Use case

Text analytics to increase productivity and improve decision-making

Text mining used to analyze useful information from a large amount of data

This process which helps with market analysis and customer retention maximizes the value of insights extracted out of unstructured text documents.

text analytics

What do we solve?

As more and more companies move towards digital channels, the need for text mining to understand customers is heightened. Huge amounts of unstructured data is generated every minute. So, businesses feel pressured to be omnipresent and track every click and every message. But most of this is manually carried out by humans. This overload of information is too time-intensive for humans which leads to paralyzing analysis and missing out on vital insights. In fact, many current text analytics solutions do not provide industry standards in terms of quality of codification or compliance. As a result, this leaves room for a text analysis solution that is more consistent in reducing human error and bias.

How do we solve it?

dezzai Semantic AI platform will:

Text is extracted from different types of formats including documents, images, audio, and voice

Detect and classify concepts in plain text

Return the detected concepts through an API or the service is integrated into a third-party solution

WHAT do we deliver

text-mining-solution
  • A text mining solution that detects, classifies, and extracts concepts from text documents, social media content, chat conversations, images, and audio. The tool can identify critical topics in data, remove noise and provide context-enriched data. 

Benefits of applying Artificial Intelligence

Understand customer trends and product performance to enhance business intelligence 
Improves productivity by cutting down the time required to identify and classify data
Reduces costs
Increases the quality of data encoding
Enables extraction of data of all type of files and unlock ‘hidden’ information
Optimizes SEO for content
Reusable, scalable

Use cases

sentimental-analysis

Sentimental analysis (drivers)

trend-detection

Topic, theme, trend detection

content-quality

Content quality, and classification

product information

Fake news detection, language detection and translation

net-promote-score

Net promote score

marketing-research

Marketing research

voice-customer

Voice of customer, of employee, consumer, etc.

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