With conversation intelligence and AI-powered coaching, the company lands more American workers jobs.
The company's mission is to deliver a stronger workforce in areas like manufacturing, logistics, transportation, and more. Placing 400,000 associates annually to 12,000+ companies, the company's success hinges on the quality of conversations its coordinators have with candidates and their ability to remain productive. So gaining insight into their 4 million yearly voice calls, and providing higher-quality feedback and tailored coaching programs is mission-critical.
The company set out to solve three distinct challenges in building their agent-driven quality program. In doing so, their program fosters better coordinators, while also providing a deeper understanding of strengths and shortcomings across the organization.
Analysts were only reviewing just 2-4 calls per agent per month, using subjective scoring and lengthy, multipage QA forms. They wanted to provide higher quality feedback for agents and score calls in a more efficient, objective way.
Conversation intelligence can unearth hidden inefficiencies that hurt organization goals; in this case, placing workers in jobs. Analyzing thousands of interactions per month, the company wanted to extract insights at scale to better understand areas of improvement. They'd later learn this was a million-dollar opportunity to improve.
With a high volume of calls and large number of agents, training velocity is a key piece of highly efficient contact centers. The wealth of insights and analysis provided by contact center AI, the company wanted to train the right people on the right topics as quickly as possible.
“For me, the best-in-class call center is one that is not run from the top down. It is interactive, at the agent level, driven call center. The agents are your best place to find what you’re doing well and what you’re not.”
Turning Inefficiencies Into Revenue
Using Observe.AI, the company discovered that “calendar full” was referenced on 30% of calls. Looking at it closer, they realized that they were missing out on opportunities to interview nearly 2,000 more candidates each week due to inefficiencies in staffing and calendaring. When the team quantified this inefficiency, they learned it was costing their contact center $34M in revenue loss each year.
The company then took that insight to senior leadership who fixed the problem and are now eager to do more with voice insights in the future.
“As contact center people, we tend to do what we’ve always done. But what’s exciting about Observe.AI is that we can change the way we’re coaching and re-write our quality cards. We can move away from check-boxes and focus on real skill development. Using voice analytics helps us change behavior faster.”
Through Observe.AI, the company quality checks 10x more voice calls, covering hundreds of calls per coordinator per year. This solves the problem of subjective QA processes and creates more accurate insights per agent and across the entire organization. Additionally, it frees up analyst bandwidth to focus on more strategic tasks.
With a wealth of performance insights and analysis, they created the foundation for building a more relevant, more targeted coaching program for their coordinators. This includes identifying negative customer interactions - supervisor escalations, negative sentiment, compliance breaches - and being able to address them with training tailored to individual coordinators.
The company is reimaging what a contact center of the future should look like. By using AI-based technologies to better understand agent and organizational performance, they are creating new training programs, and turning agents into their best possible brand representatives.
“With Observe.AI we can look at where we can reduce average handle time, where can we create efficiencies, where can we add things to our process that may not exist. It’s a full, interactive tool for us to find our shortcomings, what we’re doing well, what we need to put into place, and in the future doing QA unlike any other call center.”
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