Email Marketing Automation

Understanding the Problem

The financial institution was missing a key opportunity to connect with new members in the early stages of their onboarding journey—often the most crucial time to build engagement and loyalty. Most new members joined with only one product (such as a checking account) and were unaware of the broader suite of financial services available to them. To address this, our team set out to develop an automated, data-driven email journey that would increase engagement, drive cross-sell opportunities, and deliver value-driven communication.
The objective was to send a personalized welcome email within one day of account opening, followed by targeted promotional emails in the first week and subsequent weeks, showcasing the services and products each member did not yet have—such as credit cards, personal loans, or premium accounts. These emails were crafted not just to sell but to educate new members on the benefits of deeper engagement with the institution.

My Role

In my role, I led the strategy and execution from a data integration and performance optimization perspective. I was responsible for identifying new members through backend data analysis, extracting and transforming product usage data, and segmenting members based on what they had—and more importantly—what they didn’t. I developed and implemented the logic for triggering email workflows at the right time, with the right content, through the Documatix platform. I worked closely with the marketing and IT teams to ensure that the data infrastructure was robust, accurate, and secure.

Tools: Documatix, Kentico CMS, CRM Systems, ETL Pipelines,

Execution Details

1. Data Integration

Objective: Seamlessly connect internal and external data sources to the Documatix platform for real-time decision-making.

- Partnered closely with the data engineering team to integrate CRM systems, transactional databases, and third-party data sources into a centralized data repository.
- Led the implementation of automated ETL (Extract, Transform, Load) pipelines to ensure continuous data flow, including updates to member profiles such as account types, transaction history, and demographic attributes.
- Ensured this enriched and consolidated data was available in real time within the Documatix platform, forming the foundation of all email automation workflows.

2. Data Transformation

Objective: Convert raw data into actionable insights that aligned with Documatix workflow logic.

- Designed data mapping protocols that transformed backend data fields into meaningful business logic—e.g., flagging account statuses as “Y” (active), “N” (inactive), or “n” (null/default). These flags directly powered the conditional logic in automated workflows.
- Developed rules to trigger specific emails based on account activity, such as “1 day since sign-up” to launch a welcome series or “7 days without new engagement” to re-introduce available services.

3. Data Validation and Cleansing

Objective: Maintain data accuracy and integrity to ensure reliable campaign performance.

- Conducted ongoing audits of critical data fields, including email address validation, product ownership statuses, and member demographics to ensure consistency and usability.
- Created error-handling mechanisms to automatically detect and flag anomalies such as duplicate records, missing contact information, or invalid product codes.
- Collaborated with IT and compliance teams to align validation protocols with internal data standards and external regulatory requirements.

4. Pipeline Design and Optimization

Objective: Build high-performance, scalable infrastructure to support expanding email campaigns and audience segments.

- Designed and deployed robust data pipelines to handle both batch updates and real-time synchronization between data repositories and the Documatix platform.
- Optimized database queries to reduce latency and support thousands of records processed per trigger event.
- Stress-tested workflows and pipelines to ensure they could scale with future campaign volume without degrading system performance.

5. Monitoring and Troubleshooting

Objective: Maintain operational excellence through real-time visibility and proactive issue resolution.

- Designed monitoring dashboards to track data flow, pipeline health, and workflow performance in real time.
- Built automated alerts for critical failure points such as delayed syncs, misfired triggers, or data dropouts.
- Actively collaborated with data engineering and DevOps teams to resolve technical issues, conduct root-cause analyses, and implement fixes with minimal downtime.

Key Insights & Results

Personalization works: Tailoring emails to promote services members didn’t yet have led to a significant increase in interest and click-through rates.
Timing is critical: Triggering emails within the first 14 days post sign-up captured attention during the highest engagement window.
Clean data = strong performance: Ongoing cleansing and validation ensured workflows were precise and relevant.

Business Impact

34% increase in email engagement rates.
22% improvement in product adoption (e.g., credit card signups, premium upgrades).
Created a scalable and automated framework requiring minimal manual intervention.

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