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Blackbook.ai

Survey Topic and Sentiment Analysis

A company that performs community survey and engagement analysis engaged Blackbook.ai to build an automated dashboarding solution for open text responses on surveys.

Industry

Unknown

Technology stack

Natural Language Processing

Industry

Unknown

Technology stack

Natural Language Processing

Industry

Unknown

Technology stack

Natural Language Processing

The challenge

The client had a lot of manual work assessing qualitative open text responses on surveys from their customers in order to create reports. They were after an automated way that reduced the human error, biases and that stood up to their quality standards to produce these reports. The reports combined both these qualitative answers with the quantitative demographic survey responses.

The solution

Blackbook built a solution using two highly regarded open-source LLMs to solve the client’s challenge. The first model was able to ingest all the responses from a question to identify the key topics, then assign the individual responses to topics with a confidence score. The second model assigned a sentiment score to the responses, as well as pulling out key phrases and entities so the client could understand further insights. This data, along with the quantitative demographic survey data was modelled into a dashboard with automated reporting so the process was an end-to-end solution.

The outcomes

The client saved significant time and resources by being able to automate a main part of their business processes. Analysis that usually took several resources weeks, now took under a day to produce and allowed the resources to spend time doing higher intelligence work looking for deeper insights into the data.

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