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Consumer Trend Insights: Real-Time Conversations & Interests by Age and Context (8-19)

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Datarade2024-07-22 收录
下载链接:
https://datarade.ai/data-products/consumer-trend-insights-real-time-conversations-interests-alerteenz
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资源简介:
Designed to empower companies and marketers, this dataset offers a window into the minds of young consumers, helping to identify hot topics, refine product development, and tailor marketing campaigns to resonate with specific demographics. The dataset's robust methodology, combining cutting-edge technology with human expertise, ensures a high level of accuracy and actionable insights. Whether you're looking to understand the latest slang, track brand sentiment, or identify the next big thing, this dataset is your essential tool for staying ahead of the curve. Age Groups: 8-12, 13-15, 16-19 Subject & Category: Granular breakdown of discussion topics (e.g., "Nike shoes," "want to buy shoes," "friends wishlist") Context: When and how discussions happen (driving, walking, stationary) Platform: Apps where conversations occur (TikTok, WhatsApp, YouTube, etc.) Enhanced Insights: Leverages semantic analysis, entity extraction, and LLM-powered context understanding for deeper analysis Ideal for: Market research teams, product developers, advertisers, and anyone interested in understanding the youth market. This comprehensive dataset, accessible via a RESTful API with JSON response format, provides a granular analysis of real-time youth conversations (ages 8-19). Leveraging advanced semantic analysis, entity extraction, and LLM insights, the dataset uncovers emerging trends, brand preferences, and unmet needs across multiple digital platforms. The API supports monthly data requests, enabling users to track trends over time and identify shifts in consumer behavior. Each JSON response includes detailed breakdowns of conversation topics, associated entities, app usage patterns, and user activity levels.
提供机构:
Alerteenz
搜集汇总
数据集介绍
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背景与挑战
背景概述
该数据集通过RESTful API提供JSON格式数据,专注于分析8-19岁年轻消费者的实时对话和兴趣,涵盖年龄分组、话题分类、平台使用等维度。它结合语义分析和LLM技术,帮助市场研究人员和产品开发者识别趋势、优化营销策略,并支持月度数据请求以追踪行为变化。
以上内容由遇见数据集搜集并总结生成
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