never see the inversion coming. They see the crash. The coup. The empty bank account. The factory that will not ship. Then they analogize: more staff, more robots, more of last year’s stack. Innovators do the opposite. They stay in the problem until the cost curve breaks. PayPal ousted Musk in 2000 for pushing a rebrand and a Unix-to-Windows NT migration. He did not wage a public war. He stayed a shareholder. eBay paid $1.5 billion in 2002. His ~11.7% stake — about $180 million — funded SpaceX and Tesla. By late 2008 both companies were days from death. Three Falcon 1 failures. Tesla about to miss payroll. One last rocket. Flight 4 worked on September 28. NASA signed $1.6 billion in December. He put his remaining cash into a $20 million Tesla bridge that closed Christmas Eve. Analogical thinking said “stop.” Physics said “one more launch.” Reusable first stages. Manual labor where the robots jammed. 5,000 Model 3s a week after he ripped out the over-automated line and slept on the floor. 75% of Twitter’s headcount gone so the cost of running the network inverted. That is not grit as a slogan. That is inverting labor, capital, and infrastructure until unit economics work. Follow people who have innovated at least once. Not the ones narrating the next analog. I built a platform to help average people think like that before you commit the capital. More on that soon. This is 100% a real interview LOL

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  Number 5 (@NumberFiveAlive) reported 49 minutes ago

  @clarkknowscards @phatjer300 @OnlyCharizard If you select “buyer requested cancellation” it will not ding your eBay account. All the other options from the drop down menu do. I lost top rated seller once for cancelling just 2 orders within a couple months.

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  GamerTex (@GamerTex) reported 50 minutes ago

  @card_history @UpperDeckSports In 1999 Upper Deck told me about a few of the first Patch cards ever made. The best and worst as they put it. The WORST was a yet unreleased employee card with a distinct error i how the patch was inserted. A few months later the first Jordan employee card was released. After years of looking I never found the Jordan card that was described. The 'best' patch they described is attached. I found it after years of searching the newsgroups, sportsnet and ebay.

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  Andres Fernandez (@Brok3rFernandez) reported 52 minutes ago

  @643DoublPlay @CardPurchaser He actually is asking over $10k on eBay so I got him down to $7k

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  Brandon Coty (@cotycollects) reported 52 minutes ago

  Just bought 180 tested video games across generations for about $2.50-$3 / game. The previous batch was $2/game. Sounds crazy when you can see on eBay some of these only selling for $6-8. But I also see something that made me question this. 52 minutes south of me a video game store exists that sells these games for at least $20+ The same games you’d comp on eBay for much less. Why? Because it’s hard to trust random sellers and in this niche I’ve see people want to buy from people they like, people they trust and people they vibe with. Therefore I’m buying a disc refurbishment machine and offering a “warranty” to my future customers where if a disc stops working, we’ll fix it to the best of our ability. I’m also packaging games with the consoles we test and increasing the prices and will have a branded website off of marketplace platforms. Does this take reselling to the next level? Yes. Will it be difficult for me? No. It’ll actually be quite fun and we’ll act a little bit like game informer for retro games. If it doesn’t workout? Cool. If it does? That’s a fun way to resell.

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  brandon (@trancetheartist) reported 53 minutes ago

  @MTGSecretLair ngl that queue was nasty today - first issue since ordering from you guys. waited in queue for 3 hours just for it to sell out immediately after sales started again. multiple listings on ebay for over retail. kinda sucks :/

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  Danny Bennett (@RealDannyB) reported 53 minutes ago

