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VoC Analysis
By converting voice files of customer conversations at call centers into text, analyzing them, and training AI models, you can provide counselor assistance services, automatically generate FAQs, evaluate service quality, and analyze customer complaints.
Next is an example of analyzing customer service interaction case, with the scenario illustrated in the figure below.
The VoC analysis app offers individual features such as sentiment analysis, call summary, keyword extraction, service evaluation, product feedback assessment, FAQ generation, and automated responses. Users can choose to use only the necessary features or combine multiple functions as needed.
To begin the analysis, upload voice files containing recorded call content first.
STT (Speech-To-Text) is then applied to the uploaded voice files to convert the audio into text. The converted text is analyzed, summarized, and categorized by similar topics.
For each category identified, FAQs are automatically generated, and the generated FAQ content is stored in the database as tables.
Users can analyze VoC through natural language Q&A. The user’s input in natural language is converted into an SQL query, which is executed, and the results are transformed into responses via LLM.
In addition to the built-in scenarios,
customized scenarios according to customer requirements can be applied within a few weeks.
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