Boosted Commerce
Learn how Boosted Commerce quickly evolved into one of the world’s largest brand aggregators by automating and optimizing all data integration processes powered by Pipes Professional
Boosted Commerce
Learn how Boosted Commerce quickly evolved into one of the world’s largest brand aggregators by automating and optimizing all data integration processes powered by Pipes Professional
About Boosted Commerce
Boosted Commerce specializes in the acquisition, development, and scaling of e-commerce brands, with a primary focus on Amazon FBA businesses and Shopify. Established with the vision to create a diverse portfolio of profitable and sustainable e-commerce brands, Boosted Commerce employs data-driven strategies and industry expertise to identify promising businesses that offer unique products and have substantial growth potential.
To ensure sustainable growth and success of the acquired brands in the competitive e-commerce market, Boosted Commerce relies on accurate data for:
- Efficient and cost-optimized inventory management in their own warehouses and in Amazon Fulfillment Centers
- Performance analysis of marketing measures such as Amazon Ads, Google Ads, and influencer campaigns
- Monitoring sales trends and customer behavior for each point of sale and product individually
Challenges
- Establish API connections:
Resource-intensive development and maintenance of API connections were required to obtain accurate data quickly and reliably from Amazon, Shopify, Facebook, and Google Ads APIs.
- Availability of reliable data:
Manual processes involved in establishing a single source of data truth were error-prone and time-consuming, making it a challenge to keep data updated and ready for analysis in Tableau.
- Optimize inventory levels:
Need to efficiently maintain inventory levels in Amazon Fulfillment Centers and in-house warehouses to minimize costs and prevent stockouts.
- Analyzing marketing performance:
Allocating orders to marketing campaigns based on causation demanded continuous and laborious manual consolidation and preparation of all marketing data
- Integration of new brands:
Integrating order, transaction, customer, and advertising data of newly acquired brands and launched products into the existing data model was time-consuming.
Actions
- Using Pipes' API connectors:
Effortlessly connected to the desired APIs through Pipes' API connectors for Amazon, Shopify, Facebook, and Google Ads, using only the respective account credentials.
- Setting up regular data updates:
Implemented automatic data updates for all brands and products across every point-of-sale, integrating them into their central data warehouse: Snowflake.
- Establishing inventory monitoring:
Developed monitoring dashboards in Tableau showcasing all Amazon FBA data, including stock levels and inventory fees.
- Automation of all marketing data:
Established a centralized database for all Instagram influencer and advertising campaign performance data in order to always have them available for cross-channel analyses.
- Creating re-usable SQL procedures:
Automated data integration from newly acquired brands, and launched products by creating re-usable SQL procedures using a standard formula to create a main wrapper procedure that creates scripts and job descriptions tailored to each individual data source, brand name, product, etc.
Results
- Relieved from API concerns:
Outsourced development and maintenance of API connectors, freeing up valuable time for data analysis and other essential tasks.
- Single source of data truth:
Achieved automated data synchronization across all brands, points-of-sale, products, and marketing campaigns, with operational integrity monitored via Slack notifications.
- Lean inventory management:
Enhanced inventory management practices, optimizing stock levels and reducing inventory-related costs at the product level.
- Data-driven marketing campaigns:
Gained an overview of the causation-based allocation of orders and revenue to Instagram influencer and advertising campaigns enables continuous data-driven optimization.
- Time savings through automation:
Automated SQL scripts reduce the time to set up all necessary data replication jobs for newly acquired brands and released products from 1.5 hours to 10 minutes. Automated data replication saves all the time spent on manual data retrieval, transformation and merging and frees up resources to work with this data.