  LONG READ: Off-brand post, but as a longtime @Nike shareholder, this needs to be said. Nike used to be a company you could invest in and trust to run itself. Now the stock is trading in the high $30’s, a fresh 12-year low, down roughly 76% from its all-time high of $163.63 in November 2021. This didn’t happen overnight. It’s been a slow burn downhill. In 2020, Nike handed the company to John Donahoe, a former eBay and ServiceNow executive with a consulting background and no real history in sneakers or sport. The stock hit its all-time high under him in November 2021, but that wasn’t a product win, it was pandemic tailwinds. Lockdown spending and a digital sales boom carried the whole brand. Donahoe leaned into it, pulling back from wholesale partners like Foot Locker and Amazon to chase direct-to-consumer sales. It worked while the boom lasted. The second it ended, that same move handed Hoka, On, and New Balance the shelf space to take over. He spent the rest of his tenure cutting costs and squeezing profit out of old product instead of investing in anything new. On June 28, 2024, Nike’s stock fell 20% in a single day after weak earnings and guidance for a 10% revenue decline, its worst trading day in 44 years as a public company. It never really recovered. Nike has now erased roughly $200 billion in market value since its 2021 peak, the largest drawdown in the company’s history. Even Jordan Brand, the crown jewel, isn’t safe. Revenue fell from $8.7 billion in 2024 to $7 billion in 2026, two straight years of decline. Hoka went from $153 million to $2.6 billion in sales in eight years. On grew 285% in three years. Nike handed them the shelf space and gave people no reason to buy new. Stop putting bean counters and consultants in charge of a brand people love. Put product people back in charge. Open the SNKRS app right now. The Jordan 4 “Rare Air” Tour Yellow drops September 5th, a 20-year-old colorway from 2006, priced at $220. A shoe that’s already been made once, repackaged, made cheaper than its original release and marked up. Stop chasing what flippers on StockX think a re-release is worth. Price product for the people who actually want to wear it. Every dollar Nike hands to resale culture is a dollar it’s not making itself, and a customer it’s not building loyalty with. Nike has an entire team of engineers dedicated to fighting bots on SNKRS, blocking billions of fake entries every month just to protect launches like this. You wouldn’t need bot protection if you weren’t manufacturing the scarcity yourself, especially when a good chunk of these same releases end up marked down in outlets and clearance stores months later anyway. So what was the artificial scarcity even for? Elliott Hill spent 32 years at Nike, most of it running product, commerce, and marketing, before retiring in 2020. Now he’s back, cleaning up a mess a consultant-era CEO left behind. Even so, JPMorgan just downgraded the stock again this month, warning the pain from the turnaround won’t stabilize until fiscal 2028. Bringing back someone who actually gets the brand is the right move. But, it shouldn’t have taken a 76% collapse to get there.

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  Richard Fitch (@Sweetfitchie) reported 58 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.

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  ❤️𝖙𝖆𝖝𝖎 // 𝖉𝖊𝖗𝖒𝖞🖤 VTuber (@taximalsVT) reported 60 minutes ago

  one of these ace attorney pachislo showed up on ebay years back (pre covid) and i honestly almost bought it the only thing that stopped me is i would have no idea how to fix it if it broke

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  DogsBeAwesome (@Glasz_Half_Full) reported 1 hour ago

  @mikelectricstuf @FedEx Before brexshit I used to have a small ebay store that sent parts overseas. Royal Mail had the same problem too.

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  Alex Thompson (@sierrastrades) reported 1 hour ago

  TL;DR Sales down, profits up, cash lower because they turned the eBay options into real shares. • Sales: $780–800M vs $972M last year. Drop is mostly Switch 2 anniversary, store closures, and selling France. • Operating income: $150–170M vs $66M. Core operations got a lot more profitable. • Net income: $290–310M vs $169M. Includes ~$238M eBay gain, minus ~$75M digital-asset loss. • Cash: $5.05–5.07B vs $8.69B last year. Cash fell because they converted the eBay derivatives into 43.4 million eBay shares, now worth about $4.95B. • Full results drop September 8.

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  Pokémon Deals, Restock and Alerts (@PokemonRestockr) reported 1 hour ago

  @Pacho9_3 It looks like eBay just took down another seller of the 30th pre orders. Seems only seasoned sellers like footballpete and a few others are actually safe. I think I’ll avoid posting 30th eBay links regardless moving forward until September 16th