Fivetran > Case Studies > PopSockets Enhances Profitability and AOV by 25% with Fivetran

PopSockets Enhances Profitability and AOV by 25% with Fivetran

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Technology Category
  • Functional Applications - Enterprise Resource Planning Systems (ERP)
  • Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
  • Consumer Goods
  • Retail
Applicable Functions
  • Maintenance
  • Sales & Marketing
Use Cases
  • Retail Store Automation
  • Supply Chain Visibility
Services
  • Cloud Planning, Design & Implementation Services
About The Customer
Founded in 2014, PopSockets has sold over 230 million of its iconic phone grips in 75 countries and now has an expanding ecosystem of related products, including phone cases, wallets, and mounts. The company, which has more than 250 employees, supports various departments, including Ecommerce, Marketing, Business Intelligence, Finance, Accounting, Supply Chain, and Operations. PopSockets uses various sources for its data, including Amazon Ads, Klaviyo, SQL Server, Google Ads, Bing Ads, MySql RDS, Google Analytics, Facebook Ads, Snapchat Ads, Pinterest Ads, and Shopify. The company's data is stored in the Snowflake Data Cloud and is hosted on the AWS Cloud Platform.
The Challenge
PopSockets, a retail and consumer goods company, was facing significant challenges with its data management and reporting processes. The company was struggling with reporting efficiencies and communicating insights across various departments, including Ecommerce, Marketing, Business Intelligence, Finance, Accounting, Supply Chain, and Operations. The lack of strict timelines for data refreshment and the tedious process of manually aggregating reports were hampering the company's growth. As PopSockets began to experience tremendous year-over-year growth and adopted an ERP system, the volume of data grew exponentially. The company was grappling with data silos, unscalable manual efforts to aggregate and store data in a single source of truth, and a lack of visibility into marketing data to understand the ROI of ad spend on various channels. PopSockets needed a scalable solution that would allow its small team of data engineers to build automated data pipelines for faster analytics and reporting.
The Solution
PopSockets adopted Fivetran, a modern data stack solution, to centralize its data and build models for deeper insights. Fivetran, coupled with Snowflake and PopSockets' BI tool, helped the company support and unify data from additional ERP systems as they scaled across the world. It also enabled the company to automate reports with reliable and up-to-date data and assess the performance of individual ad campaigns on different channels more effectively. Fivetran's solution was a key component in PopSockets' strategy to manage its explosive growth through various sales channels and increased paid marketing efforts. The solution allowed the company to centralize growing ERP data as it scaled worldwide, save hours of resources by eliminating the need to manually download reports from various platforms and aggregate them for analyses, and create leaderboards by SKU to show what products were contributing to not just sales and unit velocity, but also profitability.
Operational Impact
  • The implementation of Fivetran's solution led to significant operational improvements for PopSockets. The company was able to double its daily Return on Ad Spend (ROAS) and increase its Average Order Value (AOV) by 25%. By pulling in ERP data, PopSockets was able to create leaderboards by SKU to show what products were contributing to not just sales and unit velocity, but also profitability. The solution also saved the company hours of resources by eliminating the need to manually download reports from various platforms and aggregate them for analyses. Furthermore, Fivetran's solution allowed PopSockets to centralize its growing ERP data as it scaled worldwide. The company plans to further leverage Fivetran's solution to join ecommerce data and Klaviyo data to help segment customers and develop tailored marketing initiatives, create a holistic view of product performance on Amazon, and leverage a modern data stack to help with AI/ML by aggregating data to understand purchase behavior of different products in different regions.
Quantitative Benefit
  • 2x increase in daily profitability from ad spend
  • 25% increase in Average Order Value (AOV)
  • Saved at least 1 headcount by eliminating manual tasks of a traditional data engineering role

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