Pattern matching has been part of artificial intelligence (AI) algorithms for quite some time, but what is pattern matching specifically in AI quality assurance?
Even more to the point … how is pattern matching being used in AI Quality Assurance (AIQA) for contact centers? And in what scenarios should it be the methodology of choice?
What is Pattern Matching in AIQA?
Pattern-matching AI utilizes systems that identify and recognize patterns within vast datasets or input data. This approach relies on statistical algorithms and machine learning techniques to detect recurring patterns, similarities, and anomalies in the data.
In the context of contact center quality assurance, pattern-matching AI evaluates customer interactions by comparing them to predefined patterns or benchmarks. This methodology enables AI systems to consistently assess performance, identify trends, and flag deviations from expected behaviors.
Scenarios Suited for AIQA Based on Pattern Matching
Here are some prime examples of scenarios ideally suited for assessment using pattern matching in AIQA:
- Sentiment Analysis: Pattern-matching AI can analyze customer interactions to detect shifts in sentiment or emotion. By identifying recurring patterns in language and tone, it can gauge customer satisfaction levels and flag instances of dissatisfaction or frustration.
- Script Adherence: You can use pattern-matching AIQA to evaluate agent performance by comparing scripted responses to predefined benchmarks. Pattern-matching AI identifies deviations from established scripts or guidelines, enabling contact centers to ensure consistency and compliance with company standards.
- Keyword Recognition: Pattern matching is a particularly effective method of AIQA when you can identify keywords or phrases indicative of specific customer inquiries or issues. Pattern-matching AI can detect recurring patterns in conversation transcripts, enabling targeted interventions and resolution strategies.
- Fraud Detection: You also can use pattern-matching AI to detect suspicious patterns or behaviors indicative of fraudulent activity in financial transactions or customer interactions. In this case, pattern-matching AI analyzes transaction data and user behaviors to identify anomalies and flag potential fraud cases for investigation.
Best Practices for Utilizing Pattern Matching in AIQA
Implementing a system that uses pattern matching in AIQA requires adherence to these best practices:
- Define Clear Patterns and Benchmarks. You’ll need to establish clear patterns and benchmarks for evaluating customer interactions based on business objectives, regulatory requirements, and customer expectations.
- Regular Updates and Calibration. Plan for regular updates and calibration of pattern-matching algorithms. Your AIQA needs to adapt to evolving needs, trends, and patterns in customer interactions.
- Leverage Machine Learning Techniques. Enhance pattern recognition capabilities by leveraging machine learning techniques to refine algorithms and improve accuracy over time.
- Human Oversight and Intervention. As good as AI can be, you still need to maintain human oversight to validate AI-generated assessments, address edge cases, and ensure fairness and accuracy in evaluations.
Benefits of Quality Assurance Employing Pattern Matching AI
Embracing pattern-matching methodology in AIQA yields many benefits for your contact center. Some of these benefits include:
- Efficiency and Scalability: Pattern matching AI enables efficient and scalable evaluation of customer interactions, allowing your contact center to effectively handle large volumes.
- Consistent Performance Evaluation: With pattern-matching AIQA in place, you receive consistent and standardized evaluations of customer interactions. This minimizes variability and ensures compliance with predefined patterns and benchmarks.
- Early Detection of Issues: Pattern matching AI lets you detect trends and anomalies early on, enabling you to take proactive measures to enhance customer satisfaction and loyalty.
Implementing an AIQA program grounded in pattern matching can elevate performance, enhance compliance, and deliver superior customer experiences in your contact center.
However, pattern-matching AI alone may not be able to give you all the answers you need.
ARC’s unique solution is based on human-driven AI quality assurance, which adds a human element to the already unique capabilities of pattern matching, combined with an additional AI component, logical reasoning.
We invite you to book a meeting with the experts at ARC to discuss in further detail what pattern matching, logical reasoning, and human-driven AIQA could do for your contact center.
To get in touch, use this form to book a call or you can reach us directly at 1-866-798-0488. If you prefer email, you can contact us at info@arcqs.com.