Automated Customer Segmentation for Email Campaigns in eCommerce
- Apparel
- Equipment & Machinery
- Procurement
- Time Sensitive Networking
Hugh & Crye, a men's fashion company, was facing a challenge in managing their customer data for email campaigns. They wanted to understand their customers better, specifically whether a customer was making their first purchase or a subsequent one. This information was crucial for their email marketing campaigns, which were designed differently for first-time buyers and returning customers. However, they lacked the bandwidth to manually track a customer's lifecycle, especially in relation to purchases. The process of exporting data, segmenting it, and preparing it for their email marketing in MailChimp was extremely manual and time-consuming.
Hugh & Crye is a men's fashion company that aims to bridge the gap between ill-fitted, mass-produced shirts and expensive, custom-tailored shirts. They strive to make dressing well accessible to their customers by offering fitting guides and blog posts about what makes a well-fitted shirt. The company was looking for a way to better understand their customers' purchasing habits in order to tailor their email marketing campaigns accordingly. They needed a solution that could automate the process of segmenting customers based on their purchase history and add them to the appropriate email campaign.
Hugh & Crye turned to Zapier, an app automator, to streamline their customer data management process. They used Zapier and its filters to automatically segment customers from Shopify and add them to the correct campaign in MailChimp. Whenever Hugh & Crye received a paid order in Shopify, Zapier would take the customer's order information and run it through a filter. This filter would look for specifics such as whether the customer already existed, the total orders from this customer, and any other information that would inform their email campaign. Then, Zapier would add the customer as a subscriber to a specific list in MailChimp. This process was repeated with different Zaps, each one segmenting a different type of customer into their own list.