E-commerce Growth Automation System
Workflow logic and architecture designed and planned as a portfolio case study.
Growth operating system for product research, campaign planning, creative testing, customer follow-up, and performance reporting.
Project Overview
A growth operating system for product research, campaign planning, creative testing, customer follow-up, and performance reporting, designed to keep e-commerce growth activity in one connected routine rather than scattered tools.
Business Context
E-commerce teams typically run paid campaigns, customer follow-up, and reporting as separate efforts, which makes it hard to see how creative decisions, spend, and follow-up connect to actual outcomes.
Problem
Campaign briefs, offer tests, and reporting are not structured consistently, and there is no routine connecting marketing activity to CRM follow-up or content production.
Proposed Solution
A structured operating rhythm: campaign briefs and audience hypotheses defined up front, offer and creative tests run on a schedule, and automated reporting on spend, revenue, conversion rate, and customer acquisition cost feeding a weekly optimization routine. Marketing tasks are connected to CRM follow-up so customer response feeds back into planning.
Target Users
- Small e-commerce teams running Meta and TikTok campaigns
- Founders managing growth without a dedicated media buyer
- Teams that need marketing and follow-up data connected instead of siloed
System Workflow
- 1
A campaign brief is drafted with audience hypotheses and offer variants
- 2
Creative tests run against the defined audiences
- 3
Performance data is pulled from ad platforms and GA4 into a reporting sheet
- 4
A weekly review compares results against the brief and sets next actions
- 5
Customer responses and follow-up tasks are logged back into the CRM workflow
Key Features
- Structured campaign briefs and audience hypotheses
- Automated reporting on spend, revenue, and conversion rate
- Weekly optimization routine
- Connection between marketing tasks and CRM follow-up
Architecture Overview
The system connects Meta Ads and TikTok Ads campaign data with GA4 and Shopify-concept storefront data, using n8n to automate data pulls into Google Sheets, where campaign briefs, test results, and the weekly optimization routine are tracked.
Planning Layer
Where campaigns and tests are defined.
Execution Layer
Where campaigns run and data is generated.
Reporting Layer
Where performance is consolidated and reviewed.
Automation Logic
- Scheduled n8n workflows pull spend and performance data from connected ad platforms
- Reporting sheets calculate conversion rate and acquisition cost automatically from raw data
- Weekly review tasks are generated from the previous week's results
Security and Privacy Considerations
- Ad platform and analytics access uses scoped, revocable API credentials
- Customer data referenced in follow-up tasks is limited to what is needed for the specific action
- Reporting exports avoid including unnecessary personal customer information
Challenges
- Keeping campaign briefs structured enough to compare results consistently over time
- Connecting marketing and CRM data without duplicating effort across tools
- Designing a weekly routine that is thorough without being too time-consuming to sustain
Business Value
- Centralizes campaign, storefront, and follow-up data into one reporting routine
- Keeps creative testing structured instead of ad hoc
- Connects marketing outcomes to CRM follow-up
Current Limitations
- Designed and planned as a portfolio system rather than run against live ad spend
- Reporting automation currently targets Google Sheets rather than a dedicated dashboard
- Test structures would need calibration to a specific store's catalog and audience
Future Improvements
- Move reporting into a dedicated dashboard with trend visualization
- Add automated anomaly flags for spend or conversion-rate shifts
- Expand the creative-testing structure with a template library
Project Gallery
Campaign brief template
Visual placeholder reserved for the brief and hypothesis structure.
Weekly reporting view
Visual placeholder reserved for the consolidated performance sheet.