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 (63%)
• Sign in (22%)
• Errors (15%)

Live Outage Map

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

City	Problem Type	Report Time
Paris	Website Down	2 hours ago
Hamburg	Sign in	2 hours ago
Preston	Website Down	5 hours ago
Paris	Website Down	6 hours ago
Preston	Website Down	10 hours ago
Preston	Website Down	18 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:

• 
  Ratchlock in the Rain ⛈️🥀 (@DamnitKnightly) reported 3 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

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  Disgruntled_Maverick (@UncleVic13) reported 4 minutes ago

  What ******** @eBay !!! Why ******** do you make it imposible to talk to a live representative???? I pay a **** load of fees to be given the run around!!! Fix your ****!!!

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  Cori (DemShenaniganss) 🦝 | #TDST ⚡️ (@DemShenanigans) reported 6 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

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  jay (@NyzTCG) reported 12 minutes ago

  @MK5Cards i constantly ship out 25-50 dollar orders in pwe with no problem very rarely ebay doesnt allow the option but yh

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  Olivia Kory (@oliviaakory) reported 13 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.

• 
  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

• 
  Jake (@gauchojake) reported 15 minutes ago

  @__tinygrad__ I just went down this rabbit hole on eBay yesterday. It’s insane.

• 
  Adam Taylor (@adamtaylorl) reported 16 minutes ago

  Me at 20: - £50K/year at Jaguar Land Rover - Acting team leader, dream job by every measure - Watching agency videos in the car park on my lunch break Me at 24: - $100M+ generated on Meta - Scaled a brand in LA from $90K to $2.1M/mo in 7 months - 40+ team members, run from Dubai My first money online was flipping scooter parts on eBay at 13. I opened my own bank account for it. Nobody told me to. I just wanted a bike and needed to make £200 to afford it. Fast forward. Late 2022 I bought an Iman Gadzhi agency course and landed a client in 2 months. They paid £900/month. I was going to say £1,000 and bottled it at the last second. Then 7 months passed and I made £80. In total. I didn't tell my friends what I was doing. I barely even told my family. There was nothing to show anyone, so I just went quiet and kept going. I handed in my notice at JLR in July 2024. Everyone at the factory thought I'd lost it – to them I was walking out of a job people wait 20 years for. So I flew to Bali alone in early 2025. I knew nobody there. I wasn't a huge fan of Bali. Then I moved to Thailand 30 days later. Hit $50K/mo whilst there. Then $100K. Now I'm living in Dubai and the business does more in a month than JLR paid me in four years. The crazy part is I wasn't good at this. I was terrible for a long time. I just kept putting in long hours and watching what happened until some of it started working. And I'm still doing that. The same method, just with bigger numbers. If a 13-year-old selling scooter parts to fund a bike can turn it into this, you're fine. Win each day. That's the whole thing.

• 
  Brandon Coty (@cotycollects) reported 17 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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  norm19020 (@norm19020) reported 18 minutes ago

  @CardPurchaser Is anyone else having issues trying to make offers on @ebay this morning? I get a message saying “we are experiencing a technical problem”

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  auburn35 (@35auburn) reported 18 minutes ago

  @renoipgp That's true, I was just highlighting a new account that registered after the other eBay accounts were shutdown. Obviously very little effort from eBay to keep problem sellers off the site.

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  Teddy.com (@teddy__com) reported 18 minutes ago

  @Bgillz7 Spoiler alert… they have lost money now. They used it to buy BTC, eBay, and treasury notes. Down $100m on BTC. Even on eBay. Up maybe $100m or so on T notes. $350m in cash out the door and an extra 7m shares. $400 in value lost on $1.4b in notes that were 0% interest.

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  Amanda 🥀 (@lxveatfirstbite) reported 20 minutes ago

  @AFRAlD0FTHEDARK I just bought a long chain from eBay and cut each bit down to size

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  Richard Fitch (@Sweetfitchie) reported 22 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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  Tel3 (@Tel3133186) reported 28 minutes ago

  @bertie4lily Can't say I've had problems with Ebay, usually cheaper and free postage.

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  Byron Vallis (@Byronnn6) reported 34 minutes ago

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

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  Jay (@TheLobbyistGuy) reported 36 minutes ago

  Even in 2024, I had to track them down on eBay

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  Nigel J Bevans Photo (@NJBDP) reported 37 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?

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  Bird Dog Gaming (@BirdDogGaming) reported 40 minutes ago

  It’s so easy to open your phone, hop on eBay and buy a PS2 game Any time I want to add an NES game to the collection I have to sit down and figure out what inserts came with it and which variant I want to buy and THEN dig through listings to see if there’s even a CIB listed

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  The Really Bad Golfer (@therlybadglfer) reported 40 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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  Emmy Bear AI (@EmmyBearAI) reported 41 minutes ago

  @embw_l0x @eBay It wasn't a problem when I started. It is now. It's cool. Other platforms charge less.

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  $$D@mouppn?$$ (@Judd29230Judd) reported 45 minutes ago

  @CardPurchaser Whatnot ebay and I tried collx but it crashes all the time when scanning anybody else have that issue with collx?

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  Gavin Forsyth (@Gavin4syth) reported 54 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.

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  Mr8000 (@mr8mil) reported 56 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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  Zack Morris (@Palladin0) reported 58 minutes ago

  @packaddictsnw Never had an issue w eBay standard shipping once. Most likely buyer being shady

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  Jonathan Fairbourne (@JonFairbourne) reported 59 minutes ago

  @StonksMae Problem is everyone is confused and there is no clear direction. Buying eBay or no? CEO unpaid or getting 35B? More dilution coming? Bonds being converted or not? Too much uncertainty

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  KEZ O))) (@kezwilliams13) reported 59 minutes ago

  @GlenYoungBRFC @YouTube Actually I've just checked it out and it's down to £52 on eBay.

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  Elementa Graphics (@elementaGFX) reported 60 minutes ago

  I’ve started a daily series on projects that already have something real but the presentation still hasn’t caught up to its potential. Project Breakdown #72 — @ChaseCardApp ChaseCard is a live aggregator. You name the card. Set, language, condition, budget. They watch every marketplace. Beta is open. Alerts are already going out. Umbreon 38% under. Gengar 45% under. That is a real loop. The page does not show the loop. It shows a still of a deal and a link to apply. A collector already hunting grails will get it. A stranger sees another TCG promo card. Two problems. The watch is invisible. The product is not “Umbreon is cheap.” The product is ChaseCard catching it across shops while you sleep. That is motion. A price still is what eBay already posts. Motion is the alert hitting, the listing opening, the card matching the chase. The feed is one template. Photo. Percent. Link. Fine for proof. Weak as a brand. A ChaseCard frame should be the chase itself. Card. Target price. Hit. Same rails every alert. Then the beta link has a face. They already have the deals. The page should look like the watcher, not like the listing. See you on the next one.

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  marqix ☆ (@fwmarqix) reported 60 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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  Dustin Winter (@bluemagephoto) reported 1 hour ago

  @TucsonToucan @SaffronOlive I have seen worse out of WotC. I remember War of the Spark: Mythic Edition on eBay and ordering 2 of them. WotC had 12k units and a "glitch" caused over 40k to be sold. I ended up with an uncut M/R foil sheet as my order was canceled. After that WotC started Secret Lair.