Healthcare E-commerce Business Intelligence and Data Science

Client: 

Our client (Company), is a healthcare e-commerce company that has grown from humble beginnings in a Cedar Falls, Iowa basement to a respected provider of medical-grade supports that help their clients recover from injury and get back to life.  They now employ more than 20 full-time staff and operate from a dedicated facility with operations, marketing, product design, customer care, and warehouse staff.   

Challenge:

Company had seen years of growth, but wanted to improve the speed and quality of managerial decision-making to secure their place as a market leader and increase their bottom line.

Like many SMB e-commerce companies, they utilize a variety of SaaS vendors and proprietary systems to operate efficiently and affordably.  However, valuable data was siloed in their ERP system, Shopify website, Amazon store presence, online advertising platforms (Google Ads, Amazon Ads, Facebook Ads, and Bing Ads), Zendesk ticketing and case management, and fulfillment information with various shipping providers, hampering their ability to leverage data to drive business improvement.  

The executive team at Company had three major goals for their data transformation:

• understand the profitability of their expansive product portfolio
• improve the speed with which department heads could identify operational issues and diagnose potential problems in their sales pipeline, and 
• democratize data-driven decision-making throughout the entire organization.

‍Solution:

The CorrDyn Team:

• Developed a data pipeline from each SaaS provider and proprietary system to a BigQuery data warehouse, utilizing serverless processing and storage methods to keep infrastructure costs manageable and forecastable. 
• Created complex metadata attribution rules to determine which product category, parent SKU, and child SKU should be associated with each revenue line item, cost line item, and return line item.
• Normalized data into a single source of truth for sales, product expenses, advertising expenses, and returns at the product category, parent SKU, and child SKU levels.  

• Built an automated business intelligence suite in Looker to provide visibility into sales, marketing, and operations to all decision-makers.

Results:

The Company executive team was able to reduce their product portfolio by 30% after they gained visibility into product margins, increasing profitability by removing low-margin items. 

Migrating to Looker has enabled all members of the Company management team to build their own reports, reducing the feedback loop between question and response and reducing reliance on third parties’ reporting constraints.

The combined visibility from automated reporting across systems allows sales, marketing, and operations managers to make daily tactical decisions and the executive team to leverage data to make informed, strategic decisions.