AI QA Software vs. Human QA: Who Does a Better Job at Monitoring Sales Calls?

In this blog, we’ll explore the differences between AI QA software and human QA in the context of sales call monitoring, the advantages of each, and how businesses can benefit from combining both approaches for optimal results.

What is Call Monitoring, Who is Responsible for It, and Why Is It Important?

Call monitoring refers to the process of evaluating and assessing phone conversations between sales representatives and customers. The goal is to ensure that sales calls meet the company’s quality standards, align with scripts, and lead to successful outcomes. Call monitoring helps identify potential issues, gauge customer satisfaction, and improve the overall performance of sales teams.

Who is Responsible for Call Monitoring?

Call monitoring is typically the responsibility of a Quality Assurance (QA) team or a Sales Manager, depending on the size of the organization. QA specialists are often tasked with listening to recorded calls and evaluating them based on set criteria. In some cases, sales managers may also monitor calls to provide direct feedback and coaching to their team.

In larger organizations, quality assurance automation tools or AI-based systems may be used to assist with the process, helping to scale the monitoring efforts and provide real-time insights.

Why is Call Monitoring Important?

1. Improves Sales Performance: By regularly monitoring sales calls, businesses can identify areas for improvement in communication, product knowledge, and objection handling. This helps sales reps refine their approach and close more deals.
2. Enhances Customer Satisfaction: Monitoring calls ensures that sales reps are adhering to customer service standards, handling objections appropriately, and providing a positive experience for customers.
3. Ensures Compliance: In many industries, ensuring compliance with legal or regulatory standards is crucial. Call monitoring helps verify that sales reps follow company policies and adhere to regulatory guidelines.
4. Provides Valuable Insights: Call monitoring allows companies to gain insights into customer pain points, objections, and needs, which can be used to refine sales strategies and tailor future conversations

How AI is Transforming Call Monitoring and Its Role in the Larger Quality Assurance Process

As sales teams continue to grow and customer interactions become more complex, AI in call monitoring has become an integral part of the broader quality assurance process. AI-powered quality assurance tools are revolutionizing how businesses assess and monitor sales calls, making the process faster, more efficient, and data-driven.

AI’s Role in Transforming Call Monitoring

AI technology is capable of analyzing vast amounts of data in real-time, providing insights that are difficult or time-consuming for humans to extract. Here’s how AI is transforming sales call monitoring:

• Real-Time Feedback: Traditional call monitoring often relies on reviewing recorded calls after the fact. With AI call monitoring, businesses can gain real-time insights into calls as they happen. AI can detect problems like tone inconsistency, script deviation, or missed opportunities during the conversation, and immediately notify the sales rep or supervisor with recommendations. This enables immediate corrections, leading to improved customer interactions and faster resolution of issues.  
• Automated Call Analysis: Instead of manually reviewing each call, AI tools can automatically analyze a large volume of calls, focusing on key aspects like script adherence, product knowledge, and customer sentiment. By automating this process, businesses can scale their call monitoring efforts without the need to hire additional QA specialists.  
• Sentiment and Emotion Detection: AI-powered tools can detect customer emotions and sentiment during the call by analyzing speech patterns, tone, and pace of conversation. This allows AI systems to understand if a customer is frustrated, satisfied, or disengaged, giving sales teams deeper insights into how the conversation is progressing and whether additional actions are needed.  
• Improved Accuracy: One of the key benefits of AI call monitoring is its accuracy. AI can assess thousands of calls using the same consistent criteria, reducing the potential for human error and bias. It provides objective, data-backed insights that help sales teams improve their performance over time.

AI’s Place in the Larger Quality Assurance Process

While AI call monitoring is a game-changer on its own, it fits into a larger quality assurance framework that includes both human oversight and automated systems. Here’s how AI complements the overall quality assurance in sales:

• Seamless Integration: AI-based tools can seamlessly integrate with other quality assurance automation tools and CRMs, making it easy to track performance, manage follow-ups, and identify long-term trends. This ensures that call monitoring is part of a larger effort to enhance the quality of customer interactions, from initial contact to post-call follow-ups.  
• Actionable Insights for Coaching: While AI call monitoring offers detailed, objective data, human quality assurance specialists can use these insights to coach sales reps. The combination of AI-driven data and human feedback ensures that sales reps get not only quantitative feedback (e.g., call performance metrics) but also qualitative advice that can help them build better rapport with customers and improve their soft skills.  
• Continuous Improvement: AI in quality assurance helps to build a culture of continuous improvement within sales teams. AI tools can monitor trends over time, identifying recurring issues in sales calls, and pinpointing areas where additional training is needed. This ensures that sales teams are always evolving and refining their approach to customer interactions.  
• Scalability: As sales teams grow, AI-powered tools help maintain high standards of quality assurance without overwhelming managers or QA specialists. With AI handling large volumes of calls, human teams can focus on more strategic, higher-level tasks like advanced coaching and process improvements.

What is Quality Assurance in Sales?

Before diving into the comparison, it’s essential to understand what quality assurance (QA) means in the context of sales. Quality assurance in sales involves evaluating sales calls to ensure they meet predetermined standards, such as customer satisfaction, compliance, and effective communication. It helps sales managers and teams identify areas for improvement, coach representatives, and ensure that customers have a positive experience.

