This article provides a complete, practical walkthrough of the Manual N8Ntrainingcustomerdatastore Automate Triggered n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   How to Count Records from a Customer Datastore Using an n8n Workflow
   
   Meta Description:  
   Learn how to build a simple n8n workflow that counts customer records from a datastore using the manual trigger, a training data node, and a Set node. Perfect for beginners mastering workflow automation.
   
   Keywords:  
   n8n workflow, no-code automation, customer datastore, n8n training, count records, manual trigger, set node, workflow automation example, getting started with n8n
   
   Third-Party APIs Used:  
   n8n Training Customer Datastore API (n8n plugin for practice purposes; no external third-party API used)
   
   Article:
   
   Getting Started with n8n: Counting Customer Records from a Datastore
   
   n8n is a powerful workflow automation tool that empowers users to build complex processes without writing extensive code. Whether you’re automating lead processing, managing API integrations, or organizing day-to-day business logic, n8n gives you the flexibility to create workflows with ease.
   
   In this article, we’ll walk through a basic yet practical n8n workflow that retrieves data from a customer datastore used in n8n’s training environment and counts the number of customer records. This hands-on example is a great entry point for those new to n8n, as it uses a basic trigger and common nodes.
   
   ⏱️ What This Workflow Does
   
   This n8n workflow consists of three nodes:
   
   1. Manual Trigger – to execute the workflow manually.
   2. Training Customer Datastore – to fetch all customer records.
   3. Set Node – to calculate and store the number of records retrieved.
   
   Now let’s break down how each component works and how they connect together.
   
   🧱 Step-by-Step Breakdown
   
   1. Manual Trigger Node  
   Node Name: When clicking "Execute Workflow"  
   This node is your workflow ignition point. Instead of responding to an external webhook or timed event, it allows you to manually run the workflow with the click of a button. This is perfect for testing purposes or demos where you want to maintain full control over when the workflow starts.
   
   In this example, it’s the starting point that leads into the data-fetching node.
   
   
   2. Customer Datastore (n8n Training) Node  
   Node Name: Customer Datastore (n8n training)  
   Once the manual trigger fires, it immediately passes control to the “Customer Datastore” node. This node is part of n8n’s internal set of training tools, simulating a customer database for testing and educational purposes.
   
   The operation here is set to “getAllPeople,” which retrieves all person records from the datastore. This simulates pulling records from an actual CRM or customer database via API.
   
   
   3. Set Node: Calculating Total Records  
   Node Name: Set  
   The final piece of this workflow puzzle is the Set node. After all records are retrieved, the Set node is used to analyze the data and extract a specific value from it—in this case, a count of how many items were returned.
   
   Using the expression:
       
       {{ $input.all().length }}
   
   this node dynamically calculates and stores the number of records retrieved under a variable called itemCount.
   
   Additionally, it has the option “keepOnlySet” enabled, which ensures that only the new itemCount field is kept in the output—removing all other extraneous data from the previous node's results.
   
   🔄 Data Flow Overview
   
   - Step 1: Manual Trigger → You run the workflow manually.
   - Step 2: Training Customer Datastore → Pulls all customer records from the mock datastore.
   - Step 3: Set Node → Calculates a count of the pulled records and outputs it.
   
   🎯 Why This Workflow Is Useful
   
   Even though it’s a simple example, this workflow demonstrates fundamental n8n concepts:
   
   - Manual Triggers for testing
   - Pulling data from a datastore or external source
   - Manipulating results with built-in expressions
   - Passing and filtering data between nodes
   
   These are all core building blocks for more sophisticated workflows.
   
   🧪 Testing the Workflow
   
   To test this workflow:
   
   1. Open your n8n editor.
   2. Import or recreate the workflow using the nodes and parameters described above.
   3. Click “Execute Workflow.”
   4. View the output from the Set node—it should show an itemCount property with the total number of records retrieved.
   
   🎓 Learning Opportunity
   
   This workflow is ideal for n8n beginners, as it provides exposure to various key functionalities like data retrieval, dynamic calculation, and node chaining. From here, you can expand the workflow to include filtering specific records, sending data to an external API or database, or triggering notifications based on the count.
   
   🔗 Final Thoughts
   
   Building simple yet effective automation with n8n doesn’t have to be complicated. This example shows how combining just a few nodes can achieve useful results like counting customer records from a datastore. As you become more comfortable, you can plug in real-world databases, APIs, or business tools and elevate your automation to the next level.
   
   Happy automating! 🚀
   
   —  
   If you’re ready to explore more powerful workflows in n8n, check out the official documentation and training resources.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.