마인즈랩 voc (revo)

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AI Platform Company Big Data Analytics, Artificial Intelligence, Smart Machine 2017, MindsLab. All Rights Reserved MindsVOC “REVO” Mar. 2017 마인즈랩 http://mindslab.ai MindsVOC REVO Introduction

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Page 1: 마인즈랩 VOC (REVO)

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

Page 2: 마인즈랩 VOC (REVO)

ⓒ 2017, MindsLab. All Rights Reserved - 1 -

Problems

:

Manual Transcription

DelayedReport

FalseAlarm

MissingInformation

Manual Transcription & Summarization

Page 3: 마인즈랩 VOC (REVO)

ⓒ 2017, MindsLab. All Rights Reserved - 2 -

Solution - MINDSVOC

Automatic Transcription & Risk Detection

:

AutomaticTranscription

Real-timeDetection

AccurateReports

Thorough outAlysis

Page 4: 마인즈랩 VOC (REVO)

ⓒ 2017, MindsLab. All Rights Reserved - 3 -

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

Page 5: 마인즈랩 VOC (REVO)

ⓒ 2017, MindsLab. All Rights Reserved - 4 -

Process of MindsVOC

Internal VOC

Call Center

Chat

e-mail

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

Page 6: 마인즈랩 VOC (REVO)

ⓒ 2017, MindsLab. All Rights Reserved - 5 -

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

Page 7: 마인즈랩 VOC (REVO)

ⓒ 2017, MindsLab. All Rights Reserved - 6 -

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

Page 8: 마인즈랩 VOC (REVO)

ⓒ 2017, MindsLab. All Rights Reserved - 7 -

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

Page 9: 마인즈랩 VOC (REVO)

Copyright © 2017 Minds Lab. All rights reserved

Dasan Tower 6F, 49 DaewangpangyoRo, BundangGu Seongnam City, GyeonggiDo, Korea T.031-625-4340 F.031-625-4119 | www.mindslab.ai www.mindsinsight.co.kr

No part of this publication may be circulated, quoted, or reproduced for distribution outside the client organization without prior written approval.

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