Health & Beauty

Alliant Health & Beauty audiences are sourced from brand-specific e-commerce and Twitter data; that is then used as a study group and then joined to an offline cooperative database of direct-to-consumer purchase transactions, demographics, and lifestyle information. The analysis of the combined data is used for predictive modeling to identify other households in the cooperative that have shared characteristics predicting interest and of the associated brand and products.

Samples/Tables Included:
-Cosmetics
-Shaving
-Supplements
-Skincare
-Fitness and Weight loss
-Shower/Bath

Sample Fields Included:
- 1-800-Contacts Buyer Propensity
- Body Wash
- Bodybuilding.com Buyer Propensity
- Lipstick
- M.A.C Buyer Propensity
- Moisturizer
- Jewelry and Accessories
- The Honest Company Buyer Propensity
- ULTA Buyer Propensity
- Weight Loss

Expected Workflow
- Navigate to the Alliant Marketplace tile and click “Request”
- An Alliant representative will reach out
- Provide business requirements and/or create table query
- Upload data to Snowflake data share (if applicable)
- Alliant will return requested data

搜集汇总

背景与挑战

背景概述

该数据集通过整合品牌电商和Twitter数据与离线消费者交易数据库，用于预测建模以识别具有相似特征的家庭对健康美容产品的兴趣。它涵盖化妆品、护肤品、补充剂等多个类别，并包含购买倾向和具体产品字段，如唇膏和保湿霜。使用流程涉及从Alliant Marketplace请求数据，与代表沟通需求，并通过Snowflake数据共享获取结果。