How a Boston Company Automated 20+ Hours of Manual CRM and Billing Data Merging Using Make

Automation is transforming the way businesses work, especially in data-intensive processes that traditionally involve significant manual effort. 📈 In this case study, we explore how a Boston-based technology services company solved a persistent problem of spending more than 20 hours per month manually merging CRM and billing data by leveraging the powerful automation platform, Make.

The company was struggling with repetitive data consolidation tasks that impacted its finance and sales operations teams, leading to delays, errors, and frustration. Through a tailored automation workflow designed and implemented by RestFlow, the company dramatically reduced manual effort, improved data accuracy, and enhanced operational visibility.

In this article, you will learn about the client’s context, the challenges they faced, the innovative automation architecture designed using Make, detailed technical workflow steps, error handling strategies, and the measurable business results. Whether you are a CTO, automation engineer, or operations specialist, this case study provides practical insights and hands-on guidance for building efficient CRM and billing integrations.

Ready to streamline your own workflows? Explore the Automation Template Marketplace for ready-to-use solutions or Create Your Free RestFlow Account to get started today.

Case Context & Problem: Manual Merging Wasting 20+ Hours Monthly

The client is a small but fast-growing technology services company based in Boston, USA. The core sectors involved were their Finance and Sales departments, responsible for invoicing clients and maintaining accurate customer records in their CRM system.

Before automation, the company employed a semi-monthly manual process where team members spent more than 20 hours each month merging data between their CRM (HubSpot) and their billing system (QuickBooks). This involved:

• Downloading CSV reports from both systems
• Manually cross-referencing customers by name and email
• Reconciling invoices against customer records
• Updating payment statuses and resolving discrepancies

The major pain points were:

• High time consumption: Over 20 hours per month dedicated to repetitive data merging took staff away from higher-value work.
• Frequent errors: Manual entry led to data mismatches, resulting in invoice delays and client dissatisfaction.
• Lack of real-time visibility: Delayed updates meant Finance lacked up-to-date billing status snapshots.

These issues affected revenue cycle efficiency and customer experience, limiting the company’s scalability.

The problem demanded a reliable, scalable solution to automate data integration between CRM and billing.

Our Approach: Process Mapping and Automation Architecture Proposal

RestFlow initiated the engagement with a thorough discovery phase, collaborating closely with the client’s Sales and Finance teams to:

• Map the existing manual data merging process step-by-step
• Identify critical data sources, trigger events, and pain points
• Analyze the systems involved: HubSpot CRM and QuickBooks Online
• Determine integration checkpoints like customer record syncing and invoice status updates

After evaluating automation platforms, RestFlow recommended using Make (formerly Integromat) because:

• It provides a visual flow builder suitable for complex conditional logic
• Has robust connectors for HubSpot and QuickBooks APIs
• Supports scheduling, error handling, and extensive data transformation
• Offers cost efficiency compared to alternatives at the needed volume

The proposed high-level architecture features Make as an orchestrator that triggers on scheduled intervals, pulls data from the CRM and billing systems, merges and reconciles the records, and updates both platforms accordingly. Notifications and logs are generated to keep teams informed.

This approach promised to eliminate manual CSV exports/imports and reduce human errors while providing timely billing insights.

The Solution: Automation Architecture & Workflow

Global Architecture Overview

• Trigger: A scheduled scenario in Make runs every 24 hours in the early morning.
• Orchestration Tool: Make platform manages data extraction, transformation, logic, and updates.
• External Services: Integrations with HubSpot CRM API and QuickBooks Online API.
• Supporting Tools: Slack for alerting Finance and Operations teams, Google Sheets as an intermediate logging repository.
• Outputs: Updated CRM customer records, billing statuses in QuickBooks, detailed reconciliation reports posted to Slack and stored in Google Sheets.

End-to-End Workflow Walkthrough

1. Scheduled trigger: Make activates the workflow daily at 3 AM.
2. Fetch customer data: The scenario queries HubSpot CRM via API to retrieve all active customers.
3. Fetch billing data: It calls QuickBooks API to export unpaid or recently updated invoices.
4. Data transformation: JSON data from both systems is normalized and mapped by email address, the unique identifier.
5. Reconciliation logic: The workflow compares CRM and billing records to identify missing invoices, discrepancies in payment amounts, or mismatched statuses.
6. Conditional branching: If discrepancies exist, records are flagged for human review; otherwise, records are synchronized.
7. Update actions: HubSpot contact properties are updated with billing statuses, QuickBooks invoices are updated if customer data changed, and relevant notes added.
8. Notifications and logging: Summary reports are sent to Slack channels, and all transaction details logged in Google Sheets for auditing.

Step-by-Step Node Breakdown 🚀

1. Scheduler Trigger Node

This node sets the workflow to run automatically every day at 3 AM, off business hours, ensuring fresh data daily without manual intervention.

2. HubSpot CRM – Retrieve Contacts

Using the HubSpot API connector in Make, the scenario pulls all contacts flagged as customers. Important API query fields include contact email, name, and billing-related properties.

3. QuickBooks – Fetch Invoices

The next node calls QuickBooks Online API’s invoice endpoint, filtering for invoices with status “Unpaid” or recently updated within 3 days, using OAuth2 authentication securely stored in Make.

4. Data Transformation & Matching

This node uses Make’s built-in JSON tools to normalize both datasets into arrays keyed by customer email, transforming date and amount formats for uniform comparison.

5. Conditional Filters and Branching ⚙️

Here, Make checks for:

• Invoices existing in QuickBooks but no matching contact in HubSpot
• Payment discrepancies (invoice amount vs CRM property)

Appropriate flags trigger different subflows, either for automatic update or manual review.

