roundtable michael dwyer , troy surdick, senior joseph ...€¦ · segment customers and apply...

ROUNDTABLE

September,

2018

Michael Dwyer ,

Vice President,

Research, CallMiner

Troy Surdick, Senior

Product Manager,

NICE Nexidia

Joseph Ciuffo, Lead

Demonstration

Consultant, Technical

Sales, Genesys

Brendan Dykes,

Global Director

Product Marketing,

Genesys

Analytics –

Speech, Text,

and AI

Presenter photo

Presenter photo

Intelligence from Customer Interactions

Content Coverage:Squeezing Every

Ounce of Intelligence Out of Your Calls

Mike Dwyer

Vice President

Research & Innovation

Proprietary & Confidential, CallMiner Inc.


3

About CallMiner: Customer Engagement Analytics

Our Vision

“To empower organizations of any size to extract and take action

on intelligence from customer interactions to optimize CX, sales,

marketing, compliance, and contact center performance.”

Unique CallMiner Value

Recognition

Velocity

Turnkey Integrations,

packaged content

and self-serve

customization enable

fastest time-to-value

Agility

Open API and artificial

intelligence enables

agile solutions, flexible

integration and

predictive modeling

Results

ROI via automation,

Playbooks, exceptional

support and innovation

from collaborative

community

2018 Best Speech

Analytics Solution

2018 SilverCall Center Solution

Nuance and CallMiner Unite to

Debut Unparalleled Customer

Engagement Analytics

http://www.callminer.com/new-wave?utm_source=crmxchange

http://www.callminer.com/new-wave?utm_source=crmxchange



4

It is the “JUICE” extracted from call.

How much do we actually know about our contacts?

Successful contact center implementations of AI Prediction and Root-Cause Discovery depend on having access to as MUCH information about the interaction as possible…

“Content Coverage” is the Metric of how much of contact center’s calls or chats have been mined for analysis …



5

So what should we look for?

1. Contact Sampling

2. