HiOperator unveils QAScout, setting new standards in customer support quality

San Francisco-based HiOperator startup which focuses on customer support technology, is tackling one of the industry’s most persistent challenges today with the launch of QAScout, an AI-powered tool designed to enhance the quality assurance process in customer service. The tool provides brands with real-time insights into customer service agent interactions by automatically scoring every conversation. 

The company’s CEO and founder, Liz Tsai, explained the value proposition of QAScout in an exclusive interview with VentureBeat: “QAScout is a self-service, stand-alone solution that any business can easily onboard and quickly obtain QA insights,” Tsai said. This adaptability signals a growing trend where companies are seeking agile and efficient solutions that integrate seamlessly with existing systems.

Businesses traditionally struggle with the limitations of post-interaction QA, which typically hovers around a 5-10% analysis rate. This lag in feedback creates a reactive, rather than proactive, approach to quality control. “By illuminating the entire category, and using real-time dashboards to see everything that’s happening, businesses can root out potential issues before they become systemic,” Tsai pointed out.

HiOperator’s QAScout provides brands with real-time insights into customer service agent interactions by automatically scoring every conversation. (Image Credit: HiOperator)

The AI edge in customer interaction

QAScout’s introduction is timely, as the demand for automated and AI-powered customer service solutions skyrockets. These solutions are often sought after for their scalability and efficiency, but they come with the challenge of maintaining interaction quality. QAScout addresses this by auto-QAing every ticket, ensuring a comprehensive overview of agent performance and customer satisfaction.

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The AI tool is designed to grade interactions on key parameters like resolution, empathy, tone, and grammar, using sophisticated natural language processing (NLP) models. Tsai elaborated on the fairness and transparency of the system, saying, “By consistently reporting over each interaction, leaders can be flagged to evaluate someone who is poorly performing as per QAScout, and then make a human decision to ensure that the reporting is correct.”

HiOperator’s commitment to a nuanced approach that blends technology with human oversight could be a game-changer for customer support. An example cited by Tsai illustrates the impact: “Hailey, our AI agent, achieved a 20% higher QA score improvement for a D2C apparel retailer by shortening the QA feedback improvement loop.”

Ensuring Transparency and Continuous Improvement

The introduction of QAScout might raise concerns among customer service agents about increased surveillance. However, Tsai believes that the transparency QAScout provides will be mutually beneficial, reinforcing a culture of continuous improvement and acknowledgment of exemplary service.

Looking ahead, HiOperator plans to further integrate QAScout with its suite of automated tools, reinforcing its position as an adaptable, comprehensive CS/CX solution provider. Tsai concluded with a reflection on the future of AI in customer service: “Self-service, targeted solutions like QAScout provide a great way for companies to dip their toes into the AI water to see instant results — and then architect more AI solutions from there.”

HiOperator’s innovative step with QAScout is expected to encourage more companies to adopt AI solutions, not by overhauling their entire systems but by enhancing them with smart, adaptable tools that deliver immediate value and scale with their needs. As customer service interactions become increasingly automated, QAScout appears to be leading the charge toward a more responsive, transparent, and quality-focused future.

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