Data Requests.

**Title: Request for Real US ChatGPT Conversation Data – Mortgages and/or iGaming** WLDM is looking to acquire licensed datasets containing real, historical AI chatbot conversations from US-based users, specifically covering two categories: 1. **Mortgages:** Mortgage rates, lenders, refinancing, home loans, mortgage comparisons, and related financial questions. 2. **iGaming / Online Casinos:** Casino recommendations, platform comparisons, bonuses, licensing, gambling regulations by US state, and related questions. **Providers may offer datasets for either category individually or both categories together.** We are open to purchasing one category or a combined dataset, depending on availability, quality, and pricing. ### Data requirements - Genuine user conversations, preferably from OpenAI's official ChatGPT platform. - US-based users and English-language conversations. - Full multi-turn conversations, including original user prompts, AI responses, and follow-up messages. - Original historical responses, not regenerated answers or synthetic conversations. - Conversation timestamps, session IDs, AI platform and model identifiers. - Citations, source URLs, and background web searches where available. - Clear provenance, lawful collection practices, and documented user consent. ### Volume and delivery We are initially interested in several thousand conversations, with the possibility of larger volumes or ongoing deliveries. Preferred formats: CSV, JSONL, or Parquet, with secure file delivery or S3 transfer where available. ### Licensing requirements The licence should permit commercial research, publication of aggregated findings and appropriately anonymized excerpts, conference presentations, client deliverables, and retention of derived research results. ### Information requested from providers Please include: - Which categories you can supply: mortgages, iGaming, or both. - Number of qualifying US conversations available per category. - Original AI platform and exact model used, particularly whether conversations originated directly from ChatGPT or third-party applications using GPT models. - Collection date ranges and available metadata. - A representative sample and data dictionary. - Pricing for one-time purchases and ongoing access, including any minimum order requirements. - Applicable licensing terms and restrictions. We welcome proposals from direct data providers, authorized resellers, and data brokers capable of sourcing these datasets.

Seeking 10,000 entirely synthetic retail transaction records for testing a sales analytics dashboard. Include fictional product IDs, product categories, transaction dates, quantities, unit prices, and store regions in CSV format. All records must be artificially generated, with no real people, businesses, payment details, or contact information. Sellers should describe the generation method and usage rights.

Seeking a fully synthetic retail sales dataset for testing a demand-forecasting demo. Need 12 months of daily transactions across 20 fictional stores and 100 fictional products, with date, synthetic store ID, synthetic product ID, units sold, unit price, discount, and stock availability. CSV preferred. All records must be generated, with no real people, businesses, customer identifiers, or contact details. Please describe the generation method and permitted usage.

I need a fully synthetic retail transactions dataset to test a sales analytics dashboard. Please provide 10,000 fictional transactions with transaction date, fictional product ID, product category, quantity, unit price in USD, discount, and fictional store ID. CSV format is preferred. Include a field dictionary and document how the synthetic records were generated. Do not include real people, real customer records, contact details, or confidential business information. The data must be licensed for testing and demonstration.

I need a fully synthetic retail sales dataset for testing a demand forecasting demo. Please provide 12 months of fictional daily transactions across 10 fictional stores and 50 fictional products, including date, store ID, product ID, units sold, unit price, discount, and inventory level. CSV or Parquet is preferred. All records must be artificially generated, with no real people, businesses, contact details, or confidential source data. Please explain the generation method and provide permission to use the synthetic dataset in a demo.

Seeking a fully synthetic retail transactions dataset for testing a sales analytics prototype. Include 10,000 fictional transactions with transaction date, fictional product category, quantity, unit price, discount, and fictional store region. Prefer CSV or JSON. Do not include real people, real businesses, personal information, or contact details. All records must be artificially generated and clearly labeled synthetic. Sellers should describe the generation method and permitted uses.

I need a fully synthetic retail transactions dataset to test a sales analytics demo. Please provide 1,000 fictional transactions with transaction date, fictional product ID, product category, quantity, unit price in USD, and fictional store ID. Include a short field dictionary and generation method. All records must be artificially generated; do not include real people, real customer identifiers, contact details, or actual business transactions. This request is for synthetic demo data only.

I need a fully synthetic retail transactions dataset for testing a sales analytics dashboard. Please provide 10,000 fictional transactions with transaction date, fictional product ID, product category, quantity, unit price in USD, and a fictional store ID. CSV is preferred. Include a field dictionary and explain how the synthetic records were generated. Do not include real people, real customer records, contact details, or confidential business data.

I need a fully synthetic retail sales dataset for testing a demand forecasting demo. Please provide 12 months of fictional daily sales across 10 fictional stores and 50 fictional products, with date, store ID, product ID, units sold, unit price, and promotion flag. CSV is preferred. All records must be artificially generated, contain no real people or business records, and be licensed for demo use. Please explain the generation method and any limitations.