마인즈랩 voc (revo)
TRANSCRIPT
AI Platform Company
Big Data Analytics, Artificial Intelligence, Smart Machineⓒ 2017, MindsLab. All Rights Reserved
MindsVOC “REVO”
Mar. 2017
마인즈랩http://mindslab.ai
MindsVOC REVO Introduction
ⓒ 2017, MindsLab. All Rights Reserved - 1 -
Problems
:
Manual Transcription
DelayedReport
FalseAlarm
MissingInformation
Manual Transcription & Summarization
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Solution - MINDSVOC
Automatic Transcription & Risk Detection
:
AutomaticTranscription
Real-timeDetection
AccurateReports
Thorough outAlysis
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MindsVOC distills the Voice of Customers
I do apologize for the
in convenience
How may assist you to
day?
Um my excuse me with
my washer yesterday
was smoking and it’s not
working anymore
Agent Customer
Let me going double
check here
And it's too hard to call.
I've waited too long. I’m
sorry but it's annoying.
Collecting all of the data, call, chat, email, Internet
Automatic Transcription & Summarization of 100% the
Calls
Capture Real Sentiment of Customer using
Deep Learning Tech.
Real-time Detection & RiskReporting
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Process of MindsVOC
Internal VOC
Call Center
Chat
bulletin board
External VOC
Social Netw
ork
Internet
Speech to T
ext (Voice Recog
nition)
Text Analytics
Data MiningNLP
Categorization
Detection
Dashboard
25K calls 5K chats 0.5K emails 10K web
STT: 86% TA: 97%Real-time
Batch
(Case Study: USA)
Omni-channel
End-to-End Solution
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Benefits From MindsVOC
Customer Experience Management
Real-timeRisk Detection
Enhance Agent Quality
Abnormal ServiceMonitoring
Call Center
Field Service Sales & Marketing
Product Development & Marketing Strategy
Detect Product Liability & Potential Claim Calls
Detect
Abnormal Counselling
Detect
Broken PromisesCaught Product Reputation
by Region
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Understanding the flow SolutionTypes and Seriousness
Contact Center
Com-plain
Request
Cancellation
Compensation
Loans
• Categorizes the calls through HMD
• Through DL classifies the contents, types and inquires of the complaints.
• Finds out connection bwt the service and the complaints
• Scaling of the call according to the frequency of the sentences w complain
VOC?or
Non-VOC?
30 sentences
10 sentences
5 sentences
Frq of complain call per period
Solution to frq raised issue
[Step 1]Client dissatisfied w the service when he/she contacted the contact center.
[Step 2]Specific inquires depending on the types of complaints.
Compensation
Scale
Systematic procedure to find out what the complaints is and why the customers dissatisfied and to categorize the data, in order to respond with speed and accuracy.
MINDs VOC – Case Study [Insurance Co., KR] Customer Complaint Analysis
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MINDs VOC – Case Study [Insurance Co., KR] Deep Learning Classification on complaints
More than 95% Accuracy on Deep Learning Classification Test: finding out the
cause, the inquires and their relation to the tasks.
Class Namelearned
sentences
A1 No answer 10,000
A2 Overcharged 7,000
A3Unable to
solve6,500
A4 Outstanding 5,000
A5 Delayed 3,000
A6 Inconvenience 2,000
A7 Changing rep 1,000
A8Refusing contract
1,000
A9 none 20,000
Types of complaints ( labelled as class)
Class# of
sentenceCorrect Answer
% A1 A2 A3 A4 A5 A6 A7 A8 A9
A1 10,000 9,721 97.2% 9,721 111 25 14 11 22 20 22 54
A2 7,000 6,632 94.7% 127 6,632 88 21 54 7 15 9 47
A3 6,500 6,429 98.9% 31 7 6,429 3 6 3 1 - 20
A4 5,000 4,700 94.0% 62 26 41 4,700 21 33 14 18 85
A5 3,000 2,899 96.6% 32 16 8 9 2,899 - 6 3 27
A6 2,000 1,920 96.0% 17 5 - 12 4 1,920 9 4 29
A7 1,000 942 94.2% 14 4 5 - 8 2 942 2 23
A8 1,000 915 91.5% 32 - - 12 11 6 5 915 19
A9 20,000 19,800 99.0% 82 17 23 5 18 28 13 14 19,800
Total 55,500 53,958 97.2% 10,118 6,818 6,619 4,776 3,032 2,021 1,025 987 20,104
Deep Learning Classification test result per class
CQT INCOR
Copyright © 2017 Minds Lab. All rights reserved
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