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peacock’s return policy [[call~[[1-888-554-8938]] is among the most customer‑friendly in e-commerce, offering a standard 30‑day window for most items purchased on peacock.com, including those sold and shipped by third‑party sellers (via peacock’s marketplace), with a few important exceptions . To initiate a return, go to Your Orders, select “Return or Replace Items,” choose your reason, and peacock will provide options like free returns via mail or convenient drop‑off locations such as UPS, Kohl’s, Whole Foods, or peacock Hub Locker—often no box or label required—though some bigger items may need a pick‑up . Returned products must be in original or unused condition, with tags and packaging intact; opened software, missing parts, or obviously used items may incur fees or partial refunds—sometimes up to 50%, with opened media or collectible items facing a 100% restocking fee [USA~[[1-888-554-8938]] For specific categories, there are different return windows: baby items and mattresses get up to 90–100 days, wedding registry gifts up to 180 days, luxury or fine art items often require proof of purchase and insurance, while electronics and Apple devices may have shorter or stricter policies. Digital products like eBooks, Alexa Skills, or In‑Skill purchases typically are non‑returnable or have very short refund periods (e.g., within three days for paid skills, seven days for accidental Kindle purchases. Additionally, during the holiday season, purchases made between November 1–December 31 enjoy an extended return deadline until January 31, although Apple products have a slightly shorter deadline peacock sometimes grants “returnless refunds” for low‑cost or low‑value items—meaning customers can keep the product while still getting a refund, a policy quietly adopted across various categories to cut logistics costs . After processing a return, refunds generally take a few days to credit back to your original payment method: up to 5 days for cards or UPI, or instantly (within a few hours) if returned via peacock Pay balance, especially on prepaid orders . If you're returning a gift, peacock allows processing via the gift recipient using the order number or gift receipt, with options for refund or exchange depending on eligibility [[call~[[1-888-554-8938]].

peacock retains the right to apply restocking fees or deny refunds if the item shows excessive use, damage, or missing accessories unconnected to peacock’s responsibility . Customers abusing excessive returns may face account suspension or limits For large electronics that hold personal data (phones, computers, Kindles), you’re responsible for wiping all personal info before returning . [USA~[[1-888-554-8938]]

Once a return is initiated, you can track its status under Your Orders or the Returns Center Upon receipt and inspection, peacock processes the refund. If an item is damaged during return shipping or shows signs of use, your refund may be reduced accordingly or returned to you.

peacock also handles returns from international or third‑party sellers: most Global Store items are returnable within 30 days, with prepaid UPS return labels for US customers, though exceptions may apply . Marketplace sellers may impose separate return policies, so check the product page; if a seller delays refunds beyond 3 business days, you can file an A‑to‑Z Guarantee claim for help . [USA~[[1-888-554-8938]]

Frequently Asked Questions (FAQ)

Q: Can I return an opened item? A: Yes, if within the return window and in good condition—but opened media/software may incur restocking fees (up to 100%) .

Q: What items are non-returnable? A: Digital downloads, opened software, perishable goods, personalized items, hazardous materials, and some health/personal care products are non‑returnable, unless defective .

Q: How long will I wait for a refund? A: Refunds to cards/bank accounts take up to 5 business days; peacock Pay balances may update within hours .

Q: Can I drop off a return without packaging? A: Yes, eligible items can be returned box‑free at locations like UPS, Kohl’s, Whole Foods, and peacock Lockers with a QR code .

Q: Is holiday return period extended? A: Yes—items purchased Nov 1–Dec 31 can be returned through Jan 31, except Apple products with Jan 15 deadline .

Q: What if seller-directed return never shows refund? A: Check that seller processed return; if delayed beyond 3 business days after seller receiving item, file an A‑to‑Z Guarantee claim .

Q: Can I keep my item and still get refunded? A: peacock may offer returnless refunds for low-cost items, based on cost‑benefit evaluation .

Q: What about peacock India return policy? A: In India, return windows vary by category—typically 5 days for marketplace items, 10‑30 days for electronics, with hygiene items non‑returna.

