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How Mazenet Trained & Hired 76 Google Ads
Support Executives in Just 30 Days

Large organizations increasingly rely on the Train & Hire model to bridge the skill gap, reduce hiring risks, and build job-ready talent pipelines. But implementing this model at scale, especially for customer-centric roles like Google Ads Customer Support, comes with its own set of hiring, training, and operational challenges.

This case study explores how Mazenet Solutions, a leading workforce development partner, successfully onboarded 76 trained candidates for a major Google Ads customer support project in Gurgaon, despite significant sourcing barriers and talent readiness gaps.

Problem Statement:

The client needed immediate onboarding of 76 job-ready candidates for the Google Ads Customer Support process in Gurgaon. The training cycle had to be completed in under 18 days, and the hiring window was restricted to just 12 days to kick-start the training.

BU Expectations : Each candidate had to be trained and assessed on,

  • Google Ads and ad-operations understanding
  • Customer handling skills
  • Strong communication skills with Zero MTI
  • Ability to support global customers professionally

Key Obstacles Faced

  • Communication Barriers
  • No mother-tongue influence
  • Reluctance to the mandatory 1-month internship
  • Tight budget
  • Low interest in support roles
  • Understanding of the Google tech platforms
Bulk Hiring through Train and Hire program

How Mazenet Solutions Approached the Mandate

Multi-Channel Sourcing Strategy
  • With a strong connection with the institutes across India, Mazenet taps a minimum of 45% of the right fit groomable candidates from the direct institute hiring.
  • Expanded sourcing beyond job boards to reach a wider, more relevant talent pool.
  • Utilized internal databases, employee referrals, and college placement networks to identify candidates with strong learning potential.
  • Activated targeted outreach through WhatsApp groups, training communities, and organic social channels to maintain sourcing momentum.

This multi-stream approach ensured consistent candidate inflow, even when dropout rates were high.

Rigorous Pre-Screening for Communication Quality
  • Implemented focused evaluations for English fluency, pronunciation clarity, tone, and active listening.
  • UsConducted one-on-one communication screenings and mock call simulations to test customer-handling readiness.
  • Conducted a special interview-oriented training program for the candidate who can be groomed with focused training & prepared them for the interviews.
  • Shortlisted only those who demonstrated adaptability and the ability to improve through training.

This ensured the training batch was highly trainable and aligned with the communication standards required for Google Ads support.

Structured 18-Day Training Program
  • Designed a structured curriculum covering Google Ads fundamentals, support workflows, and hands-on practice to meet the client's requirements (80% Practical & 20% Theory).
  • Mazenet’s Edzentra, the AI integrated LMS carries the entire training process, including the assessments, to have live updates to the clients & the training team to understand the individual performance & enable the customized learning approach if required.
  • Integrated soft-skill enhancement sessions focused on pronunciation, confidence building, and language refinement.
  • This blended technical and communication training enabled candidates to become job-ready within 18 days.
Attrition Managemen
  • Setting a clear end goal on the Train and Hire Process & the growth in the particular domain for any newcomers with the continuous backup & support makes them trust the process & perform better.
  • The structured plan of hiring, Training & onboarding within the committed timelines ensures a higher rate of candidate retention.
  • The effective training approach, methodologies & interactive training led by the experts in the industry reduce attrition to below 5% in any IT/Support-based programs.
End-to-End Post-Training Placement Support
  • A dedicated team of seasoned recruiters to manage assessments, interview scheduling, and candidate coordination to streamline the placement process.
  • Supported candidates with documentation, client interactions, and onboarding requirements.
  • Ensured the hiring pipeline moved efficiently, enabling the client to onboard all 76 trained candidates within a week.

This structured support helped deliver the mandate on time and without compromising quality.

The Final Outcome

Outcome Result
Candidates Sourced 190
Profiles Shortlisted 95
Candidates Trained 80
Final Hires 76
Turnaround Time 18 training days + 12 days of hiring
Hiring Cost Within client’s limited budget

The Impact & Final Insights

This is one of our successful deliveries in the Google Ads project, where we have deployed 600+ in the last 2 years. This 76 is in a quick succession where the client wants to deploy on an immediate basis by commencing batches in parallel.

This project highlights Mazenet’s strong capability in Train & Hire for Google Tech, demonstrating how structured workforce development and targeted talent transformation can accelerate hiring outcomes. Our Train & Hire model continues to help enterprises overcome hiring bottlenecks, improve job-readiness, and scale teams faster, especially for high-volume functions like Google Ads support and other Google tech roles.

With proven frameworks, deep sourcing expertise, and domain-focused training programs, Mazenet continues to partner with leading organisations like Fortune 500 companies and Big 4 firms to build project-ready talent pipelines on time and at scale.

If your teams are expanding or facing skill shortages, Mazenet’s proven Train & Hire solutions can help you access a consistent flow of job-ready talent tailored to your business needs.

Project Requirements:

This Train and hire requirement is given by one of top Fortune 500 Companies

Project: Google Ads Train & Hire

Location: Gurgaon

Roles Filled: 76 [Customer Support]

Time-to-hire: 18 Days

Time to hire: 12 Days

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