As the use of Artificial Intelligence tools continues to grow in the Quality Assurance world of CX; organizations wonder if all-in AI tools can provide greater customer satisfaction, deliver stronger measurable results, and maximize efficiency more so than manual QA programs.
To determine if there is value in adding AI to your QA program, organizations must clearly understand the value of their manual QA program and use it as a benchmark to measure the effectiveness of an AI-based QA program. Rather than solely focusing on the cost factor, organizations should also compare the quality and accuracy of their manual QA program to the quality and accuracy of an AI-based QA program.
In this blog, we’ll reflect on three common patterns shared by Vasu Prathipati, CEO of MaestroQA, and uncover the critical role that manual QA programs play in streamlining processes, reducing costs, and improving customer satisfaction. By understanding these patterns, you can determine if manual QA programs are best utilized to improve customer satisfaction and deliver more actionable results.
“One of the common patterns that I noticed while researching why our customers come to us and what problems they were facing in their world was around understanding and measuring agent performance,” said Prathipati. "Our customers found that while productivity metrics can track how much work an agent does, they don't always capture the quality of that work, or they found that using productivity metrics to incentivize behavior could be problematic.
Furthermore, Customer Satisfaction (CSAT) surveys were not always reliable indicators of high-quality customer service or support performance because they didn’t always consider the process involved.”
For example, “say you have 100 agents that support 40,000 customers per person, and you’re spending $4,000,000 on your support team; what would happen if a QA metric for agents didn't exist, or what would happen if you add one?”
Understanding and measuring agent performance accurately is mission-critical. We have heard stories of customers letting go of the highest-performing people because leadership was using metrics that didn’t reflect people’s work accurately!
The second pattern that Prathipati noticed in his research on why customers come to MaestroQA is that they want a new way to manage their BPOs or outsourced call centers. “Sometimes customers don't have a quality program at all, but they want a QA program to manage their BPOs, or sometimes the BPO has their own quality program, but customers are finding that the BPOs quality scores are all at 97 to 98% score, but that’s not the real reality, so they want to take more control of the QA program internally so that they can hold their BPOs accountable to these quality metrics. Imagine that you have a BPO and they have 200 agents there that are paid $20K per year; that’s $4,000,000 per year to that BPO. What would happen if a QA program didn't exist to manage that BPO, or if you add one?”
Prathipati suggested another way of looking at it: “What if your manager didn't have 1:1 meetings with you, or if you’re a manager and didn't have 1:1’s with your direct reports? How would that impact the productivity and work quality of the team? The same concept applies to managing and optimizing your BPO agents.
How are some of the world’s industry-leading companies leveraging MaestroQA to manage their BPOs?
One of the fastest-growing direct-to-consumer underwear and apparel companies has a fully outsourced support team but utilizes MaestroQA for its QA program. The result: a 99% CSAT and their BPO agents are bonused based on QA performance.
Here’s another one– a leading food delivery app made training and development for outsourced agents a central part of their BPO partnership strategy. By leveraging MaestroQA, they created a detailed training and agent development plan that gives BPO agents the skills and support they need to provide excellent customer experiences. They even implemented a rigorous onboarding certification program required for all new BPO agents to complete. “We’ll guide teammates through to retrieve that certification,” said the company’s Quality Assurance Lead.
Lastly, Prathipati revealed that people come to MaestroQA because they want to invest in a quality program that allows them to do deeper root cause analysis. “We hear from our customers that their CSAT metrics are down, but they don't know why. Or they notice that AHT is going up, and they don't know why, or they have a goal to reduce contact volume, but they don't know what's really driving an increase in these contact volumes, or they’re seeing a spike in escalations but don’t understand why they’re seeing this spike. Is it because they have new agents? If so, why do they have new agents? Are there retention issues?” Customers use manual QA programs to dive deep into these issues and complete a true root cause analysis.
“A manual QA program and a good QA scorecard,” said Prathipati, “is a great way to do these deep dives.”
During another research call that Prathipati conducted with a top-tier on-demand provider, the Senior Customer Service Operations Manager said: “my QA analysts are in the MaestroQA tool all day. I get feedback that they don’t have to listen to a call more than once because they can go back and read a section they had a question about. So, I'd be pretty confident that's saving them time. I like that with MaestroQA, we're leveraging data from multiple sources to build rules showing insights about the business.”
In the end, Prathipati said, “we’ve talked about three common patterns and the challenges that manual QA programs help organizations overcome, so when you’re thinking about layering in AI, it’s important not to look at your QA program just as a cost, but to look at the current value that it’s delivering. So much so, “that when you invest in a technology such as AI, is it clearing that bar? It needs to be delivering more value than your current quality program. So it’s a one plus one equals three situation.”
If you would like to learn more about MaestroQA, request a demo today.