Food & Beverage

Alliant Food and Beverage 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 of the associated brand, cuisine and products.

Samples/Tables Included:
-Food and Grocery Delivery Services
-F&B Brands
-Cuisine Preferences

Sample Fields Included:
- Peapod Buyer Propensity
- Blue Apron Buyer Propensity
- DoorDash Buyer Propensity
- naturebox.com Buyer Propensity
- Nespresso Buyer Propensity
- Omaha Steaks Buyer Propensity
- Postmates Buyer Propensity
- Coffee
- Mexican Cuisine
- Cooking and Food Enthusiasts

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

该数据集整合了品牌电商和Twitter数据与线下消费交易数据库，通过预测建模分析家庭对特定品牌、美食和产品的偏好。数据涵盖食品配送服务、品牌倾向和烹饪兴趣等多个类别，用于识别具有相似特征的潜在消费者群体。