When looking for ways to upgrade your contact center, you face an onslaught of industry jargon. Do you need a Conversation Intelligence or Conversation Analytics platform? If you wanted to analyze your call data, should you look for a Speech or Voice Analytics solution? As new contact center solutions flood the market, what do these labels mean?
At MiaRec, we have helped retailers, financial institutions, government agencies, and more find the right tools to transform their contact centers. We have seen firsthand how difficult it can be to keep up with industry terminology, especially as definitions continue to evolve over time.
In this article, we will review multiple industry terms and their relationships to each other. Discover the differences between Conversation Intelligence and Conversation Analytics platforms. Learn how Speech and Voice Analytics solutions work with Conversation Intelligence platforms to benefit your contact center. By the end of this article, you will have the lingo you need to target your contact center’s pain points.
As you are looking for ways to make the most of your call data, you discover Voice and Speech Analytics solutions. What is the difference between the two? While there are features that differentiate Speech and Voice Analytics, industry professionals often use these terms interchangeably.
Voice Analytics has typically referred to any solution analyzing calls with tonality and pitch to determine customer sentiment. Meanwhile, Speech Analytics solutions used AI-driven Keyword Extraction, Topic Analysis, and more. However, as both Voice and Speech Analytics solutions adopt new features such as Agent Assist or Auto Call Summary, traditional definitions are becoming less applicable. That is why more people refer to Speech and Voice Analytics interchangeably.
Voice and Speech Analytics solutions are a great way to transform how your contact center utilizes data. They promise to analyze call recordings or live calls to extract insights that you can use to drive business decisions, improve agent workflows, and more. Popular Voice and Speech Analytics vendors include MiaRec, Verint, and NICE CXone.
If Speech and Voice Analytics are used interchangeably, then are Conversational Intelligence and Conversational Analytics platforms the same as well? In most cases, Conversational Intelligence and Conversational Analytics are also used interchangeably. However, Conversational Analytics can sometimes refer to a solution offering additional omnichannel capabilities.
Conversation Intelligence and Conversational Analytics solutions both have features such as Topics Analytics, Sentiment Analysis, Keyword Spotting, and more.
Conversation Intelligence platforms prioritize analyzing transcribed call recordings, while Conversational Analytics solutions could include additional omnichannel communication features such as chatbots. This makes Conversation Analytics solutions such as CallMiner better for contact centers looking to provide omnichannel experiences. Meanwhile, using Conversation Intelligence solutions such as MiaRec or Observe.AI is a great way to tackle your data silos.
Both Conversation Intelligence and Conversation Analytics can turn call transcripts into actionable insights. Because of their overlapping similarities, many people conflate the two and lump them into one terminology.
MiaRec is a Conversation Intelligence platform that provides Voice Analytics solutions. We will be using MiaRec Sentiment Analysis to help illustrate the relationship between Voice Analytics and Conversation Intelligence.
Most Voice Analytics solutions offer Sentiment Analysis, which tells you whether a call has gone positively or negatively. But what can you do with this information?
MiaRec’s Conversation Intelligence platform takes the data that Sentiment Analysis has analyzed and turns it into meaningful insights and trends.
Conversation Intelligence tracks analyzed data over time and organizes it by different criteria such as by call dates, agents, and more. It presents data-driven insights in an easy-to-understand visual format. You can use these insights to track call script efficiency, customer feedback, product reviews, and more.
You now know what some of the most popular terms in the market mean. You can use this information to decide for yourself which solution best meets your contact center needs.
A Conversation Analytics platform is ideal for contact centers that want to provide omnichannel customer experiences such as self-service options, automated communication workflows, and more. In most cases, a Conversation Intelligence platform that offers Voice Analytics solutions is best for contact centers looking to take advantage of features such as Sentiment Analysis to drive business decisions and improve contact center operations. These data-driven insights can shed light on call volume trends, missed customer opportunities, and areas of agent improvement.
Both Conversational Analytics and Conversation Intelligence platforms will provide you with the insights you need to boost agent performance, improve call script efficiency, and better understand your Voice of Customer. Empower marketing teams with the call insights they need to drive customer-focused marketing campaigns and strategies. By getting a comprehensive look at how your agents are performing, you can devise personalized coaching plans, ensure compliance, and streamline agent onboarding. There are endless ways to utilize Conversation Intelligence and Conversational Analytics to the fullest. Discover additional use cases at Maximizing The ROI Of Contact Center Voice Analytics: Top 5 Use Cases.
While it is not possible to cover every market term, we recommend reading What Is The Difference Between WFO, WFM, WEM, Conversation Intelligence & More to learn more about other popular industry terms you will run into.
.