ALTEN Group Case Studies Sharing

ALTEN in Italy helped two important clients – a leading international bank and a company specializing in pet care – to implement an AI-driven solution to help them streamline data acquisition, automatically categorize feedback, and generate quantitative and qualitative insights to enhance customer understanding and inform strategic decision-making.

Sentiment analysis – the process of examining text to determine if the emotional tone of the message is positive, negative, or neutral – is fundamental to companies seeking to stay at the top of their game. Mobile apps deliver a wealth of information regarding customer habits, preferences and needs. Yet processing the large volumes of text data – from emails, customer support chats, social media, and reviews – can be a formidable and time-consuming task.

Challenge: To improve sentiment analysis for two leading companies to provide faster, more accurate insights

Solutions: Comprehensive sentiment analysis based on automated data collection, leveraging AI-powered chatbots, multilingual capabilities, and data visualization

Benefits:

  • Automatic generation of data
  • Time savings
  • Increased efficiency and accuracy
  • Daily monitoring for real-time insights
  • Improved online reputation management
  • Heightened customer experience
  • Data-driven decision making
  • Actionable insights for continuous business improvement

A dynamic tool

ALTEN set out to use generative AI to automate the process of sentiment analysis for two leading clients. Although the two clients provided very different services, their needs were similar to those of almost all enterprises today: tocollect and analyze user feedback from various digital platforms, such as app stores and social media, so as to respond better to user needs and preferences. However, traditional methods of gathering data and extracting insights are time-consuming and lack the scalability required for real-time monitoring and actionable sentiment analysis. By automating the acquisition of reviews from mobile apps, and using data visualization to capture them, advanced sentiment analysis can offer results that are usable in a dynamic and interactive way.

Tailor-made solutions…

The ALTEN team began by transforming the banking client’s knowledge base into a textual document and uploading it to a vector database, using Microsoft Azure. They then deployed chatbots with natural language interaction to allow users to engage with the system in normal conversation. Users were then able to review the responses by accessing the knowledge base used by the chatbot.

For ALTEN’s other client, the focus was on automating the collection of reviews from social media platforms such as Facebook, Instagram and TrustPilot, then making this information usable in a dynamic and interactive way through data visualization. The ALTEN team began by collecting user comments from the social media platforms using web scraping. The data were then processed, classified and ranked using generative AI, in particular Azure’s OpenAI Service. The graphic representation of the sentiment analysis was carried out on the Microsoft Power BI platform.

…for improved insights

In both cases, the data gathering and analysis processes were fully automated, providing significant improvements in accuracy and comprehensiveness. Once the data are gathered, they are automatically categorized to generate quantitative and qualitative key performance indicators (KPIs) as well as important insights for informed decision-making. Its native multi-language function ensures that the system is widely accessible.

In both cases, the system was able to help the client analyze user feedback efficiently and extract insights for maximum effect.

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