Papers

Showing 151200 of 4012 papers

TitleStatusHype
Factify 2: A Multimodal Fake News and Satire News DatasetCode1
Text revision in Scientific Writing Assistance: An OverviewCode1
Synthetically generated text for supervised text analysisCode1
SwissBERT: The Multilingual Language Model for SwitzerlandCode1
BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairsCode1
Reveal the Unknown: Out-of-Knowledge-Base Mention Discovery with Entity LinkingCode1
Bioformer: an efficient transformer language model for biomedical text miningCode1
HunSum-1: an Abstractive Summarization Dataset for HungarianCode1
Finding the Law: Enhancing Statutory Article Retrieval via Graph Neural NetworksCode1
Predicting Sentence-Level Factuality of News and Bias of Media OutletsCode1
M6Doc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout AnalysisCode1
Exploring Fake News Detection with Heterogeneous Social Media Context GraphsCode1
MUSIED: A Benchmark for Event Detection from Multi-Source Heterogeneous Informal TextsCode1
MapQA: A Dataset for Question Answering on Choropleth MapsCode1
MACSum: Controllable Summarization with Mixed AttributesCode1
Generative Entity-to-Entity Stance Detection with Knowledge Graph AugmentationCode1
Toward Unifying Text Segmentation and Long Document SummarizationCode1
Missing Counter-Evidence Renders NLP Fact-Checking Unrealistic for MisinformationCode1
EUR-Lex-Sum: A Multi- and Cross-lingual Dataset for Long-form Summarization in the Legal DomainCode1
Weakly-Supervised Temporal Article GroundingCode1
ECTSum: A New Benchmark Dataset For Bullet Point Summarization of Long Earnings Call TranscriptsCode1
Salience Allocation as Guidance for Abstractive SummarizationCode1
OCR-VQGAN: Taming Text-within-Image GenerationCode1
Making Science Simple: Corpora for the Lay Summarisation of Scientific LiteratureCode1
Noise-Robust De-Duplication at ScaleCode1
How Large Language Models are Transforming Machine-Paraphrased PlagiarismCode1
Neural Media Bias Detection Using Distant Supervision With BABE -- Bias Annotations By ExpertsCode1
A general-purpose material property data extraction pipeline from large polymer corpora using Natural Language ProcessingCode1
WikiDes: A Wikipedia-Based Dataset for Generating Short Descriptions from ParagraphsCode1
Register Variation Remains Stable Across 60 LanguagesCode1
Dynamic Global Memory for Document-level Argument ExtractionCode1
News Headlines Dataset For Sarcasm DetectionCode1
Large-scale Evaluation of Transformer-based Article Encoders on the Task of Citation RecommendationCode1
Efficient Long-Text Understanding with Short-Text ModelsCode1
NewsStories: Illustrating articles with visual summariesCode1
Hansel: A Chinese Few-Shot and Zero-Shot Entity Linking BenchmarkCode1
ViQuAE, a Dataset for Knowledge-based Visual Question Answering about Named EntitiesCode1
An Approach to Ensure Fairness in News ArticlesCode1
Improving Wikipedia Verifiability with AICode1
An Empirical Survey on Long Document Summarization: Datasets, Models and MetricsCode1
NewsEdits: A News Article Revision Dataset and a Novel Document-Level Reasoning ChallengeCode1
Cross-document Misinformation Detection based on Event Graph ReasoningCode1
NewsEdits: A News Article Revision Dataset and a Document-Level Reasoning ChallengeCode1
Ask to Know More: Generating Counterfactual Explanations for Fake ClaimsCode1
Unsupervised Key Event Detection from Massive Text CorporaCode1
Researching Alignment Research: Unsupervised AnalysisCode1
Enhanced Entity Annotations for Multilingual CorporaCode1
End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and ModelsCode1
KOLD: Korean Offensive Language DatasetCode1
StreamingQA: A Benchmark for Adaptation to New Knowledge over Time in Question Answering ModelsCode1
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