But as the company expanded and demand for customer support grew, maintaining consistent, high-quality service across multiple contact centers became a challenge. Feedback was slow to reach customer support agents due to the limited number of evaluations—just one to four per month.
“This delay meant that agents could be making the same mistakes repeatedly, leading to a cycle where we couldn’t address the errors in time, which ultimately hurt our quality,” says VP of Customer Operations Ryan Moore.
Growing at 30–40% annually, DailyPay needed a more scalable solution. Its existing evaluation process wasn’t enough to keep pace with this level of growth.
“And we couldn’t keep hiring additional [quality assurance] QA analysts as we expanded,” says Sigmond Varga, Senior Manager – Shared Services.
Transforming QA
After exploring several options, DailyPay adopted the Observe.AI Conversation Intelligence Platform.
The platform’s Auto QA has become the backbone of the company’s new approach to QA. Instead of manually grading a small portion of calls, DailyPay automated its evaluation process, enabling it to gain insights into every customer interaction.
This shift has streamlined QA operations and redefined the role of QA analysts within the company. Previously, they only graded calls and provided feedback. Now, they analyze data, spot trends, and address needs at DailyPay’s outsourced contact centers.
From Grading to Coaching
Today, QA analysts are seen as coaching resources who help teams improve their performance, rather than punitive individuals whose job it is to catch mistakes.
“This change has encouraged a more collaborative environment, where frontline supervisors regularly turn to the QA team for guidance on performance issues,” says Varga.
By moving from weekly to daily coaching, new agents have found their footing more quickly. This proactive coaching approach has been especially helpful for new hires at the outsourced contact centers. With quicker feedback, agents can now make adjustments in real time, accelerating their progress.
This new approach has led to notable improvements. DailyPay has seen service quality scores rise by 8.5% and customer satisfaction scores increase by 22.3%.
Likewise, the enhanced efficiency has delivered cost savings of more than $2 million by streamlining contact center operations and reducing the need for additional QA staff.
Insights That Drive Results
A standout feature of the Observe.AI platform is ‘Moments,’ which enables DailyPay to monitor specific agent behaviors and flags key instances during customer interactions. This capability has proven crucial in identifying issues that undermine customer experience.
For example, Moments tracks instances where agents refer customers back to their employers—a practice that can frustrate callers. By capturing this data, DailyPay can directly address the issue, improving agent responses and customer satisfaction.
Moore adds that the modular Observe.AI platform “has become invaluable not only for understanding customer interactions, but also for gaining marketing and product insights.”
Improving First Contact Success
The kind of visibility provided by Moments has also helped DailyPay tackle another challenge—first contact resolution (FCR).
By analyzing the communication gaps in customer calls, the company was able to identify inefficiencies that prevented issues from being resolved during the first interaction. This analysis led to a 4–5% improvement in FCR for several teams.
As Moore shares, “FCR was a major issue affecting a substantial percentage of our calls. These findings empowered us to push for necessary changes and better align our internal processes with user needs.”
Expanding AI’s Role
DailyPay’s partnership with Observe.AI doesn’t stop at QA. The company is now using Summarization AI to simplify and speed up notetaking, reducing the time agents spend writing summaries by 40–60 seconds per call. This boosts productivity while easing the workload for agents.
Looking ahead, DailyPay is excited about the potential of predictive AI models to proactively coach agents and anticipate customer needs based on previous interactions.
“We aim to provide better insights across the organization by extending Observe.AI’s use to other areas, such as card servicing and client success teams,” says Varga.
Discover how DailyPay transformed its QA operations with Observe.AI. Read the full customer success story.
