Quality assurance is a fundamental part of contact center operations, whether it is to enhance agent performance, ensure compliance and business performance, or improve the customer experience (CX).
A company’s most valuable assets and data source are their customer interactions. Contact centers are in a unique position as they have access to this window into the CX. Deriving value from this data lies in how companies analyze and harness the wealth of insights to drive operational performance.
Data analytics, business intelligence, and sentiment analysis provide CX professionals with greater insights to identify patterns and issues that enable them to place focus on making the improvements to impact overall customer satisfaction.
Quality Management Transformation
Artificial intelligence (AI), text and speech analytics, machine learning (ML) and natural language processing (NLP) are all hot topics and have been the main driver behind the quality management transformation in recent years.
Although automation and digitalization has changed the way companies interact with their customers, human assisted channels are still an essential function across contact centers with phone support remaining the primary touchpoint. Inefficiencies and resource constraints across quality assurance (QA) programs are the main obstacles for contact centers to improve performance and optimize the customer experience. This is where technology and big data comes into play.
The Power of Data
AI and ML technology is not here to replace the human touch, but the combination will maximize the benefits by shifting the focus from identifying issues to fixing them. AI-powered quality monitoring gives access to an amplified level of BI, providing a holistic approach to understanding the overall customer journey, as well as a supplement for human QA teams to improve accuracy and redistribute resources to take the company to a new level of efficiency.
Imagine if you could gather data about every customer touch! The power of AI makes it possible to work on large datasets rather than samples, generating representative and accurate data in a fraction of the time. The enhanced level of data provides organizations with analysis right down to the individual agent level.
Quality monitoring with AI capabilities will boost
It’s not enough to analyze what customers say – but also how it is conveyed!
Gathering customer feedback by listening to hours of calls or conducting surveys that have limited responses may not accurately represent your customer’s true feelings. However, by using sentiment scores in conjunction with surveys, you can accurately pinpoint where your customers are dissatisfied and most importantly…act on it!
Sentiment analysis is a voice technology that uses machine learning algorithms to automatically monitor all conversations and determine whether a customer is positive, negative, or neutral, by dictating and incorporating tone, feeling and emotion. To identify the sentiment, the machine looks at what’s hidden behind the words, such as pauses and breaks, pace, and agitation.
Measuring customer sentiment provides insights into the quality of conversations and customer satisfaction, which will not only enable organizations to improve internal processes, but also offer their customers the consistent, high-standard service experience they expect. The increased volume of data helps you understand and determine what your customers need and detect opportunities for improvement.
Holistic approach to Quality Assurance
An added benefit of sentiment analysis technology is a way to more accurately understand how your customers feel about your brand and their experience. This helps uncover issues and monitor agent performance to both improve the employee experience and strengthen customer relationships. Correlating sentiment score with other contact center KPIs, e.g., average handle time (AHT) and first call resolution (FCR), can provide guidance to supervisors and managers in terms of identifying training and coaching needs to empower agents.
This holistic approach to the customer journey provides a huge competitive advantage and allows organizations to monitor customer opinions and even intervene where and when possible. Identifying patterns and keywords that occur frequently enables organizations to improve internal processes and policies so that customer issues can be addressed, and quality services ensured.
Shifting from Reactive to Proactive
Customer sentiment can have a direct impact on customer satisfaction and loyalty, by enabling organizations to shift from a reactive to a proactive approach. Let’s say there are customers that had a bad experience and indicate leaving, the customer success department can proactively contact the customers before they make their final decision to leave. Pivoting the CX and fixing issues like this is a top priority for CX organizations.
The insights obtained from sentiment analysis allow organizations to prioritize issues by urgency and take action to stay ahead of the issue. The information can easily be passed on to the appropriate departments that contribute to developing strategies for customers, allowing them to respond quickly and effectively. Customers who have had an issue that was addressed promptly are often more loyal than those who never encounter any problems. This has an immense impact on quality, customer success, and the evolution of the contact center.
The Bottom Line – Get to know your customers
Go beyond numerical scores, take a deep dive, and obtain more consistent results. The more data, the more knowledge, the better CX. Automation has transformed CX expectations and organizations now have access to actionable insights about the entire customer journey. Quality programs with an AI boost are growing more accurate, more efficient, and more relevant – allowing businesses to enhance agent performance, operational performance and the overall CX!
Measure what matters most to your customers
– Digitally, Automatically, Intelligently
RevealCX Boost is designed to generate representative, accurate data in a fraction of the time. It is designed with purpose and intent of industry experts who know the common pitfalls of quality assurance and how to avoid them. The platform focuses on deep data insights about customer behavior and needs while providing robust reporting that gives an accurate view of performance.
Learn more about RevealCX Boost here.