Our consultants were spending more time clicking through irrelevant stages than actually engaging with candidates. We needed a solution that could mirror our unique hiring approach. That’s when we fully customized Genie Hiring ATS & CRM System to align perfectly with our internal hiring workflow.

One of our biggest pain points was lost follow-ups during candidate nurturing. In IT recruitment, where the best candidates are off the market in days, even a short delay can cost you a great hire. We implemented a custom automated follow-up system within our ATS that triggers tailored emails or reminders based on candidate stage and last contact activity. This reduced manual tracking, kept communication consistent, and increased response rates significantly.

We also built customized “Best Match” algorithms that prioritize candidates not only by skills and keywords but also by hiring manager preferences, cultural fit indicators, and historical hiring success data. This adaptation helped our recruiters identify the most suitable candidates faster and improved our client satisfaction scores.

Another key customization was integrated client dashboards, giving clients real-time visibility into shortlists, interview status, and candidate feedback. This drastically reduced the back-and-forth email trails and brought transparency into the hiring process, aligning both our internal team and clients around shared data.

It resulted in a system that feels less like a tool and more like an extension of our recruitment core. We’ve reduced time-to-fill by almost 30%, improved candidate engagement, and strengthened client trust by keeping them informed throughout the process.

Our customization wasn’t about adding more features; it was about making our ATS work the way we recruit. By aligning technology with our human workflow, we turned a once-administrative system into a strategic enabler of hiring success.

In today’s market, high application volume doesn’t always mean high-quality talent. It’s common for us, and the clients we support, to see 100+ applicants for a single role within 48-72 hours. The challenge? Roughly 95% of those applicants are unqualified.

The real bottleneck isn’t finding people. It’s filtering signal from noise.

At Main Line Talent Group, we customized our ATS to solve this exact problem. Two changes have had the biggest impact:

1. A smarter, more structured data model

Because we recruit for niche ERP roles across manufacturing and distribution, precision matters. Every candidate in our database is tagged with:

– Years of experience in specific ERP systems (Epicor Kinetic, P21, Eclipse, JD Edwards, Infor Syteline, Acumatica, etc.)

– Proficiency scores captured during qualification calls

– Relevant industry verticals such as Medical Device, Aerospace & Defense, or Building Supply Distribution

This gives us a clear skills fingerprint for every candidate, making it easy to shortlist talent for highly specialized requirements.

2. Automated prequalification at scale

We optimized our keywording process and built prequalification forms that go out immediately when a candidate applies. This allows us to quickly separate qualified applicants from general job seekers and focus our time where it counts.

The outcome:

Individually, these enhancements may look small. But together, they create a data-rich ecosystem that dramatically improves filtering, speeds up shortlisting, and strengthens the accuracy of every talent pipeline we deliver.

In a world where volume is increasing and specialization is rising, clean candidate data isn’t just nice to have—it’s a strategic differentiator.

At my first company, we had a strict rule that no candidate could go more than 14 days without an update after their last step in the process. We customized our ATS with a field that showed the number of days since the last communication for each candidate, which we used as a sort function to see who needed an update first. We also added email templates for the most common scenarios, such as rejections, interview invites, or simple status updates like “we’re still reviewing applications.”

With those features, we wanted to streamline and automate parts of our hiring process, improve candidate experience, and strengthen our employer brand. And it worked. Even with a few thousand applications per month, no one was ghosted, and we regularly received praise from candidates for our communication.

In my opinion, the most valuable ATS customization we ever made was building a role-specific hiring workflow template that automatically triggered different stages, assessments, and panel assignments depending on the job family. I believe that a one-size-fits-all pipeline was quietly slowing us down because engineering, sales, and operations all required completely different evaluation rhythms. To be honest, recruiters were spending more time fixing the pipeline than running it.

I still remember one painful week when three engineering candidates slipped through without a technical screen because the default ATS flow didn’t include it. That was the moment I realized our system was working against us. So we created automated templates: engineering roles triggered coding tasks and tech screens, sales roles triggered pitch simulations, and ops roles triggered case studies.

The impact was immediate. Errors dropped, time to stage shortened, and hiring managers finally trusted the process instead of manually double-checking everything. What you and I believe does not matter; the fact is that customizing the ATS to mirror how your team actually hires removes friction, reduces misses, and frees recruiters to focus on relationship building instead of pipeline policing.

One customization we made to our ATS was building a tiered pre-screening workflow that automatically groups applicants into ‘qualified,’ ‘partially qualified,’ and ‘requires review’ based on must-have criteria.

Our pain point was time lost manually sorting high-volume applicants for light-industrial and temp-to-hire roles. By customizing the ATS rules around certifications, shift availability, and distance from the job site, we reduced initial screening time by more than half.

This automation allows us to connect strong candidates with employers faster while ensuring that recruiters spend their time on meaningful conversations instead of repetitive filtering.

