Challenge

A marketing agency needed a scalable way to monitor and understand public sentiment across multiple social media channels. Their teams faced several challenges:

• Limited visibility into sentiment trends, making it hard to launch personalized campaigns.

• Manual and inconsistent tracking of user feedback, which was slow and resource-heavy.

• Unstructured data with hashtags, links, and emojis that hindered analysis quality.

• No scalable tools for real-time sentiment detection and emotional trend analysis.

Solution

Automated Processing:

Targeted Sentiment Detection:

Advanced AI Models: 

Leveraged NLP and Generative AI to enhance language understanding and emotion detection.

Reusable Design:

Collected, cleaned, and analyzed over 27,000 posts without manual effort.

Focused on key content elements to accurately classify posts as positive, neutral, or negative.

Built the system to support multiple industries, languages, and teams, ensuring long-term flexibility.

We built an automated sentiment analysis system tailored for high-volume, unstructured social media data:

Interactive Dashboards:

Delivered on-demand dashboards for campaign performance and sentiment trends.

Impact

The solution drove measurable improvements in brand monitoring and engagement:

• 70% time savings, replacing manual tracking with automation.

• Enhanced customer insights, enabling better product and service improvements.

• Faster responses to customer feedback, boosting engagement and loyalty.

• Higher satisfaction and ratings by identifying and addressing issues early.

• Better campaign performance, adjusting strategies in real time based on public sentiment.

“Monitoring telecom network performance across countries with real-time data and automated reporting.”