Hello, everyone, we repurposed data from an old project into a Kaggle dataset\u2b07\ufe0f Happy to hear your thoughts and feedback<\/p>\n
What this is about:
Major US retailers run hundreds of promotions daily – but there’s no clean, structured source to track them over time. I built a pipeline that scrapes 5 major e-commerce sites daily and extracts every promo, coupon code, and deal into a structured format using GPT-4o-mini and Llama.<\/p>\n
Covers Office Depot, Ulta, Home Depot, 1800Flowers, and Shutterfly (for now) – with discount type, value, expiration date, and source URL for every record.<\/p>\n
A few things the data shows right now:<\/p>\n
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- Office Depot dominates volume: 73 promos today vs 10 for Home Depot<\/li>\n
- Ulta and 1800Flowers both hit 50% as their max discount: beauty and flowers are aggressive<\/li>\n
- Only 4% of promos have coupon codes: most discounts are applied automatically at checkout<\/li>\n
- Home Depot ran 228 promos on April 8th: likely a flash sale event worth investigating<\/li>\n<\/ul>\n
You can find it here: https:\/\/www.kaggle.com\/datasets\/indext-data-lab-ai\/promos-dataset<\/a><\/p>\n
4,955+ records collected over 37 days and counting. Next update tomorrow morning<\/p>\n<\/div>\n
submitted by \/u\/KaiseyTayl <\/a>
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