Case Study

AUTOMotive disaster detection

Understanding the Client’s Voice through Social Media platforms regarding given products in a supervised or unsupervised manner

Contact us for more detail

IN BRIEF

KEY INFORMATION

EMOTION ANALYSIS

Detecting feelings through natural language understanding techniques

TOPIC MODELING

Unsupervised classification to analyze text into valuable customer labels

BEHAVIOR MONITORING

In real-time by detecting incoming alerts and minimizing client retention

Challenges

  • Extract data from target social platforms that contain valuable information to the client’s use case
  • Detect customer sentiments by considering irony and sarcasm (subjective aspects in communication)
  • Identify the specific yet diverse types of disasters faced by customers

Solution

  • Dashboard which monitors the negative comments across the different social platforms
  • Personalized filters for the database (hot topics, date, time, social networks, negativity degree, etc.)
  • Detecting specific issues  that will be fed through a feedback loop for quality assessment before impacting the reputation on a large scale

Gains

  • Maintain brand reputation
  • Provide faster and efficient iterations for the products’ quality assurance
  • Keep the client in touch with a real-time market behaviors

Testimonial

“We can detect our product defects in no time! We feel we are more in control of our reputation like never before.”