Conversation Intelligence Software

Conversation intelligence software records, transcribes, and analyzes sales and customer service calls with the goal of improving performance. Conversation intelligence employs speech analytics to identify topics and sentiment analysis to understand the speaker’s emotions.

Conversation intelligence platforms pinpoint key moments in customer and prospect exchanges so you can easily understand how to improve in future interactions. Plus, sharing those examples and the related data is a snap with a conversation intelligence platform. Agents can effortlessly jump to key moments in calls to efficiently understand how to optimize their own pitch or customer service.

Conversation intelligence analyzes recorded and transcribed text to give insights into customer and prospect conversations. Conversation intelligence software uses speech analytics in order to evaluate the topics discussed and the emotions expressed. With these tools agents will benefit from individualized KPIs like speaking speed, time, interruptions, and more.

Conversation intelligence is usually powered by artificial intelligence (AI), which automates analysis for rapid and efficient optimization.

Examples of conversational AI include chatbots and virtual assistants like Alexa, Siri, Google Assistant, Cortana, and more. These assistants, which understand natural language and user intent, offer personalized responses. They’re powered by conversation intelligence and speech analytics.

Conversation intelligence tools prices generally range from $80 to $100 per user per month, but they can even cost as much as $200 per user. Some platforms will also add a base price to the monthly subscription fee, which can be in the thousands of dollars.

Speech analytics is used to understand, process, and analyze human speech. Speech analytics software is powered by artificial intelligence, technology which allows it to automatically transcribe call recordings and evaluate them. Once the audio recording has been converted to text, speech analytics will identify the topics discussed and the emotions expressed by the speakers. That’s why speech analytics is very useful for contact centers and sales representatives. Speech analytics analyzes customer or prospect interactions to identify opportunities for optimization.

There are two types of speech analytics.

1. Speaker dependent

   In a speaker dependent speech analytics system, the technology is trained by the person who will be using the system. With this type of speech analytics, the system can be highly accurate but only achieves that level of accuracy with the person who trained the system. That’s why this type of speech analytics is generally reserved for personal use.

2. Speaker independent

   With a speaker independent speech analytics system, the technology is trained to respond to any speaker. To be capable of responding to any speaker, the system must understand a big variety of speech patterns, inflections, and enunciations. The accuracy of this speech analytics technology is generally lower than a speaker dependent system, but more appropriate for professional use.

Speech analytics is a technology that processes transcriptions of voice recordings or live calls from a sales teal or contact center. A speech analytics software will evaluate speech to identify topics and complete sentiment analysis, the identification of emotions expressed by the speakers.

Speech analytics is a branch of artificial intelligence that analyzes transcripts of customer or prospect calls or live telephone calls to understand, process, and analyze human speech. The result of AI speech analysis is the identification of topics and emotions expressed by the speakers. The identification of emotions is also referred to as sentiment analysis. Contact centers and sales teams can benefit from AI speech analysis because it gives insights on how to improve sales pitches and performance.