Tags: Increased CR, Reduced Escalation Rates, Reduced Failure Rates, Better Customer Experience, NLP, Natural Language Processing, Analytics, Conversational, Brand Experience
Problem: NLP engines on the market are generalized models, taking a ‘one size fits all’ approach to solving the vast array of enterprise domain / use cases. This leads to an unnecessary number of chats that escalate to a human, costing companies millions of dollars in unnecessary expenditures and a negative customer experience.
Solution: Dashbot turns unstructured, noisy, inter-related and often tangled conversational data into operational and actionable insight, in real-time. They enable customers to build their unique NLP engine around specific keywords, concepts and use cases from their own conversational data.
Performance: Intuit had so much unstructured data, their team was spending days trying to manually identify mishandled or unhandled intents.
Dashbot provided a full transcript of every session to map out conversational paths a user had with QuickBooks Assistant – how and what customers were asking. They were able to optimize the conversation flow based on the actual conversations customers were having.
- 35.3% reduction in not handled rate
- 57% reduction in escalation
- Ongoing performance increases
- Now only high-priority calls need to be handled by a human
Persona: Director of Customer Success or Conversational Designers