Transforming Data Management for Enhanced Marketing Insights: A Case Study on Carter's
Technology Category
- Analytics & Modeling - Predictive Analytics
- Wearables - Smart Clothing
Applicable Industries
- Consumer Goods
- Retail
Applicable Functions
- Sales & Marketing
Use Cases
- Retail Store Automation
- Theft Detection
About The Customer
Carter’s, Inc., established in 1865, is the largest U.S. branded marketer of baby and children’s clothing. The company's products, including Carter’s and OshKosh B’gosh, are sold at over 600 company-owned retail stores, as well as thousands of national department stores and retailers. As a leading brand of children’s clothing, gifts, and accessories in America, Carter’s is committed to understanding customer engagement with their marketing campaigns and optimizing their strategies based on data-driven insights.
The Challenge
Carter’s, a leading children’s clothing brand in America, was facing a significant challenge in managing and analyzing vast amounts of performance marketing data from various sources, including Google SA 360 and Facebook. The team was overwhelmed with the manual task of collecting data using spreadsheets, a process that was not only laborious but also considered low-value. The need for a more efficient approach to manage and process data was evident, as the team sought to understand customer interactions with their campaigns and improve future performance. The goal was to examine specific data points to gain insights into potential and existing customers' behavior.
The Solution
To overcome the challenge, Carter’s turned to Adverity, a platform that automated and upgraded their data ingestion process. This solution allowed the team to analyze and establish reporting almost in real-time, freeing them from the daily grind of data management. The automation provided by Adverity unveiled more accurate data, enabling Carter’s to deepen customer segmentation and journey mapping. The platform also facilitated greater data accessibility across the organization, allowing the senior team to interact with and customize the data according to their specific needs. This sophisticated tool empowered different teams to perform their jobs more effectively, leading to faster and more productive insights.
Operational Impact
Quantitative Benefit
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