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CASE STUDY 04

College Baseball Recruiting Email Automation

An automated workflow that extracts player information from recruiting emails and organizes the data in Google Sheets for faster and more consistent review.

Project Overview

College recruiting information often arrives through email and requires someone to manually review each message and transfer important player details into a spreadsheet.

This project demonstrates how business systems and data integration can connect Gmail, Make.com, Regex parsing, Google Sheets, and Apps Script to reduce repetitive data entry.

The Challenge

Recruiting information had to be manually reviewed and transferred from emails into spreadsheets.

The Solution

Automatically identify recruiting emails, extract player information, and create structured spreadsheet records.

The Value

Reduce repetitive work and create a more organized recruiting review process.

The Business Problem

Recruiting emails contain valuable player information, but much of that information is embedded inside email subject lines and message content instead of a structured database.

Manually transferring this information takes time and can lead to inconsistent formatting or missed information.

The Automation Workflow

  1. Gmail monitors incoming recruiting emails.
  2. Make.com receives relevant email data.
  3. Regex and text parsing extract recruiting information from the email.
  4. Player information is separated into individual data fields.
  5. The information is mapped to the correct Google Sheets columns.
  6. A new player record is automatically added to the recruiting spreadsheet.
  7. Apps Script can further organize records based on location or other recruiting criteria.
College baseball recruiting email automation workflow using Make.com, Gmail and Google Sheets

Recruiting Data Captured

Data Organization

Google Apps Script can further organize recruiting records after they are added to the master spreadsheet.

For example, New Hampshire players can be routed to an in-state tab while players from other states can be organized into an out-of-state tab. This keeps the master data intact while making the recruiting information easier to review.

Estimated Time Savings

Before automation, each recruiting email required approximately 3–5 minutes to review the message, identify the relevant player information, and manually enter the data into the recruiting spreadsheet.

For every 100 recruiting emails, this represents approximately 5–8 hours of manual data entry.

With the automated workflow, player information is extracted, organized, and added to Google Sheets automatically. Staff can focus primarily on reviewing player information and handling exceptions rather than manually transferring data.

3–5 Minutes

Estimated manual processing time per recruiting email.

5–8 Hours

Estimated manual data-entry time per 100 recruiting emails.

Automated Entry

Player information is extracted and added to the spreadsheet automatically.

Business Value

Tools & Skills

Make.com Gmail Regex Google Sheets Google Apps Script Workflow Automation Data Extraction Data Mapping Process Improvement

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