Overview
- Industry: Financial Services / Manufacturing
- Client: CPI Card Group
- Duration: 2025 – ongoing
- Key Services: Data Automation, Sales Reporting, Media Monitoring
- Tech Stack:Databricks, AWS, Python, Streamlit, n8n
The Challenge
CPI Card Group needed to reduce the heavy reliance on manual processes for both sales reporting and media monitoring. Teams spent hours each month on repetitive tasks that slowed down decision-making and delayed insights.
Key challenges included:
- Manual extraction from Monarch (Excel/CSV) with repetitive calculations.
- Sales teams depending on slow, manually created reports.
- Representatives receiving individual Excel files each month with no self-service option.
- Media monitoring based on time-consuming manual searches across multiple sources.
The Solution
Celerik developed a set of automation solutions tailored to CPI’s needs, improving efficiency across sales and PR workflows.
Our contributions included:
- Sales Automation (Databricks + Streamlit):
- ETL pipelines to clean and transform Monarch financial data.
- A web application delivering personalized sales reports directly to each representative.
- Media Monitoring (n8n):
- Automated monitoring of CPI mentions across blogs and news sources.
- Classification of positive/negative mentions with automated daily summaries.
Results
| Aspect |
Before |
After |
| Data Processing |
Manual extraction from Monarch with repetitive steps. |
Automated Databricks ETL pipeline with structured tables. |
| Performance |
Sales teams relied on slow manual reporting. |
Automated Streamlit app delivers reports instantly to each rep. |
| User Experience |
Individual Excel files distributed monthly. |
Secure self-service web app with direct access for each representative. |
| Scalability |
Media mentions searched manually across sources. |
Automated n8n workflow monitors every 30 minutes with daily summaries. |
Key Outcomes:
- Automated sales reports, saving hours of manual effort.
- Secure and direct access for sales reps to their performance data.
- Media mentions tracked in near real-time, enabling faster PR responses.
- Manual reporting time reduced by 80%.
- PR reaction times improved by several hours.
Lessons Learned
What Worked:
- Combining Databricks and Streamlit for scalable sales reporting.
- Leveraging n8n for flexible, low-code marketing workflow automation.
What Could Be Improved:
- Direct integration with the Monarch API to eliminate remaining manual steps.
- Enhanced visualization of media sentiment in dashboards.
Team Achievement
This project highlighted cross-functional collaboration between data engineering, marketing, and automation teams. The delivery of two complementary automation solutions supported both Sales and PR, proving the value of scalable automation across departments.
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