Best ways to use : AI in Contact Centre

Transcription

1 Best ways to use : AI in Contact Centre Stephen Kennedy Director of Solutions, egain 6 March 2019

2 Gartner predicts that by % of customer interactions will involve an emerging technology such as machine-learning applications, chatbots or mobile messaging, up from 11% in 2017 Application leaders will face the task of onboarding 12 immature but rapidly improving customer interaction channels for CRM 3 out of 4 interactions will involve some emerging tech Today, the average number of channels is under five Though the proportion of phone-based communication will drop from 41% to 12% of overall customer service interactions, a human agent will still be involved in 44% of all interactions 70% of human agent interactions will be digital 2

3 ML+AI+KB: Three Critical Capabilities Seamless orchestration for an easy, connected digital experience Intent Classification Process Guidance Knowledge Base Machine learning drives intent classification Learning bootstrapped and optimized with human-resolved chat transcripts Mimics human triage based on confidence levels and contextual clarification Seamless escalation to human assistance with context if intent cannot be established with enough confidence Powerful AI engine drives parallel reasoning Easily capture and maintain process and best practice knowhow Next best step with conversational guidance for omnichannel engagement OOTB data integration to auto-answer questions direct from data sources Pause and resume Multimedia content Personalized based on single-sourced content and dynamic request context Authoring and publishing workflow built-in Access control with audit and traceability Data macros to personalize content with real-time data 3

4 Match the right tool to the task Low business risk Cannot capture & maintain know-how Automatic execution based on machine learning Can capture & maintain know-how Evidence-based reasoning enhanced with machine learning High business risk Machine learning input with expert augmentation Evidence-based reasoning with supervised learning 4

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6 CHALLENGE #1 VARIATION IN PERFORMANCE

7 CHALLENGE #2 FOUR LEGACY KNOWLEDGE TOOLS

8 THE SOLUTION ALBERT AI GUIDED KNOWLEDGE SYSTEM

9 What we delivered Roll Out & Training Deployment and training to 10,000 advisors and 500 retail stores. Knowledge Content and AI Guidance From over 20,000 individual articles to 10 AI Guided Help case bases. Complete overhaul of knowledge content adhering to standards. Clear content ownership and accountability. Single Knowledge content team. Automated Contact Reason Capture Contact reasons captured through use of AI Guided Help. Retired call reason capture tools (x2 widely used).

10 The Challenge What We Did In the Frontline First Contact Resolution Improved Based on analysis by EE Quality Team: When Guided Help used correctly FCR measured at 85% When Guided Help not used at all FCR measured at 62% Up 23 percentage points (37% improvement) FCR +37% Results Learnings Customer Satisfaction Improved Use of Guided Help has contributed to a 30 point increase in NPS. Complaints have also reduced. NPS +30 The Future Improved Speed to Competency 50% improvement Reduced from 6 months+ to 3 months.

11 Customer Engagement in a Digital World XFORM Learn and predict Insights accelerate product innovation Autonomous orchestration in micro-loops Analytics + ML CHANGE Centralize and personalize knowledge Translate process to interactive guidance All agents can effectively resolve all contacts Knowledge + AI RUN Engage customer across touch points Connected, digital-first experience Contextualize customer journeys Digital + Omnichannel 11

12 AI Value in 30 Days! 12

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