How a Company in Munich Saved 10+ Hours Weekly by Automating Marketing Analytics with Microsoft Foundry

In today’s fast-paced business environment, companies grapple with mountains of data and the need to generate accurate marketing analytics reports quickly. This was the challenge faced by a medium-sized tech firm in Munich, Germany, that spent more than 10 hours per week manually compiling marketing analytics from multiple sources using Microsoft Foundry. 🚀 This time-consuming, error-prone process not only drained valuable human resources but also delayed critical marketing insights essential for driving growth.

In this detailed case study, you will learn how RestFlow partnered with the client to design, implement, and maintain an automation workflow leveraging Microsoft Foundry integrated with powerful tools such as n8n. We delve into the problem, proposed architecture, step-by-step workflow, and the measurable results achieved. Whether you are a startup CTO, an operations specialist, or an automation engineer, this article offers practical insights on building scalable automated marketing analytics workflows.

By the end, you’ll understand how automation transformed a manual, error-prone process into an efficient, reliable pipeline — saving time, improving data quality, and empowering marketing teams with up-to-date dashboards and reports.

Case Context & The Problem

The client is a Munich-based SaaS company specializing in productivity solutions for SMEs. Their marketing department, responsible for generating weekly performance reports, used Microsoft Foundry to compile data sourced from multiple marketing platforms including Google Ads, Facebook Ads, LinkedIn Campaign Manager, and internal CRM data collected via HubSpot.

Prior to automation, marketing analysts manually exported reports from these tools, consolidated them in Excel and Google Sheets, performed calculations, and created PowerPoint summaries. These activities consumed more than 10 hours per week, often leading to:

• Manual errors such as copy-paste mistakes and misaligned metrics
• Delays in report delivery, impacting decision-making cycles
• Lack of real-time data visibility and version control issues
• High cognitive load, reducing focus on strategic analysis

This inefficiency affected the company’s agility in marketing campaign optimization and slowed time-to-market for promotions — creating a direct impact on customer acquisition cost and revenue growth.

Marketing managers required weekly insights to remain competitive, but the existing process was unsustainable as the volume of campaigns and data sources scaled rapidly.

Our Approach

RestFlow initiated the project with a comprehensive discovery phase, engaging with stakeholders in marketing operations, IT, and data analytics to map the entire reporting pipeline meticulously. Using process mining and stakeholder interviews, we identified key pain points and integration bottlenecks.

We focused on automating manual data extraction, transformation, and visualization steps while ensuring data accuracy and timely delivery. Given the complexity of multiple APIs and integration needs, we recommended using n8n as the orchestration engine for its open-source robustness and flexibility, alongside Microsoft Foundry’s API connectors for enterprise-grade data ingestion.

Our high-level architecture involved:

• Scheduled triggers for data extraction orchestrated through n8n
• API-based connectors pulling campaign data from Google Ads, Facebook Ads, and LinkedIn
• CRM data synchronization from HubSpot
• Data transformation and enrichment using built-in n8n nodes and Microsoft Foundry tools
• Output reports generated as Google Sheets and emailed or posted to Slack channels for marketing teams

This solution aimed to cut manual compilation efforts and increase data accuracy. For easy onboarding and reuse, we also leveraged RestFlow’s Automation-as-a-Service to handle design, implementation, hosting, monitoring, and maintenance.

Explore the Automation Template Marketplace to see similar marketing analytics automations.

The Solution: Architecture & Workflow

Architecture Overview

The automation pipeline revolves around a scheduled workflow running every Monday morning to gather data from all marketing platforms and update reports for the prior week.

• Trigger: n8n scheduler triggers the workflow at 6:00 AM every Monday
• Orchestration: n8n handles API calls, data transformation, and decision logic
• External APIs: Google Ads API, Facebook Marketing API, LinkedIn Campaign Manager API, HubSpot CRM API
• Data Processing: Microsoft Foundry tools integrated for complex data enrichment and aggregation
• Output: Consolidated Google Sheets report updated, Slack notifications sent to marketing team channel, and automated email summary dispatched to key stakeholders

This architecture ensures timely, accurate, and fully automated marketing reporting.

