[SAMPLE] Consumer Edge Web Scraping Data | Roblox (RBLX) & Entertainment | SKU-Level Purchase ...
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https://marketplace.databricks.com/details/16bc35ec-7122-4b2e-ba09-c66715b90966/Consumer-Edge_SAMPLE-Consumer-Edge-Web-Scraping-Data-Roblox-(RBLX)-&-Entertainment-SKU-Level-Purchase-
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资源简介:
Consumer Edge is a leader in alternative consumer data for public and private investors and corporate clients. Web includes web scraping purchase data for companies like Roblox (RBLX) and the entertainment industry of over 350M consumer transactions from 11K brands and 190 countries. With over 11 years of history, KPIs tracked include parent company, website, items sold, value of items sold, inventory, and purchase data.
Tickers tracked include:
• BKNG
• CARG
• CARS
• CPRT
• CVNA
• ETSY
• IAA
• KMX
• LAD
• OPAD
• OPEN
• POSH
• PTON
• PZZA
• RBLX
• SAH
• SPOT
• TRIP
Consumer Edge’s web scraping purchase data offers insights into sectors such as:
• Automotive
• Real Estate
• Marketplaces
• Lodging
• Entertainment
Public and private investors can leverage insights from CE’s synthetic data to forecast quarterly earnings with more precision, leverage inventory as a leading indicator of future sales, combine with other datasets like transaction data for more holistic analysis, and explore product trends by brand, industry, category, and more with granular SKU-level data.
Consumer Edge是面向公募投资者、私募投资者及企业客户的另类消费者数据领域领军企业。其网页数据集包含针对罗布乐思(Roblox,股票代码RBLX)等企业,以及娱乐行业的网页抓取采购数据,相关交易累计超3.5亿条,覆盖1.1万个品牌与190个国家/地区。该数据集拥有超11年的历史沉淀,所追踪的关键绩效指标(KPI,Key Performance Indicator)包括母公司信息、企业官网、在售商品、商品销售额、库存状况及采购数据。
所追踪的股票代码包括:
• BKNG
• CARG
• CARS
• CPRT
• CVNA
• ETSY
• IAA
• KMX
• LAD
• OPAD
• OPEN
• POSH
• PTON
• PZZA
• RBLX
• SAH
• SPOT
• TRIP
Consumer Edge的网页抓取采购数据集可提供多行业洞察,覆盖领域包括:
• 汽车
• 房地产
• 电商市场
• 住宿
• 娱乐
公募与私募投资者可借助Consumer Edge生成的合成数据洞察,实现更精准的季度收益预测,将库存作为未来销售额的先行指标,结合交易数据等其他数据集开展更全面的整合分析,并通过细粒度的库存单位(SKU,Stock Keeping Unit)级数据,按品牌、行业、品类等维度探究产品趋势。
提供机构:
Consumer Edge搜集汇总
数据集介绍

背景与挑战
背景概述
该数据集提供Roblox等娱乐行业公司的网络爬取消费数据,覆盖11年历史、350M交易记录及11K品牌,包含SKU级别购买信息。投资者可利用其精准预测收益、分析库存趋势,并与其他数据集结合进行综合研究。
以上内容由遇见数据集搜集并总结生成



