Strengthen Your Contact Center with Speech Analytics + Traditional QM
Speech Analytics continues to make headlines as a powerful tool that drives results in the contact center. With its ability to process 100% of recorded customer interactions, Speech Analytics uses Artificial Intelligence to parse recorded conversations. This breaks the speech into small chunks for analysis and reveals, at a macro level, areas that are working well for the contact center and areas that need improvement.
To complement Speech Analytics, traditional Quality Management (QM) allows for a more personalized, micro view of specific interactions. Both processes are needed for contact center growth. See how each delivers unique results for your contact center.
Speech Analytics Results Enhances Insights
As the Speech Analytics engine analyzes recorded interactions, it searches for specific speech patterns. However, the engine must be “taught” the phrases and keywords that are meaningful for your contact center. Once the key phrases and words are defined, the engine heads to work, finding just the right data that is critical to your business.
For instance, let’s say you need to ensure your contact center complies with industry regulations. Adding specific statements or derivatives of them to the Speech Analytics engine, such as, “This call may be recorded,” or, “Do I have permission to access your policy information?” teaches the engine how to evaluate recordings for this key performance metric.
Speech Analytics also considers customer sentiment, such as the tone of the caller’s voice, to help you understand the customer experience. Between detailed analysis and customer sentiment, Speech Analytics can help your business gain knowledge and understanding that would previously go unnoticed. These are just a few examples of how companies achieve ROI based on Speech Analytics:
- Coach Your Agents – Increase agent coaching and target opportunities for growth while reducing the burden on quality assurance staff
- Find Processes to Improve – Pinpoint areas to improve contact center operations and monitor regulatory compliance to avoid fines or penalties
- Discover Sales Techniques that Resonate – Analyze sales performance to find key metrics that drive sales, set agent goals, and develop sales training
- Reveal Customer Sentiment – Extract valuable customer feedback about products and services, improve CSAT or NPS scores, and detect causes of customer churn
Speech Analytics + Traditional Quality Management
Speech Analytics works best when paired with a traditional QM process. Although Speech Analytics provides insight for contact centers to know all that is happening during the thousands of interactions that occur each day, there are soft skill techniques and procedural issues that can’t always be assessed without a trained ear. This is where supervisors offer great value since they are able to focus on the subtleties of an agent’s performance.
Supervisors are experts on agent progress in terms of training, coaching, skillset, and personality. They understand their staff far better than software, and their evaluations are most likely more precise. For instance, it would be difficult for a Speech Analytics engine to answer these questions:
- Did the agent effectively establish rapport with the customer?
- Did the agent skillfully ask probing questions?
- Was the agent persistent in overcoming sales objections?
A supervisor can better understand the answers to these questions using a traditional quality management scoring system. They may also choose to score questions based on a company-developed rubric, noting how an agent can adjust to better serve customers. Although these evaluations require more time from a supervisor, when used strategically, the results provide a human touch not possible with software alone.
A Winning Combination Delivers Results
To optimize your contact center and bolster the customer experience, implementing Speech Analytics with traditional QA is the best solution.
While traditional QM focuses on the subtle and often high value skills, Speech Analytics focuses on fast assessment of the breadth of interactions. In other words, supervisors are more capable of answering intricate questions (and enhancing agent skills), while Speech Analytics is preferred when it comes to measuring interaction occurrences. The key advantage of using Speech Analytics technology is that it can collect data from all calls, and use that data to quickly spot correlations, trends, and anomalies.
If you’re considering a Speech Analytics solution or just curious about the benefits it might bring to your contact center, download the white paper, “Blending Speech Analytics with Traditional Quality Management”. Then give the DVS team a call and explore your options for implementing a cost-effective Speech Analytics solution.