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 (64%)
• Sign in (22%)
• Errors (13%)

Live Outage Map

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

City	Problem Type	Report Time
Preston	Website Down	8 hours ago
Hannoversch Münden	Sign in	11 hours ago
Blackpool	Sign in	14 hours ago
Preston	Website Down	16 hours ago
Preston	Website Down	22 hours ago
Mauléon-Licharre	Sign in	1 day 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:

• 
  Corner Card Collector (@CCCollectorTCG) reported 3 minutes ago

  When selling on eBay if you see a third-party shipping company do you have issues or concern shipping the card? I always seem to have problems with ship my cards.

• 
  Byron Vallis (@Byronnn6) reported 4 minutes ago

  @calvinfroedge Free shipping and eBay fees will knock this down to like $4.5 my friend. Better luck next time

• 
  Psygnosevo (@ytevo79) reported 6 minutes ago

  Ive had an £80 offer from ebay for the first game (pictured) down from £100, but the manual has a tear mark so that puts me off. But I might pop back into that shop and get the sequel first as its a good price if its good condition.. Tis a shame only now Im interested in these!

• 
  🕯️ (@sixlinekenner) reported 7 minutes ago

  resolution to not buy more dolls this week broken by $50 ebay pullip #yay

• 
  Allyson 🪷 Bento (@NoSurrender_87) reported 12 minutes ago

  @Jtsbae69 I started using eBay in college & stick with that since I’ve built reviews. Starting fresh, I’d go down a Reddit rabbit hole, there are so many damn options now. See what sounds best. Make sure whatever you go with has seller protections!

• 
  LenSatic (@CasitaSD17) reported 13 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.

• 
  Richard Thomas (@BayleySportCard) reported 13 minutes ago

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

• 
  A.P.O.C (@AOchiawuto) reported 14 minutes ago

  @AirtelNigeria @lydiacreatesng Airtel Nigeria, why is your service so poor? I’ve tried registering on eBay, but the verification code never arrives on my Airtel line. Yet, the same code comes through immediately on MTN. What’s wrong with Airtel? Is Nigeria cursed? Please fix your SMS service!

• 
  Archer (@Archer471653301) reported 14 minutes ago

  @NINJA_2029 @PanthoriusPrime Calm down ninja go to Ebay its a scalper sell out.

• 
  Driftbound - Father Son Card Slinging (@dRIFTBOUNDtcg) reported 15 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.

• 
  Pokémon Deals, Restock and Alerts (@PokemonRestockr) reported 17 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

• 
  maeve (@lizziedossss) reported 18 minutes ago

  @TheShazamPow i actually looked this up the other day. its technically a grey area but it is blacklisted from ebay. so yes its a problem if you sell it but apparently owning it is fine?

• 
  Mr Hankey (@hivanchi) reported 21 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.

• 
  ᴅᴏɴᴏᴠᴀɴ² 🇺🇸🇬🇧 (@arcanedonovan) reported 23 minutes ago

  @PunchingCat @michiganstan25 i put them on ebay for my house down payment

• 
  slicko (@haribo4me) reported 24 minutes ago

  @GoatBeardzDD @MaiDuat31103 When company A acquires company B, doesn’t the stock price of A typically go down while B goes up? So in this case shouldn’t we expect GME to dip if they are successful at acquiring eBay?

• 
  WesleyTech (@WesleyTech) reported 25 minutes ago

  eBay is the king of terrible customer experiences. 1 example of many: They make you solve a captcha in order to LOG OUT of your account on the web app 🤬

• 
  Grey (@LeeGrey1105) reported 28 minutes ago

  @MaddiesMorgue SAME I NEVER THOUGHT ID HAVE HER, now I just have to try to hunt her boots and skirt down on ebay 😭

• 
  Ratchlock in the Rain ⛈️🥀 (@DamnitKnightly) reported 39 minutes ago

  @boomboomfaia Yeah we had to turn off shipping TO the EU because of LUCID and the new PPWR rulings (US based issue for Etsy/Ebay) But I do believe acggoods does handle most of that since they are the ones producing and shipping the items. Only thing is the tariffs but that is customer based

• 
  Olivia Kory (@oliviaakory) reported 39 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.

• 
  Carolina24 (@c_collector24) reported 40 minutes ago

  @pasch_8759_eBay @CardPurchaser @tm1515152005 Had the same issue yesterday (TWICE) with the same Kirby Puckett card that I even talked to an eBay representative about and he suggested I just relist it? No idea what they’re doing with their new AI filters

• 
  Lanny Ribes (@DOCBZ17) reported 42 minutes ago

  Ok I took my original post down, tried to choose positivity today. But this is absolutely ridiculous. Bought a card on @ebay and got confirmation of my purchase from @PSAcard vault. $325. A few minutes later I received a notification that the card had been relisted. That’s

• 
  RD's caRD's (@rdaex1) reported 42 minutes ago

  Explain the issues for us to see if you're trustworthy or not. It's a 10$ card man you're not giving the winner a Tesla. If you don't have the card in hand, just Buy it on eBay and just send it to him... If you won't do something this simple, please stop trying to infiltrate your way into this space.

• 
  yolanda j smith-bond (@yolandajsmmqc) reported 42 minutes ago

  @netnanny @Rbls24 Wanted to move discussion from Twitter (X) to @LiveJournal My login from funci* is messed up, msgd Dave's wife yesterday, & McGough from DMS (bombing by Frost Bank downtown messed up the LJ platform in ~2003). I forget ____________ tried to sell it on a shell version of eBay.

• 
  Germainrain (@germainraine) reported 46 minutes ago

  @cmpayneful @GameStopOnChain Consider this a rabbit hole, but if you choose to go down, will lead to more… like XRP. Surprisingly this stuff connected to Epstein, which is why the DOJ is gonna be important. If I were to guess I think eBay was permitting trafficking kids likewise to JP Morgan

• 
  Brandon Coty (@cotycollects) reported 47 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.

• 
  Kat 🦋 (@ArtemusBlue) reported 48 minutes ago

  @Kurumi96Neko @WholesomeMeme Earphone jack to USB-C adaptor, you can get them for like £3 off Ebay ✨ Problem solved, and it even extends your cable a bit!

• 
  Gavin Forsyth (@Gavin4syth) reported 52 minutes ago

  @eBay @askebay This does not work. The options only loop with no option to resolve my issue because I cannot contact an agent by phone.

• 
  ｃｈｅｄｄａｒ (@cheddar420yolo) reported 53 minutes ago

  @IndefiniteLT @VibesMBSE it was before my time but part of CARTER lore is they took a rogue wave shifting home ports from northeast to Bangor. a water column came down the hatch and the ship's computer was right there they had to get the replacement computer from ebay that was the story anyway

• 
  Kiro (@KiroIkigai) reported 57 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

• 
  Cori (DemShenaniganss) 🦝 | #TDST ⚡️ (@DemShenanigans) reported 58 minutes ago

  @Artemishowl_ Former SH staff circa early days (2010s) here: Can confirm, ebay kept the **** parts and got rid of the people like us who made sure that the same or better upgrades were offered. Afaik even shut down the main corporate office thay used to be in CT