Workflows
Examples of how I approach automating repetitive work, connecting business tools, and improving data processes. Business details are omitted to protect confidentiality.
Lead Capture & Automated Follow-up
New leads are captured from a form, saved to a spreadsheet, and sent a follow-up email with a link to book a call.
New lead submission
A lead fills in a form.e.g. Facebook Lead Ads
Automation trigger
The automation platform receives the submission.e.g. Zapier, Make, n8n, Activepieces
Map lead fields
Maps the submitted fields to spreadsheet columns.Create Google Sheets record
Saves the lead as a new row for follow-up and tracking.e.g. Google Sheets
Send follow-up email
Sends the lead an automated message.e.g. Gmail
Include booking link
Invites the lead to book a call. Booking is their choice.e.g. Calendly link
full_nameemailphonesubmitted_atRead this workflow as text
- A new lead submits a form, for example a Facebook Lead Ads form.
- The automation platform (for example Zapier, Make, n8n, or Activepieces) receives the submission.
- The workflow maps the submitted fields to the spreadsheet columns: full name, email, phone number, and submission time.
- It adds the lead as a new row in Google Sheets for follow-up and tracking.
- It sends the lead a follow-up email through Gmail.
- The email includes a booking link, such as a Calendly link. The lead chooses whether to book a call; the workflow doesn't book it.
- The workflow doesn't decide whether a lead is genuine or will become a customer, and email delivery depends on the recipient's mail provider.
Automated File Processing, Validation & Approval
A representative design for receiving data files, cleaning and checking them, and updating a central system only after a person approves the changes.
Stage 1 · File ingestion & pre-validation
File submission
e.g. Gmail, Outlook, Google Drive, Dropbox
Automated file watcher
e.g. Make, Zapier, n8n
Format, size & headers valid?
Correction required
Marked Pending Audit
Stage 2 · Cleaning & validation engine
Data cleaning & standardization
Duplicate & numerical validation
Audit & change report
Stage 3 · Human review (required)
Reviewer alerted
e.g. Email, Slack, Microsoft Teams
Human review
Approved?
Stopped before any database update
Approval recorded
Stage 4 · Monitoring sync & report
Sync approved data
Sync succeeded?
Sync failed
Update monitoring system
Generate report
e.g. PDF, Excel, CSV
Processing complete
Read this workflow as text
- Stage 1. A file arrives as an email attachment or in a shared folder (for example Gmail, Outlook, Google Drive, or Dropbox).
- An automated file watcher (for example Make, Zapier, or n8n) retrieves the file and creates a processing log entry.
- The workflow checks the file's format, size, and expected column headers. If any check fails, processing stops and the file is flagged for correction. It never reaches the cleaning step.
- If the checks pass, the file is marked Pending Audit.
- Stage 2. The data is parsed and standardized: names, phone numbers, addresses, and dates.
- Records are compared with existing data to find duplicates and missing required fields. Row counts and numerical totals are checked for mismatches.
- An audit and change report lists new records, updated records, duplicates, invalid or incomplete records, numerical discrepancies, and validation results.
- Stage 3. A reviewer is alerted (for example by email, Slack, or Microsoft Teams) and reviews the proposed changes, flagged records, and reconciliation results.
- If the reviewer rejects the batch or requests edits, the workflow stops before the master database is updated. Corrections are requested, and the revised file starts again at Stage 1 validation.
- If the reviewer approves, the approval status and timestamp are recorded.
- Stage 4. Only approved changes are synced: new records are appended and existing records updated, without duplicate inserts.
- If the sync fails, the batch is marked failed and an alert is sent. No completion status is recorded.
- If the sync succeeds, monitoring metrics and summary data are refreshed, a report is generated (for example PDF, Excel, or CSV), and the batch is marked Processing Complete.
Possible Implementation Stack · Option A
No-code / low-code
- Make or Zapier for workflow orchestration
- Google Sheets and Apps Script for spreadsheet operations
- Python cloud functions when complex processing is needed
- Google Sheets or Airtable for monitoring
- Slack or Airtable Interfaces for approval
- Email notifications
Possible Implementation Stack · Option B
Open-source / custom
- n8n for orchestration
- Python and pandas for data processing
- PostgreSQL or the Google Sheets API for storage and sync
- A custom approval app or a team messaging integration
- Structured reporting
These are illustrative implementation options, not a record of the technologies deployed in a particular project.
Potential benefits
- Reduced repetitive data entry
- Consistent validation rules
- Easier discrepancy identification
- Human oversight before synchronization
- Improved processing visibility
- Standardized reporting
Potential benefits of this design, not measured outcomes.
About these examples
- Anonymized Hands-on Example
- A type of workflow I have built. Details are generic, and the field names are fictional.
- Example Architecture
- A representative system design, not a verified production deployment. The implementation stacks are illustrative options.
- Confidentiality
- No business, client, or customer information is shown. The diagrams are drawn for this page, not taken from real systems.
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