Automated Lead Prospecting System for $100M+ Enterprise
Allegiance Industries · 2026
Daily Manual Input
Annual Cost Savings
Platforms Integrated
Data Points Per Lead
Result proof path
Outcome
Zero daily manual input and $9-10K annual savings.
Mechanism
Google Sheets, Make.com, Relevance AI, Apollo, and Zoho CRM connected into one daily prospecting system.
Proof
Verified client quote plus 17 mapped data fields per lead.
The Situation
Allegiance Industries is a $100M+ facility services company headquartered in Columbia, South Carolina, with 1,200+ employees operating nationwide across janitorial, security, and electrical divisions. Their sales operation depended entirely on manual research -- individual reps would search LinkedIn, company websites, and industry directories one prospect at a time, spending 15-25 hours per week on prospecting alone. The team had experimented with purchasing lead lists from third-party data vendors, but the quality was poor: outdated contact information, missing direct phone numbers, and no way to verify whether a lead matched their ideal customer profile. With two major verticals to target -- Manufacturing and Education -- the volume of research required was throttling pipeline growth. Each vertical demanded different decision-maker titles, different company characteristics, and different qualifying criteria. A sales rep targeting a school district needed to find facilities directors, while one targeting a manufacturing plant needed operations managers. The manual approach could not scale to cover both verticals adequately. They needed a system that could find, research, and enrich decision-maker contacts at scale without adding headcount, and it needed to deliver leads that were ready for outreach the moment the sales team started their day.
The Challenge
Manual Research Bottleneck
Sales reps spent 15-25 hours per week researching prospects one at a time across LinkedIn, company websites, and industry directories. This consumed over a third of their productive selling time and created an artificial ceiling on how many new prospects could enter the pipeline each week.
Inconsistent Lead Quality
Previous attempts with third-party lead lists produced outdated contact information, missing phone numbers, and unverified email addresses. Reps wasted additional hours chasing dead leads, and the inconsistency eroded trust in any prospecting data that was not manually gathered by the team.
Dual-Vertical Targeting Complexity
Manufacturing and Education verticals require fundamentally different decision-maker profiles, qualifying criteria, and outreach messaging. A single prospecting process could not serve both effectively, forcing the team to run parallel manual workflows that doubled the research burden.
No CRM Automation
Every lead had to be entered into Zoho CRM by hand, with reps copying and pasting data across fields. This introduced data entry errors, inconsistent formatting, and duplicate records that cluttered the pipeline and made accurate reporting nearly impossible.
What We Built
We designed and deployed an end-to-end autonomous lead prospecting system spanning five integrated platforms, built to operate without any daily human input. The architecture was deliberately modular: each platform handles one job, and the AI agent at the centre makes the intelligent decisions that previously required a human researcher. The system reads target companies from Google Sheets -- the simplest possible interface for the sales team to add new targets. Make.com handles orchestration, triggering daily scheduled scenarios that process companies sequentially and manage error handling, retries, and logging. The custom Relevance AI agent is the system's brain: it receives company data, determines which job titles to search based on the industry vertical, constructs optimised Apollo queries, validates the contacts returned, and builds the complete CRM payload. Apollo provides the verified data layer -- email addresses, direct phone numbers, LinkedIn profiles, and company firmographics. Finally, Zoho CRM receives the enriched leads with 17 mapped data fields and built-in duplicate detection that checks existing records before creating new entries. The entire pipeline runs automatically at 8:00 AM daily, meaning the sales team arrives each morning to a fresh batch of pre-researched, pre-qualified leads ready for outreach.
Step 1
Google Sheets
Sales team adds target companies to two separate spreadsheets for Manufacturing and Education verticals. The interface is deliberately simple -- reps only need to enter a company name and basic details, keeping the barrier to entry as low as possible for non-technical users.
Step 2
Make.com
Orchestration layer that runs daily scheduled scenarios at 8:00 AM. Reads companies from both spreadsheets, processes them sequentially through the AI agent, handles error recovery and retries, and logs every action for full auditability of the pipeline.
Step 3
Relevance AI Agent
The intelligent core of the system. Receives company data, determines which job titles to search based on industry vertical and company size, constructs optimised Apollo queries with the right filters, validates returned contacts against quality thresholds, and assembles the complete CRM payload with all 17 data fields.
Step 4
Apollo
Verified data layer providing decision-maker contact information. The agent queries the people search API with industry-specific parameters and returns verified email addresses, direct phone numbers, LinkedIn profile URLs, and detailed company firmographic data for up to three contacts per company.
Step 5
Zoho CRM
Output layer where enriched leads land with all 17 mapped data fields pre-populated. Built-in duplicate detection queries existing records before creating new leads, preventing the data quality issues that plagued the previous manual entry process and ensuring clean pipeline reporting.
The Results
Up to 41 / day
Company Processing Capacity
Configured to process up to 41 target companies in each daily run
Zero
Daily Manual Input
The run completes at 8:00 AM before the sales team arrives, replacing 15-25 hours a week of manual research
17
Data Fields Per Lead
Full profiles including name, verified email, direct phone, job title, company, LinkedIn URL, and firmographics
$9-10K
Annual Cost Savings
Replaces 15-25 hours per week of manual prospecting, freeing the sales team to focus on closing
2
Industry Verticals
Manufacturing and Education verticals with distinct decision-maker targeting logic for each
8:00 AM
Daily Execution Time
System completes its daily run before the sales team arrives, delivering fresh leads at the start of each day
How It Works Day-to-Day
The system operates on a fully autonomous daily cycle. Each morning at 8:00 AM, the Make.com orchestrator triggers and reads any new companies added to the Google Sheets inputs. The AI agent processes each company individually, researching the right decision-maker titles for the vertical, querying Apollo for verified contacts, and validating the data before pushing it to Zoho CRM. The sales team does not interact with the automation at all -- they simply add target companies to a spreadsheet when they identify new prospects and find enriched leads waiting in their CRM each morning. Reporting is built into the orchestration layer: every run logs how many companies were processed, how many contacts were found, and any errors encountered. If a company returns no valid contacts, it is flagged for manual review rather than silently dropped. After implementation, the team continued to support tweaks and resolve issues as they arose.
What This Demonstrates
Verified video testimonial
The video proof is represented by the verified client quote below so this public page does not depend on a restricted external embed.
"Jacob and his team implemented an awesome AI agent for us that saves us around 9 to $10,000 per year. Instead of being limited at around 100 new leads per day, Jacob put in a system for us within a couple of days and it really just came out flawless. I was extremely shocked at how well it worked right away. Would hire him again, and most likely will for future projects."
Eric Ormsbee
Director of Inside Sales and Marketing, Allegiance Industries
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Frequently Asked Questions
How long did it take to build and deploy the system?
The complete system was designed, built, tested, and deployed within a matter of days. This included integrating all five platforms, configuring the AI agent's targeting logic for both Manufacturing and Education verticals, mapping all 17 CRM fields, and running validation tests to ensure data quality met the team's standards before going live.
Can the system be adapted for additional verticals beyond Manufacturing and Education?
Yes. The AI agent's targeting logic is configurable, not hardcoded. Adding a new vertical involves defining the decision-maker titles, company size thresholds, and qualifying criteria for that industry. A new Google Sheet is created for the vertical, and the orchestration layer picks it up automatically on the next daily run.
What happens if the system encounters duplicate leads already in the CRM?
Built-in duplicate detection queries existing Zoho CRM records before creating any new lead. The system checks against email address, company name, and contact name to prevent redundant entries. If a match is found, the existing record is preserved and the duplicate is logged for review rather than overwriting any data.
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