Natural Language Interactive Analytics Solution
The implementation path for customer service executives from non-technical backgrounds is as follows:
- Data Source Configuration: Integrate Zendesk work order system, customer satisfaction survey form and customer service call records (support CSV/API multiple access methods)
- Semantic Layer Construction: Define business terminology mappings in the knowledge base, such as mapping the
resolution_timerelate to问题解决时长 - conversational query: Ask questions directly from the web chat interface:
- "What is the percentage of repeat work orders this month?"
- "Which customer services have below average first time resolution rates?" - Visualization of resultsAutomatically generated SQL results can be exported as charts or interfaced with BI tools such as Tableau.
Effective Case: The customer service supervisor of a telecommunication company shortened the production time of weekly report from 4 hours to 15 minutes through natural language query. The system can automatically recognize客户流失风险and other complex business concepts.
This answer comes from the articleMindsDB: An Open Source Platform for Connecting Data from Multiple Sources and Querying with SQL and AIThe
May not be reproduced without permission:AI productivity tools " How can natural language queries be used to improve the efficiency of service data analysis in customer service team scenarios?
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