Retail Stress Management with AI/Cognitive Stressometer

Efficiently monitoring customers stress to enhance their experience during peak shopping events.

Goals

  • Swiftly pinpoint and categorize stressed customers.
  • Deploy an RPA for real-time detection and resolution of complaints within the client’s system.
  • Rapid implementation ahead of Black Friday, to mitigate complaint surges and augment satisfaction scores.

Goals

  • Swiftly pinpoint and categorize stressed customers.
  • Deploy an RPA for real-time detection and resolution of complaints within the client’s system.
  • Rapid implementation ahead of Black Friday, to mitigate complaint surges and augment satisfaction scores.

Strategy

  • Assembled a specialized team including a Data Scientist, Data Engineer, and Scrum Master for comprehensive transformation.
  • Incorporated speech analytics and Natural Language Processing (NLP) for targeted intervention on detected stress cases.
  • Introduced an insightful dashboard that offers actionable directives for operational teams.

Strategy

  • Assembled a specialized team including a Data Scientist, Data Engineer, and Scrum Master for comprehensive transformation.
  • Incorporated speech analytics and Natural Language Processing (NLP) for targeted intervention on detected stress cases.
  • Introduced an insightful dashboard that offers actionable directives for operational teams.

Highlights

  • The specialized Litigation Service operation screens, categorizes, and actionably addresses cases flagged by the Stressometer.
  • A specialized workflow is employed to alleviate customer dissatisfaction, ensuring a smoother customer journey.

Highlights

  • The specialized Litigation Service operation screens, categorizes, and actionably addresses cases flagged by the Stressometer.
  • A specialized workflow is employed to alleviate customer dissatisfaction, ensuring a smoother customer journey.

Results

  • Achieved deployment just tin time for Black Friday, spanning just three sprints.
  • KPIs Improvement:
    • Willingness to transact with the company again surged from 48% to 56%.
    • Resolution timeliness drastically shortened from 14 days to merely 6 days.

Results

  • Achieved deployment just tin time for Black Friday, spanning just three sprints.
  • KPIs Improvement:
    • Willingness to transact with the company again surged from 48% to 56%.
    • Resolution timeliness drastically shortened from 14 days to merely 6 days.

Share

Cases

Resolutive Chatbot for the electric energy sector

Transforming Traveler Experience with Xtrabot

Linkedin LogoLinkedin Atento Live LogoAtento Live