Czech Conversational Chat Dataset for Retail & E-commerce Domain

This text dataset consists of chats between two native Czech people on diverse topics, specifically tailored to the Retail & E-commerce domain.


Text-based conversational dataset

Total volume

10K+ chats

Last Updated

Jun 2024

Number of participants

150 people

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About This OTS Dataset

About Gradiet Line


The dataset comprises over 10,000 chat conversations, each focusing on specific Retail & E-Commerce related topics. Each conversation provides a detailed interaction between a call center agent and a customer, capturing real-life scenarios and language nuances.

  • Participants Details: 150+ native Czech participants from the FutureBeeAI community.
  • Word Count & Length: Chats are diverse, averaging 300 to 700 words and 50 to 150 turns across both speakers.
  • Topic Diversity

    The chat dataset covers a wide range of conversations on Retail & E-Commerce topics, ensuring that the dataset is comprehensive and relevant for training and fine-tuning models for various Retail & E-Commerce use cases. It offers diversity in terms of conversation topics, chat types, and outcomes, including both inbound and outbound chats with positive, neutral, and negative outcomes.

  • Inbound Chats:
  • Product Inquiry
  • Return/Exchange Request
  • Order Cancellation
  • Refund Request
  • Membership/Subscriptions Enquiry
  • Order Cancellations, and many more
  • Outbound Chats:
  • Order Confirmation
  • Cross-selling and Upselling
  • Account Updates
  • Loyalty Program Offers
  • Special Offers and Promotions
  • Customer Verification, and many more
  • Language Variety & Nuances

    The conversations in this dataset capture the diverse language styles and expressions prevalent in Czech Retail & E-Commerce interactions. This diversity ensures the dataset accurately represents the language used by Czech speakers in Retail & E-Commerce contexts.

    The dataset encompasses a wide array of language elements, including:

  • Naming Conventions: Chats include a variety of Czech personal and business names.
  • Localized Details: Real-world addresses, emails, phone numbers, and other contact information as according to different Czech-speaking regions.
  • Temporal and Numeric Expressions: Dates, times, currencies, and numbers in Czech forms, adhering to local conventions.
  • Idiomatic Expressions and Slang: It includes local slang, idioms, and informal phrase present in Czech Retail & E-Commerce conversations.
  • This linguistic authenticity ensures that the dataset equips researchers and developers with a comprehensive understanding of the intricate language patterns, cultural references, and communication styles inherent to Czech Retail & E-Commerce interactions.

    Conversational Flow and Interaction Types

    The dataset includes a broad range of conversations, from simple inquiries to detailed discussions, capturing the dynamic nature of Retail & E-Commerce customer-agent interactions.

  • Simple Inquiries
  • Detailed Discussions
  • Transactional Interactions
  • Problem-Solving Dialogues
  • Advisory Sessions
  • Routine Checks and Follow-Ups
  • Each of these conversations contains various aspects of conversation flow like:

  • Greetings
  • Authentication
  • Information gathering
  • Resolution identification
  • Solution Delivery
  • Closing and Follow-ups
  • Feedback, etc
  • This structured and varied conversational flow enables the creation of advanced NLP models that can effectively manage and respond to a wide range of customer service scenarios.

    Data Format and Structure

    The dataset is available in JSON, CSV, and TXT formats, with each conversation containing attributes like participant identifiers and chat messages, designed to be easily accessible and compatible with popular NLP frameworks.

    Usage and Application

    This dataset is useful for various applications in NLP and conversational AI, including:

  • Conversational AI Development: Building of Retail & E-Commerce-specific conversational AI models for automated customer service.
  • Natural Language Processing (NLP) Research: Advancement of Czech NLP research in sentiment analysis and language generation.
  • Smart Assistants and Chatbots: Development of smart assistants and chatbots for complex Retail & E-Commerce interactions.
  • Text Recognition and Analytics: Training algorithms for text recognition and analytics in Retail & E-Commerce document processing.
  • Text Prediction and Generation: Improvement of text prediction and generation models for customer-agent interactions.
  • Secure and Ethical Collection

  • The data collection process adhered to strict ethical guidelines, ensuring the privacy and consent of all participants.
  • It does not include any personally identifiable information of any participant, which makes the dataset safe to use.
  • Throughout the data collection process, the data remained within our secure platform and did not leave our environment, ensuring data security and confidentiality.
  • Updates and Customization

    The dataset is regularly updated with new chat data. Customization options are available to meet specific needs, including:

  • Customization & Custom Collection Options:
  • Annotation: Various types of annotations like Named Entity Recognition (NER), Sentiment Analysis, Intent Classification, or any other application-specific annotations can be made available upon request.
  • Different topics: Custom collection can be done on specific requirements in any language and domain.
  • Region-Specific Collection: Country or region-specific terminology can be added or custom collection can be done.
  • License

    This Czech Conversational Chat Dataset for Retail & E-Commerce is created by FutureBeeAI and is available for commercial use.

    Use Cases

    Use of conversational chat dataset in Chatbot


    Use of conversational chat dataset in Text Recognition

    Text Recognition

    Use of conversational chat dataset in Text Analytics

    Text Analysis

    Use of conversational chat dataset in Text Prediction

    Text Prediction

    Use of conversational chat dataset in Smart Assistant

    Smart Assistants

    Dataset Sample(s)

    Sample Line

    Samples will be available soon!

    Contact us to get the samples immediately for this dataset.

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    Dataset Details

    Details Headline

    Dataset type

    Retail & E-commerce Chats


    10K+ chats

    Media type






    File Details

    Details Headline

    Number of thread


    Word count

    300-700 words





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