Life Cycle Of Speech Analytics
The speech analytics life cycle refers to the steps involved in implementing and using a speech analytics solution. The specific steps in the life cycle will vary depending on the solution, but a typical speech analytics life cycle includes the following phases:
Planning: This phase involves identifying the business needs and objectives for speech analytics, selecting the right solution, and establishing a project plan.
Data Collection: This phase involves collecting speech data from various sources, such as call center recordings or customer surveys, and preparing the data for analysis.
Data Preparation: This phase involves cleaning and transcribing the speech data, and labeling the data if necessary.
Query Building: This phase involves defining the search criteria for the analysis by using keywords, phrases, and operators to specify what type of data should be extracted from the speech data.
Data Analysis: This phase involves running the search query on the speech data and producing a report of the results.
Validation: This phase involves checking the quality of the speech data and the accuracy of the results, and making any necessary adjustments to the search criteria or the data preparation process to improve the accuracy of the results.
Action: This phase involves using the insights and information extracted from the speech data to take action, such as improving customer service, optimizing call center operations, or developing new products and services.
Monitoring and Continuous Improvement: This phase involves monitoring the results of the speech analytics solution and making continuous improvements to the solution and the process to ensure that it remains effective and relevant.
This is a general overview of the speech analytics life cycle. The specific steps and methods used will depend on the speech analytics solution you are using and the specific business needs and objectives of your organization.
Comments
Post a Comment