Analyze conversational data from call-centers, customer-agent conversations,
live chat and e-mails.
Deep dive to understand interactional conversations. Leverage analysis of conversations and measure performance of customer service agents with sentiment analysis. Combine multi-label classification and dynamic classification of Kimola Cogitive to automatically classify textual data.
Understand the needs of customers and which topics are included in each conversation. Upload spreadsheet and get results with multi-labels.
Integrate with favorite tools such as Zendesk, Intercom or upload a spreadsheet that contain customer-agent conversations to analyze. Measure sentiment across topics, classify automatically without training.
Automatically classify your data based on the context, whether it contains consumer reviews, news or articles.
Upload your training set and build a custom machine learning model based on your custom business needs.
Data analysis starts with data. Make use of Kimola's data scraping extension to access consumer reviews.
Conversational analysis have various types, such as Whatsapp business-customer conversations, call-center conversations or even e-mail loops that are between the customer and company.
Conversation analysis involves examining various elements such as turn-taking, adjacency pairs, speech acts, repair mechanisms, and non-verbal cues. These components are crucial for understanding the structure, organization, and social dynamics present in everyday conversations.
Export your Whatsapp Business conversations to a spreadsheet after downloading the data. Combine the conversations into one spreadsheet. Upload the dataset to Kimola Cognitive and choose multi-label classification.
Integrate Kimola Cognitive with Zendesk, Intercom, Google Sheets or simply upload the spreadsheet to the platform by dragging and dropping. Choose multi-label classification at the end of the screen to get the best out of it.
Kimola Cognitive offers automatic classification that needs no training. Kimola Cognitive also offers multi-label classification which is a must when it comes to analyzing agent - customer conversations. When combined, Kimola Cognitive offers an analysis of interactional conversations with a high accuracy rate, while analyzing conversations in 26 languages.
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