QA for sales teams usually involves assessing key factors such as:

• Call adherence to scripts
• Sales reps’ ability to handle objections
• Tone of voice and professionalism
• Accuracy in providing product or service information
• Compliance with legal and regulatory requirements

There are two primary ways to conduct this quality monitoring: human QA and AI QA software.

Human Quality Assurance: The Traditional Approach

Human QA has been the traditional method of monitoring sales calls. With this approach, a quality assurance specialist listens to a recorded call, evaluates the performance of the sales rep, and provides feedback. Let’s look at the strengths and weaknesses of human call monitoring:

Strengths of Human QA:

• Contextual Understanding: Humans have the ability to understand nuanced tones, emotions, and subtleties that AI might miss. A skilled QA specialist can pick up on underlying sentiments, customer satisfaction, and even subtle cues from the conversation that could indicate a deeper issue.
• Personalized Feedback: Human QA specialists can provide personalized, tailored feedback to sales representatives. They can coach on soft skills, such as rapport-building or empathy, which are harder to measure through AI.
• Experience-Driven Insights: Experienced QA specialists often bring a wealth of industry-specific knowledge, which can help them identify key opportunities for improvement that automated systems may not recognize.

Weaknesses of Human QA:

• Time-Consuming: Listening to calls manually is a labor-intensive process. QA specialists can only review a limited number of calls each day, making it difficult to scale the quality assurance process across large teams.
• Inconsistent Evaluation: Human QA is prone to subjectivity. Different QA specialists might have varying standards or interpretations, which can result in inconsistent feedback for sales reps.
• Limited Scalability: As your sales team grows, manually reviewing every call becomes increasingly impractical. Human QA struggles to keep up with the volume of calls in large sales organizations.

AI QA Software: The Future of Sales Call Monitoring

With the advancement of AI in quality assurance, businesses now have access to powerful quality assurance automation tools that can monitor sales calls more efficiently and at scale. AI sales calling and monitoring solutions leverage machine learning and natural language processing (NLP) to analyze calls and provide insights automatically. Let’s explore the strengths and weaknesses of AI call monitoring:

Strengths of AI QA Software:

• Scalability and Speed: Automated call monitoring with AI can process hundreds or even thousands of calls in a fraction of the time it would take a human to listen to them. This scalability ensures that every call can be monitored, regardless of the size of the team.
• Objective Analysis: Unlike humans, AI call monitoring provides consistent, objective feedback. AI evaluates calls based on predefined parameters, ensuring that every call is assessed using the same criteria without personal bias.
• Real-Time Insights: AI systems can offer real-time feedback during the call, helping sales reps adjust their approach immediately. For example, if a rep’s tone of voice is too aggressive, the AI can flag this during the conversation and provide recommendations for improvement.
• Comprehensive Analysis: Quality assurance AI can analyze not just the script adherence but also emotions, sentiment, word choice, and other factors. This can provide a comprehensive view of how well a sales call is progressing.
• Cost-Efficiency: Once implemented, AI quality assurance systems are far more cost-effective in the long run than employing a large team of QA specialists. This allows businesses to allocate resources to other areas that need attention.

Weaknesses of AI QA Software:

• Lack of Emotional Intelligence: While AI is great at analyzing speech patterns and sentiment, it lacks the human ability to fully understand emotions or pick up on non-verbal cues (such as body language) that could influence the success of a sales call.
• Dependence on Data Quality: AI is only as good as the data it’s trained on. If the AI is not properly trained or if it lacks the right data, its analysis could be inaccurate or incomplete.
• Limited Soft Skills Analysis: While AI can assess the technical aspects of a sales call, such as script adherence or product knowledge, it can’t fully evaluate soft skills like empathy, rapport-building, or the ability to establish trust.

AI QA Software vs. Human QA: Which Does a Better Job?

Both human QA and AI QA software have their strengths and weaknesses, and which one is better for monitoring sales calls depends on your goals and needs.

• For Scalability: AI in quality assurance takes the lead. Automated call monitoring systems can review a large volume of calls quickly and accurately, making them ideal for high-volume sales teams.
• For Personalization: When it comes to providing tailored, empathetic feedback, human QA is still superior. Sales reps need human guidance to improve interpersonal skills, and human experts can offer personalized coaching based on context.
• For Objectivity: AI call monitoring wins here. It provides consistent, data-driven analysis without the risk of personal bias or inconsistency.
• For Emotional Intelligence: Human QA excels in this area. Understanding tone, emotion, and non-verbal cues is something that a trained QA specialist can interpret far better than any AI tool.

The Best of Both Worlds: Combining AI and Human QA

The most effective solution may not be choosing between AI sales calling and monitoring or human QA, but rather integrating both. By using AI quality assurance tools for automated call monitoring and leveraging human QA for personalized feedback and emotional intelligence, businesses can benefit from the strengths of both methods.

This hybrid approach allows sales teams to scale their quality assurance efforts while still receiving tailored, empathetic coaching that fosters growth and development.

Salesken offers a powerful solution for automating call monitoring and quality assurance, significantly reducing manual effort while enhancing efficiency. With its AI-driven capabilities, Salesken can automatically analyze sales calls, evaluate performance, and provide real-time feedback, saving valuable time and resources.  

By minimizing the need for manual reviews, Salesken enables sales teams to focus on improving performance, coaching reps, and driving better customer interactions, ultimately boosting overall productivity and business success.Book a demo with Salesken today!