Success Story | Data Engineering & BI
Flos USA turned a fragmented stack into affinity-driven sales
Custom Python ETL pulls 10+ sales and marketing platforms into one AWS database.
Cross-platform data is mapped and blended into one analytics-ready model.
Self-serve dashboards, affinity-based bundles, and funnel drop-off analysis.
Lower effort and cost to build and refresh reports
Higher combined sales on affinity-bundled products
Sales and marketing platforms unified in one dataset
Sales regions on one reporting model: USA & Europe
Turn a Fragmented Data Estate Into One Decision Layer
Flos USA, a luxury interior-lighting brand serving the USA and multiple European markets, had reached the limits of spreadsheet-led reporting. Its direct-to-consumer and retail operations generated valuable signals, but those signals could not be read together.
The mandate was clear: connect sales performance to marketing activity, remove the recurring work of rebuilding reports, and give category managers and executives a view they could explore without waiting for a custom data pull.
Rudder Analytics designed a unified analytics foundation on AWS, then paired it with self-serve Tableau dashboards and focused market-basket and funnel analysis—turning reporting infrastructure into a tool for commercial decisions.
Every Platform Told Only Part of the Story
More than ten systems captured the customer journey, but none connected it end to end. That fragmentation created slow reporting, uncertain marketing ROI, and missed opportunities to improve conversion and basket size.
10+ Disconnected Platforms
NetSuite, BigCommerce, web analytics, paid media, email, affiliates, and call tracking all used different structures and identifiers.
Reports Rebuilt by Hand
Every reporting cycle required repeated exports, reconciliation, and spreadsheet updates before analysis could begin.
Spend Without Proof
Channel-level reporting showed activity but could not reliably connect investment with qualified demand and revenue.
Products Sold in Isolation
Purchase data contained product-affinity signals, but the team lacked a repeatable way to create bundles and cross-sell actions.
Unseen Funnel Drop-Off
Disconnected behavioral data obscured where shoppers abandoned the journey and which interventions could recover conversion.
No Self-Serve View
Category managers and CXOs depended on prepared reports instead of exploring current performance on demand.
A Reliable Path From Source Systems to Daily Decisions
Rudder Analytics built a reusable pipeline rather than another report. Custom Python services collect data through SOAP and REST APIs, Amazon RDS provides the governed PostgreSQL layer, and a shared model gives Tableau and R the same trusted commercial context.
API Extraction
- NetSuite & BigCommerce
- Web & product analytics
- Ads, email & affiliates
- SOAP and REST APIs
AWS + PostgreSQL
- Python on EC2
- Amazon RDS
- Cross-platform mapping
- One analytics-ready model
Decisions at Every Level
- CXO dashboards
- Category-manager views
- Market-basket analysis
- Funnel analysis
One Automated Pipeline
Custom Python extracts every platform through SOAP and REST APIs, then loads to Amazon RDS.
Mapped and Blended
Cross-platform mapping lets sales and marketing be read together.
Dashboards for CXOs
Tableau gives leadership one cross-channel view.
Category Manager Views
Self-serve reporting replaces hand-built updates.
Market-Basket Analysis
Analysis in R turns product affinities into bundles.
Drop-Off Analysis
Google Analytics and Mixpanel guide conversion and spend decisions.
Less Reporting Work. More Commercial Clarity.
The new foundation changed both the economics of reporting and the quality of decisions. Teams gained a shared performance view, while deeper analysis revealed practical levers for acquisition, conversion, and cross-sell.
Automated reporting reduced effort and cost by approximately 60%, while affinity-led product bundles increased combined sales by 7%.
| Metric | Before | After | Impact |
|---|---|---|---|
| Reporting effort & cost | Manual pulls and updates | Automated pipeline | ~60% lower |
| Combined bundled sales | Sold separately | Affinity-based bundles | +7% |
| Marketing spend | Spread across channels | Reallocated to qualified demand | Reduced |
| Data sources | 10+ siloed platforms | One blended dataset | Consolidated |
| Executive reporting | Prepared by hand | Self-serve Tableau | New capability |
| Funnel visibility | Drop-off unseen | GA + Mixpanel analysis | New capability |
Flos USA moved from assembling numbers to acting on them: marketing investment follows qualified demand, product affinities shape bundles, and decision-makers can explore a current, shared view without manual intervention.
Engagement summary · Rudder Analytics
Data and AI for Brands Outgrowing Their Stack
Rudder Analytics builds that platform—from the first pipeline to reporting a board can act on.
