CorrDyn connects your Shopify, Amazon, subscription, and marketing data into dashboards that show exactly which products, channels, and campaigns make money.
80%
ELT cost reduction for a subscription brand
30%
Product portfolio reduction from SKU-level profitability
5+
E-commerce and DTC clients served
The data problems we solve in e-commerce and direct-to-consumer are specific, recurring, and well-understood from years of delivery.
Shopify, Amazon Seller Central, Recharge subscriptions, and ERP systems each have their own version of revenue. Reconciling them takes days of manual work every month.
Google Ads, Meta, Amazon PPC, and affiliate programs all report ROAS differently. You cannot connect a dollar of spend to a dollar of gross margin at the product level.
Connector bills grow with row counts. Warehouse credits burn faster than expected. The data stack costs more than the insights it produces.
Looker Studio shows one number, the ERP shows another, and Amazon Seller Central shows a third. Nobody agrees on last month revenue.
How CorrDyn works with e-commerce and direct-to-consumer companies.
E-commerce and DTC brands generate data across more platforms than almost any other industry. Shopify for storefront sales. Amazon for marketplace revenue. Recharge or Bold for subscriptions. Google, Meta, and Amazon for advertising. An ERP for financials. A 3PL for fulfillment.
Each platform reports its own version of reality. Reconciling revenue across channels, connecting marketing spend to product-level profitability, and building a single view of customer behavior requires data infrastructure that most e-commerce companies do not have.
Unified multi-channel analytics. For a subscription nutrition brand, we built ongoing Data Team as a Service covering Shopify, Amazon, Recharge, and Northbeam integrations. Executive dashboards replaced a patchwork of Looker Studio reports and manual data pulls.
SKU-level profitability analysis. For a medical device e-commerce company, we connected marketing spend, conversion, and revenue data across ERP, CRM, Google Ads, Bing, Amazon, and Facebook to report profitability at the product SKU level. The product team used the data to cut their portfolio by a third, eliminating spend on products that lost money.
ELT cost optimization. For a subscription apparel brand, high row-count connector utilization was driving variable and rising costs. We migrated to lower-cost connectors, reducing ELT costs by 80% with a parallel validation approach before cutover.
Platform migrations. For a specialty coffee chain, we migrated off a legacy warehouse, refactoring transformation models and reconfiguring analytics integrations. The result was lower cost, less infrastructure complexity, and faster query performance.
We know the e-commerce data stack because we work in it every day. Storefront webhook schemas, marketplace API quirks, subscription event models, attribution platform windows. This is not theoretical knowledge from documentation. It is production experience across 5+ clients spanning nutrition, apparel, medical devices, agriculture, and specialty coffee. For a look at where retail data strategy is headed, listen to our episode on [agentic commerce and the data infrastructure it demands](/podcasts/eventual-consistency/ep-18-agentic-commerce-retail-data).
Real outcomes from our e-commerce and direct-to-consumer engagements.
CorrDyn migrated a coffee chain from Redshift to MotherDuck with dbt refactoring and a code-first BI layer, reducing costs and complexity.
Redshift to MotherDuckwarehouse platform
Eliminated cluster provisioning and managementinfrastructure overhead
CorrDyn migrated an e-commerce company from Fivetran to Estuary for Shopify and GA4 data, cutting ELT costs by 80%.
80%elt cost reduction
Shopify + GA4connectors migrated
CorrDyn built a unified analytics platform across Shopify, Amazon, and subscription channels, migrating BI to PowerBI and reducing ELT costs.
Shopify + Amazon + subscriptionssales channels unified
Migrated from Looker Studio to PowerBIbi platform
CorrDyn extracted data from a legacy 1990s system and implemented NetSuite for a major agricultural e-commerce retailer, cutting costs by 25%.
25%cost savings
Hours instead of daysfinancial reporting
Perspectives on data strategy for e-commerce and direct-to-consumer.
A bottom-up approach to event-based marketing using data integration, customer behavior analysis, and automation to optimize marketing spend.
117 questions e-commerce leaders should answer across finance, marketing, sales, operations, support, technology, and BI — prioritized by business impact.
A practical guide to calculating Customer Acquisition Cost and Lifetime Value, and using the CAC:LTV ratio to manage growth and profitability.
The capabilities we bring to e-commerce and direct-to-consumer engagements.
Build reliable, cost-effective data pipelines on AWS, GCP, and Azure. CorrDyn designs and implements data infrastructure that scales.
Turn data into decisions with BI platforms that your team will use. CorrDyn builds dashboards, reports, and analytics workflows.
Connect marketing spend to revenue. CorrDyn builds attribution models, customer segmentation, marketing mix models, and ROI reporting across channels.
Optimize data platform performance to reduce Snowflake, Fivetran, and Databricks spend by 40-80%. Faster queries, right-sized compute, lower bills.
Get a full data team without the hiring timeline. CorrDyn embeds the specific skill sets you need and owns outcomes, not just hours.
Unify your CRM, billing, and pipeline data into a single revenue model. CorrDyn builds the data infrastructure that makes RevOps work.
Tools we use in e-commerce and direct-to-consumer engagements.
AWS
GCP
Azure
Snowflake
BigQuery
Databricks
MotherDuck
DuckDB
Redshift
Estuary
Dagster
Fivetran
Airflow
Prefect
dbt
dlt
SQLMesh
Spark
Tableau
Looker
Power BI
Omni
Superset
Evidence
Rill Data
GrafanaTell us about your challenges. We will be honest about whether we can help.
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