Contact Center AI That Works

Transcription

1 Contact Center AI That Works PRESENTER John Connors, Senior Director of Digital Transformation egain Corporation

2 Contact Center AI Technology that works! John Connors Senior Director, Digital Transformation, egain March 12, 2018

3 About egain Founded 1997 Headquarters Sunnyvale, CA, USA Offices in EMEA and APAC What we do Omnichannel engagement cloud solution Digital engagement Knowledge management Artificial Intelligence Analytics

4 Trusted by leaders Banking, FS and Insurance Telecom and Media Retail and Manufacturing Federal and State Government Utilities

5 Agenda Definition of AI Where do KM and AI overlap? Choosing between KM and AI Case Study: Transformation using AI How to get started 5

6 What is Artificial Intelligence? 6

7 What is Artificial Intelligence? General AI Trying to build a system that is equal to or better than a human on general tasks Narrow or Applied AI Building useful applications, usually restricted to a particular domain, specific tasks Historically, most benefit has been gained from applied AI

8 AI: Learning systems Probabilistic engines, neural networks IBM Watson Star of the Jeopardy quiz show Microsoft TAY Learned from Twitter interactions Turned off within 24 hours due to it making extreme responses 8

9 AI: Taught/built systems Rules based /expert systems (Since 1970s (e.g. Mycin) Most chatbots, virtual assistants, avatars Case based reasoning (CBR) systems Bot Platforms Service based architectures just add your domain expertise Microsoft Bot Framework Facebook Messenger Platform Kik Amazon Alexa/Echo/Dot Google Home 9

10 Where does AI overlap with KM? Virtual Assistants Language processing engines, with an avatar user interface. Use dialog with web users and business rules to discern relevant information to provide. Can decide to escalate to Chat providing full context. Guided Help Case Based Reasoning engines which use data gathered from conversational interaction, or via batch entry, to provide expert advice, diagnostics or process guidance. 10

11 Types of Contact Transactional Change something Solve something Diagnostic or Advisory Tell me something Informational 11

12 Mix of Contact types Frequency Informational Transactional Diagnostic or Advisory Complexity 12

13 Mix of Contact types Frequency Increasing potential for Customer dissatisfaction Decreasing chance of FCR Decreasing potential for Compliance Informational Transactional Danger Complexity 13

14 What about traditional KM? 14

15 15

16 EE Customer Service Overview 6 In-house sites Partners in UK, Ireland & India 10k Advisors 16

17 THE #1 CHALLENGE VARIATION IN PERFORMANCE 17

18 Performance is a MIXTURE of PEOPLE and PROCESS Is it the people delivering great service regardless of process... Is it the processes delivering great service regardless of person... 18

19 The best people can crack it Quartile 1 Quartile 2 Top percentile: 55+ NPS, 85%+ solve rate Quartile 3 Bottom percentile: -5 NPS, 55% solve rate Quartile 4 19

20 Second Challenge 4 Knowledge Tools T-Mobile Knowledge Orange Knowledge Top Tools Content Topic Orange Diagnostics EE (Phase 1) 20

21 But Tools weren t the only problem 10% consistent usage of knowledge Inconsistent answers Over 20,000 articles Tick sheets for contact reasons 21

22 THE SOLUTION ALBERT 22

23 ALBERT Phase One Search, Browse and AI/Guided Help capability within the egain system for the top 10 contact drivers New content for the EE brand, some imported content for other brands PLUS federation over existing repositories Automation of Reason Code assignment Saving of the Guided Help session summary to CRM 23

24 Albert UI Agent & Retail templates 24

25 ALBERT Phase One H Roll out to all onshore & offshore contact centers 10,000 named users (6k concurrent) 500 retail stores Albert use was not mandated but On calls where AI/Guided Help was being used 23% increase in FCR 20% increase in NPS Reduced complaints 25

26 THE UPDATED SOLUTION ALBERT II 26

27 ALBERT Phase Two All contact drivers covered by Guided Help Search became a secondary access method 16k KB articles => 10 GH case bases + 1.5k articles Relaunch of Albert with refreshed UI Alignment of Albert use with agent compensation 27

28 Albert II What is the Agent Experience like? 28

29 Pre-answer questions giving GH some context 29

30 Guidance for the advisors 30

31 New Advisor Feedback Loop - Not right? Tell us.. Knowledge Usage Feedback Response sent within 24 hours. Content Team Assessment Content Updated (Small/Medium change) 31

32 In the frontline - What we found 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% Customer Satisfaction Improved Use of Guided Help has contributed to a 20% increase in NPS. Complaints have also reduced. Induction Training Reduced 14 days > 8 days Guided Help has led to new employee inductions being reduced from 14 working days to 8 working days or less. FCR +23% NPS +20% Improved Speed to Competency 50% improvement Reduced from 6 months+ to 3 months. 32

33 The Performance Gap The worst performers are now pretty good! Bottom quartile now has: 70% solve rate Average NPS of 42 Compare that with pre-albert figures: 55% solve rate Average NPS of -5 33

34 In Life Agent impact Agents are less stressed Make the interaction as good as possible but don t stress about the outcome But follow the guidance or there are consequences Find My Phone three strikes policy 34

35 BEYOND THE FRONTLINE: DRIVING BUSINESS TRANSFORMATION

36 Utilising the call reasons Integrating the call reason data into our business has given EE actionable insight Agents follows guided help Data transformed to derive call reasons Extra metrics attached to the call reasons (NPS, AHT & FCR) Insight now available to answer 2 problems 1 2 Business awareness of call drivers People & performance management 36

37 Company wide drive to improve Customer Service Propensity to contact (PTC) split by repeats & transfers (CS owned) and unique (business owned) Regular weekly tracking Company wide programme to drive initiatives Clear accountability 37

38 Company wide drive to reduce PTC Categories aggregated to business functions with owners assigned Call reasons grouped into business functions and movement tracked weekly Clear accountability & ownership 100% buy in around the entire business Key Learning by being descriptive on how other areas can help reduce PTC the programme was much more successful than previous years. 38

39 Insight driving Transformation Call volumes have been reduced by 45% Tangible results of the drive to reduce PTC Repatriation of off-shore contact center Complaints to the Ombudsman Less than 11% now come from EE, was 50% Broadband tickets reduced by a factor of 11 39

40 AI for Contact Center Finding & Using Intelligence Call recordings Voice IVR utterances Process Guides Training material KB articles Best agents Domain experts Complexity Decide scope Define KPIs Value 40

41 Get Agile 41

42 Visit us at Booth #2203 for more information!