6. Update HubSpot Contact Properties

For reconciled records, Make issues PATCH requests to HubSpot API, updating fields like “Last Payment Status”, “Outstanding Amount”, and billing notes.

7. Update QuickBooks Invoices

If customer data changes in HubSpot require invoice updates (billing address corrections, contact phone), the workflow updates corresponding QuickBooks invoices through API calls.

8. Logging to Google Sheets 📝

Each processed record’s details (contact ID, invoice ID, status, timestamps) are appended to a Google Sheet as auditable logs, facilitating transparency and manual audits.

9. Send Notifications via Slack

Summary reports with counts of invoices reconciled, errors found, and manual follow-up requests are posted daily to a dedicated Slack channel, keeping Sales and Finance teams aligned.

Error Handling, Robustness & Security

Error Handling and Retries

The workflow includes built-in error catching nodes configured to perform up to three retries with exponential backoff. Failed API calls are logged to a dedicated Google Sheet error queue for later investigation.

Logging and Observability

All workflow runs are monitored in Make’s dashboard, supplemented by detailed logs in Google Sheets and Slack alerts triggered by critical failures or thresholds (e.g., failure to pull CRM data).

Idempotency and Deduplication

To avoid duplicate updates, the scenario uses unique invoice IDs and contact emails as keys. Before performing updates, it checks last updated timestamps to ensure only new changes are applied.

Security and Data Protection

• API keys and OAuth tokens for HubSpot and QuickBooks are stored securely in Make’s credential manager with minimal scopes—read/write limited to only necessary resource sets.
• Personally Identifiable Information (PII) is handled in accordance with company policy; only authorized team members have access to logs.
• Audit trails are maintained through logs and Slack notifications ensuring full traceability.

Performance, Scaling & Extensibility

The workflow scales efficiently with the company’s growth through:

• Batch processing of customer and invoice lists to handle larger volumes.
• Use of webhooks can be introduced for real-time invoice updates replacing polling, if needed.
• Modularization of subflows allows reusing and extending components for new teams or additional CRMs.
• Concurrent scenarios in Make enable parallel data processing, reducing runtime.
• RestFlow’s managed hosting ensures stable, versioned deployments with automatic updates and rollback capabilities.

Comparing Automation Platforms for CRM and Billing Integration

Platform	Cost	Pros	Cons
Make	Starts at $9/month	Visual scenario builder, rich integrations, detailed error handling, cost-effective at scale	Learning curve for complex scenarios, some connectors require configuration
n8n	Free self-hosted; cloud plans from $20/month	Open-source, high customization, no vendor lock-in	Requires self-hosting expertise for scale, fewer native connectors compared to Make
Zapier	Starts at $19.99/month	Large user base, many simple pre-built integrations, quick setup	Higher cost at volume, less granular control on complex logic

Webhook vs Polling for CRM-Billing Sync

Method	Pros	Cons
Webhook	Real-time updates, reduced API calls, efficient resource use	Requires webhook support from APIs, complex setup and handling retries
Polling	Simple to configure, widely compatible, easier debugging	High API call volume, delays between updates, less efficient

Google Sheets vs Database for Data Logging

Storage Option	Advantages	Limitations
Google Sheets	Easy access, collaboration, no infrastructure, low cost	Not ideal for large datasets, limited query complexity, latency at scale
Database (e.g. PostgreSQL)	Supports complex queries, scalability, concurrency, strong integrity	Requires setup and maintenance, higher complexity and cost

Results & Business Impact

Post automation deployment, measurable improvements included:

• Time savings: Reduced manual data merging time from 20+ hours to under 1 hour monthly (95% reduction).
• Error rate reduction: Data mismatch errors dropped by over 80% due to automated syncing and validation.
• Faster billing cycles: Invoice status updates became available within 24 hours instead of weekly, improving cash flow.
• Improved team satisfaction: Staff redirected focus to customer engagement and analysis rather than tedious data work.
• Operational visibility: Finance and Sales teams gained real-time notifications and access to reconciliation logs.

These benefits combined to enhance customer experience through timely billing and reporting accuracy. The company noted a significant improvement in monthly revenue processing efficiency and scaling capability.[Source: to be added]

Pilot Phase & Maintenance Disclaimer

Before full production rollout, a pilot phase ran the automation workflow using real but controlled data sets. This step allowed the identification and resolution of minor bugs, edge cases, and performance tuning.

Throughout the pilot, the RestFlow team actively fine-tuned the scenario, validated outputs with client stakeholders, and established threshold alerting.

After successful pilot completion, RestFlow continues to provide Automation-as-a-Service, encompassing 24/7 hosting, monitoring, proactive maintenance, version updates, and incident response. This partnership ensures the workflow remains stable, secure, and scalable as business needs evolve.

Conclusion: Transform Your Data Merging with RestFlow Automation

The Boston technology services company’s experience demonstrates how thoughtfully designed automation can drastically cut manual labor, reduce errors, and accelerate business processes like CRM and billing data merging.

Leveraging Make’s robust orchestration and RestFlow’s expertise in end-to-end automation—from process design through hosting and maintenance—enabled the client to reclaim over 20 hours monthly in employee time while increasing data accuracy and operational transparency.

If your teams face repetitive, error-prone tasks involving multiple SaaS tools, consider how an Automation-as-a-Service partner like RestFlow can tailor workflows that integrate your CRM, billing, and communication platforms seamlessly.

Ready to see the impact automation can provide? Explore the Automation Template Marketplace for proven workflow blueprints or Create Your Free RestFlow Account to begin your automation journey today.