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Use Case | Insufficient Supervisory Coverage | Expensive training and hiring process | Inaccurate NPS & CSAT scores due to small sample |
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Situation | Only 1-5% of customer interactions are being analyzed Lack of coverage + human error and bias → inaccurate, insufficient insights
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Risk | | | |
Call Journey Solution | | Sentiment analysis of each agent ongoing, highlight negativity ongoing/trend? Employee insights, aiding in performance, coaching, and wellness and assisting in staff retention
| AI, NLP and NLU produce a robust understanding of the sentiment and acoustics of interactions Sentiment analysis of each call. Customise analysis to look for NPS relevant speech/text
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Outcome | Enhanced decision making Mitigated risks Excellent QA Immediate identification of problematic areas in process, CX and agent performance Reduced wasted effort and cost (QA/team leader) Faster outcomes
| Staff wellness also has a flow-on effect to customer experience and financial outcomes Better resource allocation Reduced training costs and efforts
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Other Departments
Use Case | Risk of compliance breaches and large fines | Boosting Sales Performance | Accelerating R&D of Products and Services | Personalization of Marketing Campaigns |
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Situation | | | | |
Risk | | | | |
Call Journey Solution | 100% coverage and compliance coverage Rules engine is programmed to proactively identify potential breaches Combination of human and artificial intelligence → comprehensive results Ensure key statements are actually said Highlight dangerous statements
| rules engine can be programmed to efficiently identify customers’ key drivers, trends and patterns Sales is emotion driven, analyse speech+words, highlight bad/good calls for training / improvement
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Outcome | Reduce risk of fines Flag ‘warning lights’ before it happens Reduced cost of compliance management Proactive compliance management vs reactive
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