We reconfigured our ATS to prioritize people over profiles. Standard ATS platforms are designed to disqualify candidates quickly based on keywords, which was a major pain point for us. We hire coaches, so we need to see beyond a resume to find qualities like empathy and communication. Our old system was filtering out incredible talent simply because their experience didn’t fit a rigid template.

The biggest change was adding a mandatory “Nurture Pathway” field for every promising candidate, even those we reject. This field assigns them to a specific long-term communication track based on their career goals. What we’ve built is essentially a talent community management tool that happens to also process applications. Now, when a role opens, our first step is to engage with our warm network rather than posting a job ad.

There was an early customization that helped our team the most, which was incorporating a tagging and categorizing tool for all of the different hospitality roles (i.e., servers, chefs, front desk, etc.). Prior to this, our team spent a lot of time sorting through and reviewing applicants manually, which made the hiring process take longer and contributed to great candidates being easily overlooked.

Having the tagging and filters to sort candidates specifically based on their experiences, certifications, and role preferences helped our recruiters focus on the most relevant applicants in their review process.

As a result, the duration of the hiring period decreased significantly, and communications/updates with both employers and candidates became significantly easier. It really helped the ATS become more user-friendly and allowed it to become a greater fit for the fast-paced, high-volume nature of hospitality recruiting.

One of the most effective customizations we made to our ATS was fully integrating it with our AI Recruiting Consultant, RiC, which is backed by the expert recruiters of ARC Group. This hybrid model combines predictive analytics and large-scale candidate matching with human oversight, allowing the system to automatically scan over a billion profiles, rank candidates based on job descriptions, and highlight potential fit points.

This customization addressed a key pain point: our previous workflow relied heavily on manual screening, which often missed passive candidates and slowed down the hiring process. By combining AI-driven insights with recruiter evaluation of motivation, communication, and cultural fit, we now surface top talent that would otherwise be invisible, while maintaining the human judgment needed for long-term success.

Evaluating the effectiveness of this AI + human approach shows measurable results: time-to-hire has decreased by nearly 80 percent, candidate quality and fit have improved, and our overall hire rate sits at 93.8 percent. This model proves that automation accelerates recruiting without replacing human expertise, giving us speed, accuracy, and confidence in every hire.

We worked to modify our ATS to embed skill-based assessments at the candidate screening stage. This provided an immediate way to filter technical ability before interviews and was a step toward eliminating the time-wasting behavior of interviewing people whose core skills were not up to par. Automation of this filtering improved hiring efficiency and increased candidate quality while giving the applicants a far more transparent, merit-based experience.

We customized our ATS by integrating Enjoy Mondays to create unique identifier URLs for our LinkedIn job postings. This allowed us to route candidates directly to complete job assessments before any human engagement. The system only flagged candidates who precisely matched our job opportunities, which saved significant time and improved the overall candidate experience. This customization addressed the pain point of spending too much time screening candidates who weren’t the right fit.

We have spent thousands of hours adding AI recruiting agents and interviews to 100 different ATS platforms for high-volume roles (staffing, skilled trades, hourly workers, healthcare, retail, etc.). These are our main takeaways for ATS Customization:

– Create the simplest application form possible (just phone, email, and optional resume with no more than 3 knockout questions). You lose over 10% of your applicants for every page of form fields you add on the frontend of the application. You can easily ask these in automated AI pre-screens.

– Automate the front-end, humanize the back-end: Use AI to handle screening and scheduling so recruiters can focus on relationship-building and the end of the funnel.

– Instant engagement matters: The best candidates don’t wait. Respond within minutes, not days.

– 24/7 availability is a competitive edge: The best candidates already have jobs and apply after hours (65% of applications come in outside 9-5).

– Integrate, don’t bolt on: AI should live inside your ATS workflow, not beside it, because it’s hard to train your whole team on a new tool.

– Voice AI interviews build trust: Natural, conversational interviews feel more personal than chatbots or never hearing back at all.

– Balance automation with empathy: Recruiters should handle the moments that truly require judgment and care.

– Shorten time-to-decision: Allow hiring managers direct access to shortlisted candidate summaries and recordings after the AI interviews. Fast feedback loops keep candidates engaged and reduce ghosting.

The hardest part of hiring media buyers was that resumes don’t tell you much. Someone could list three years at an agency, but I’d have no idea if they actually knew what they were doing. We needed to see their work.

We ended up customizing our ATS to work more like a performance marketing dashboard than an HR database. Before applicants can submit, they have to input their lifetime ad spend managed, average ROAS, and links to their top three campaign case studies. It’s mandatory.

That one change filtered our applicant pool and saved us more time than any other change. People who couldn’t back up their claims just didn’t apply. We also built a custom stage we call the ‘Live Audit’. Top candidates get access to a dummy ad account and record a video walking through growth opportunities they’d pursue. By the time we hop on a first call, we’ve already seen how they think and whether they can actually do the job.

It cut our wasted interview time by at least 50%. Maybe more.