A utility company performed a large customer survey. The aim was to use artificial intelligence to get more insights in the structured and unstructured content. We applied sentiment analysis on the content and combined it with business intelligence dashboards to have visual insights in the survey.

A utility company performed a large customer survey. Initially the customer wanted to analyse themselves manually the thousands of structured and unstructured content. Lantana proposed to accelerate the process in using artificial intelligence. The aim was to use artificial intelligence to get more insights in the structured and unstructured content. We applied sentiment analysis on the content and combined it with business intelligence dashboards to have visual insights in the customer survey. We compared the outcome of the survey, i.e. the score the customer gave to the utility company with the A.I. generated sentiment score. We have transferred the knowledge of the use of the tool so that the customer can further apply filters gain insights in the survey.

Business Value

Faster and better insights in unstructured data compared to manual analysis
Compare and adjust customer satisfaction score (outcome of the survey) with the A.I. generated sentiment score
Business intelligence dashboards easy understandable and interpretable
Use less human resources for better results & insights

Implementation Plan

Analysis of the content (customer survey)
Data engineering and pre-processing (langauge detection, NLP techniques)
Run sentiment analysis on unstructured content
Build dashboards and BI insights reports
Handing-over and training

Company
Skills
Used technologies
Complexity
Intermediate
Effort Needed
20 man.days
ROI
2 man.months of manual labour
Customer
At a utility company – confidential
Industry
Confidential
Partner
Lantana
Application Type
artificial intelligence
Tech Stack
Azure, Microsoft cognitive services, Microsoft Power BI
Learning Path
Others
Github
X
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