Speech analytics imot.Io is often seen as a cheaper alternative to salesai. Let’s find out what the difference is between imot.Io and salesai. In this article, we will take a detailed look at the capabilities of each. To help you choose the best solution for your business. You will learn how each platform handles the tasks of audio-to-text transcription. Emotional state monitoring, conversation labeling. And reporting and notifications. We will also compare traditional keyword-based speech. Analytics methods with modern technologies based on large language. Models (llm) like salesai to show how new technologies can significantly improve your business processes.
Overview of speech analytics functionality of Imot io
>>Convert audio to text
Imot.io’s speech recognition technology is based phone number list on keyword analysis, which allows it to achieve an accuracy of up to 70%. The next step will be to manually check this data set to ensure higher recognition accuracy.
Analysis of emotional states
Identifies emotional states with 70% accuracy, helping to identify problem calls and improve service quality.
Highlighting key aspects of dialogues
The service allows you to highlight important aspects of conversations for subsequent analysis.
Visual reporting: Managers can receive detailed reports that help them better understand the dynamics of customer interactions.
Search conversations by keywords
Quickly search for the conversations or messages you need using keywords.
Setting up data processing parameters
The ability to customize call and message ghirlandaio, guercino and filippo de pisis processing parameters depending on the company’s tasks and needs.
Generate reports and notifications
The system sends notifications to Telegram within 3-5 minutes after a call if problems arise. It is possible to create customized reports for individual tasks.
One of the imot.io clients shared his impressions after the pilot
>>Problems with question evaluation : Vlad noted that the system they had previously worked with had a working tool, but did not allow setting semantic blocks for question evaluation. The system global seo work required manual input of all possible interpretations of words and their location in the sentence, which significantly increased labor costs and the complexity of setting up communication evaluation.
>Promises Didn’t Live Up To : Initially, contractors promised to connect a neural network to automate the assessment of more complex questions (for example, tracking diminutives in managers’ speech). However, in practice, the tool turned out to be unfinished, and such functions either did not work or cost significantly more than expected.
