Happy customers are a foundation for any business and business leaders understand that customer feedback provides the ability for the business to provide an exceptional customer experience.  However, for years, business leaders have struggled to gain meaningful insights from customer-initiated contacts. Questions have been difficult to answer due to the unstructured nature and sheer volume of the data –

  • What is the general sentiment of my customers?
  • What are my customer’s pain points and what are the root causes for their contacts?
  • Why did customer contacts increase today or yesterday?
  • Are there specific agents that need training to reduce customer frustrations during a contact or to reduce escalations?

By harnessing the power of big data, data science and natural language processing, these questions cannot only be answered, but answered on a near real time basis.  By having access to this vital information, business leaders can take proactive measures to make changes and improvements before it impacts the customer experience, increases the risk of getting a bad reputation and drives a decline in business performance, decreasing customer retention and revenue.

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Leveraging contact center analytics allows business leaders to view such things as:

  • Customer Sentiment: For each contact, a numerical score is generated based on the sentiment of the customer, which provides a real time view of the customer base and provides the ability to drill down into the data to determine if there are segments of customers that are sources of poor sentiment.
  • Sources of Customer Contacts: Each contact is classified into a specific topic or topics. This allows business leaders to better understand why customers are making contacts.  For example, if a majority of calls are related to billing issues, are there opportunities to automate processes or provide additional information online or through the IVR to reduce agent contacts, thus reducing customer frustration and decreasing costly contact time with agents?
  • Contact Duration: Call duration can be viewed at a more granular level to allow business leaders to view contacts that dramatically increase resolution time. Is there something common among these types of contacts that provide an opportunity to change processes to reduce contact duration?
  • Agent Quality: Using a combination of metrics, agent quality scores can be generated for each contact. Are there agents that can benefit from increased training?  Are there specific contact types that are driving lower agent quality scores?  Introducing an agent quality score gives business leaders more insight into agent performance and allows them to make proactive changes to address any agent issues.

Implementing a data-driven approach into contact centers can be challenging for organizations due to volume, variety and velocity of data produced through contact centers.  Additionally, with the rapid advances in machine learning, natural language processing and big data technologies, it is difficult to determine which technologies and data to leverage to generate the greatest ROI on contact center analytics projects while ensuring additional incremental improvements can be realized as technology advances.

Which metrics should we focus on to increase customer retention and revenue while decreasing operational costs?

Which technology stack should be utilized to ensure these metrics are available in a time-frame that will allow for quick operational decision making?

How do we aggregate data from various sources (voice calls, emails, online feedback forms, online chats) to ensure that we have a holistic view of all customer contacts?

How do we associate the metrics with our customer segments to ensure that we are providing a great customer experience across all of our customer segments?

These are just a few of the pressing questions that must be answered as a part of a contact center analytics project.

 

Contact us today to find out the answers to these questions so that you can advance down a path that leads to a better customer experience and greater contact center performance!


 

 


 

Blake Lassiter, Solutions Architect

Blake Lassiter, Solutions Architect

Blake brings over fifteen years of experience in software development and project, program and product management to Syntelli. In his current role as Solutions Architect, Blake assists the company in sales and services by architecting and developing data science and big data solutions to meet diverse client needs across a variety of channels. 

Blake resides in Birmingham, Alabama and when he isn’t developing and implementing solutions for clients, he enjoys playing guitar and spending quality time with friends and family.