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Parachute Home's Success with NetSuite Data Centralization
Technology Category
- Application Infrastructure & Middleware - Data Exchange & Integration
- Functional Applications - Enterprise Resource Planning Systems (ERP)
Applicable Industries
- Apparel
- E-Commerce
Applicable Functions
- Maintenance
- Procurement
Use Cases
- Last Mile Delivery
- Time Sensitive Networking
Services
- System Integration
- Testing & Certification
The Challenge
Parachute Home, a U.S.-based direct-to-consumer brand selling home essentials, was struggling to manage data from its two core systems, Shopify and NetSuite’s cloud ERP software. Shopify powered Parachute’s ecommerce platform and transactional process, while NetSuite triggered the fulfillment process. However, these systems were running in a siloed manner, making the data from both sides increasingly hard to manage. Parachute was using custom-built data loaders to connect into Shopify and NetSuite, but the results were inconsistent. There were data quality problems that resyncing rarely solved, and the absence of logs made it hard to identify issues. The time-consuming data ingestion process was hindering the brand's digital ambitions.
About The Customer
Parachute Home is a direct-to-consumer brand based in the U.S. that sells home essentials such as bedding, bath linens, decor, furniture, and more. The brand has found success by offering exceptional affordability, quality, and innovation. To compete with bigger brands, Parachute needed to centralize data from its core systems, Shopify and NetSuite’s cloud ERP software, to improve customer retention and drive sales. The brand is digitally native and ambitious, aiming to stand up and test proof-of-concepts quickly.
The Solution
To simplify data integration and automate backend processes, Parachute implemented Fivetran’s cloud-native, pre-built connectors to Shopify and NetSuite. These connectors enabled the generation of business-critical insights, from orders per day to margins and profitability. Reports and forecasts were easily surfaced in Looker and shared with different business divisions. The data could be analyzed in multiple ways, aiding various teams in their functions. For instance, finance used it to match orders against forecasts, the product team tracked orders and sales, customer service troubleshooted delays in the fulfillment lifecycle, and merchandising teams analyzed the performance of newly launched products. Fivetran connectors were regularly updated as NetSuite and Shopify changed their APIs, ensuring constant syncing of critical fields.
Operational Impact
Quantitative Benefit
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