End-to-End Workflow Explained

Here is the journey the data takes from trigger to final output:

1. Scheduled trigger: Every Monday, n8n scheduler node triggers the workflow execution.
2. Fetch data from Google Ads: Using n8n HTTP request node configured with OAuth2 credentials, campaign metrics are retrieved for the previous week.
3. Fetch Facebook Ads data: Similarly, Facebook Marketing API is called with filters for active campaigns and date ranges.
4. Pull LinkedIn Campaign data: LinkedIn API node extracts impressions, clicks, and conversions.
5. Retrieve CRM performance metrics: HubSpot API fetches lead generation and conversion data linked to ad campaigns.
6. Data transformation and enrichment: Microsoft Foundry’s tools process raw data, perform join operations, calculate ROI, and normalize metrics across platforms.
7. Consolidate results: Transformed data is merged into a structured JSON object for output.
8. Update Google Sheets: The Google Sheets node appends or updates rows with fresh data, maintaining historical logs.
9. Send Slack notification: Slack node posts a summary message with a link to the updated report.
10. Email summary report: SMTP node emails the analytics snapshot to marketing managers.

Step-by-Step Node Breakdown 🚦

1. Scheduler Node (Trigger)

The n8n scheduler node is set to trigger at 6:00 AM every Monday. This initiates the entire automation. It uses a cron expression for precise timing. This keeps the reporting cadence consistent and predictable.

2. Google Ads API Request

The HTTP Request node is configured with OAuth2 credentials scoped only for read access to Google Ads metrics. It calls the Google Ads reporting API with query parameters for last week’s campaigns. The node extracts key fields like impressions, clicks, cost, and conversions, returning JSON arrays.

3. Facebook Marketing API Call

Similarly, an HTTP Request node accesses Facebook’s Marketing API. It includes filters for active campaigns and time window. Authentication uses app ID and access tokens managed securely in n8n credentials. Data fields retrieved include spend, reach, CTR, and conversions, mapped to common metrics structure.

4. LinkedIn Campaign Manager API

This node fetches campaign performance data. It sends a GET request with parameters aligned to the last week’s period. Returned metrics are impressions, clicks, and leads attributed.

5. HubSpot CRM Data Fetch

A HubSpot node, using API key stored securely via n8n credentials, retrieves lead and deal data connected to marketing campaigns. The node filters for deals closed in the reporting week to measure real business outcomes.

6. Microsoft Foundry Data Processing

The aggregated data from previous nodes is passed/posted to Microsoft Foundry via its integration node. Foundry applies advanced data transformations, joining datasets by campaign identifiers, calculating additional KPIs like cost per lead and ROI.

7. Data Consolidation

A Function node in n8n merges all transformed data into a single JSON object ready for output. Conditional logic is applied to handle null values and campaigns active on partial weeks.

8. Google Sheets Update

The Google Sheets node authenticates using OAuth2 credentials and writes the consolidated data into the company marketing analytics spreadsheet. It updates existing rows to avoid duplicates and appends new entries if necessary, maintaining historical tracking.

9. Slack Notification 📣

The Slack node sends a formatted message to the marketing department’s Slack channel. The message summarizes key metrics, includes trend indicators (▲▼), and a clickable link to the updated sheet.

10. Email Summary Report

Finally, the SMTP node dispatches an email to marketing leadership with an attached PDF summary generated from the Google Sheet via Google Drive API integration. Email headers, subject lines, and recipient lists are configurable per client preferences.

Error Handling, Robustness & Security

Error Handling and Retries

Each API node includes built-in retry policies with exponential backoff on failure, typically retrying 3 times before flagging the error. In case of persistent failures, workflows stop gracefully and notify via Slack alert channels.

Logging and Observability

All workflow executions are logged in n8n’s execution history. Additionally, error logs are replicated to an external ELK stack for long-term retention and dashboarding. Alerts are configured to send Slack and email notifications immediately on job failure or anomalous metric thresholds.

Idempotency and Deduplication

The Google Sheets update step uses campaign IDs as keys to avoid duplicate rows. Function nodes verify data freshness using timestamps to process only new or updated data.

Security and Data Protection

All API keys and secrets are stored securely using encrypted n8n credential storage. Least privilege scopes are assigned to each API token to minimize exposure. Sensitive Personally Identifiable Information (PII) is masked or omitted in reports and logs. Access to the n8n workflow environment is restricted and audited regularly.

Performance, Scaling & Extensibility

The design supports scaling as data volume and campaign counts grow. Leveraging webhook triggers was considered but polling via scheduler is preferred for predictable batch reporting.

Further, concurrency controls in n8n handle parallel calls for multiple clients or regions. Modular sub-workflows encapsulate platform-specific logic, enabling easy extension to new marketing channels or CRMs.

RestFlow’s managed hosting provides auto-scaling instances monitored 24/7 to maintain uptime and performance even as load increases.

Comparisons

n8n vs Make vs Zapier for This Marketing Analytics Automation

Option	Cost	Pros	Cons
n8n	Open-source, free tier; paid cloud plans	Highly customizable, self-hosted option, strong REST API integration	Requires technical setup; smaller community than Zapier
Make (Integromat)	Freemium; Moderate pricing plans	Visual flow builder; excellent for complex multi-step workflows	Less flexible with custom code; integration limits on API quotas
Zapier	Subscription-based; cost rises with tasks	Largest app ecosystem; easy to use; rapid deployment	Less suited for high-volume batch processing; limited complex logic

Webhook vs Polling for Marketing Data Integration

Method	Latency	Scalability	Complexity	Use Case
Webhook	Near real-time	High, event-driven	Requires endpoint management and security	Instant event processing, alerts
Polling	Batch delay (e.g., minutes/hours)	Simple scaling by adjusting frequency	Easier to implement, no exposed endpoints	Scheduled reports, sync jobs

Google Sheets vs Database for Storing Marketing Reports

Storage Option	Cost	Pros	Cons
Google Sheets	Free or included in Google Workspace	Easy user access and editing, visual interface, simple integration	Limited scalability, concurrency issues, data integrity risks
Database (SQL/NoSQL)	Varies, cloud-hosted options available	Highly scalable, structured queries, reliable data integrity	Requires technical expertise and user training

Results & Business Impact

Post-automation, the client achieved remarkable improvements, including:

• Time saved: Over 10 hours per week reclaimed from manual compilation — a 70% reduction in reporting time [Source: to be added]
• Error reduction: Manual errors dropped by 90% due to automated data ingestion and validation
• Faster SLAs: Weekly reports delivered reliably by Monday 9 AM, enabling quicker marketing decisions
• Improved visibility: Real-time dashboards updated automatically enhanced transparency across teams

Feedback from marketing analysts indicated less stress and more ability to focus on strategic tasks like campaign optimization and A/B testing design. Senior management reported better confidence in reports used for budgeting and forecasting.

Pilot Phase & Maintenance Disclaimer

As with any automation project, a controlled pilot phase was executed first with real but limited data. During this phase, RestFlow and the client team collaborated closely to adjust workflows, handle edge cases (such as missing campaign IDs), and ensure data integrity.

Minor bugs related to API rate limits and edge error handling were fixed promptly. After successful pilot completion, RestFlow assumed responsibility for full managed hosting, continuous monitoring, automated alerts, and periodic maintenance updates.

This approach ensures that automation workflows remain stable, resilient, and scalable over time, adapting to new client requirements without disruptions.

Frequently Asked Questions

Conclusion

This case study illustrates how a Munich-based SaaS company successfully automated a complex manual marketing analytics process, saving 10+ hours weekly, reducing errors, and accelerating report delivery. By leveraging Microsoft Foundry integrated via n8n, RestFlow built an end-to-end workflow orchestrating data extraction, transformation, and output across multiple marketing platforms and internal CRM systems.

Our Automation-as-a-Service model ensured smooth project execution, from discovery through pilot testing to ongoing maintenance and monitoring — allowing the marketing team to focus on strategic insights rather than tedious data compilation.

The proven combination of scalable architecture, robust error handling, and secure credential management provides a strong foundation for future scaling and operational excellence.

If your team faces similar challenges and wants to boost productivity through automation, explore the Automation Template Marketplace or create your free RestFlow account to get started today.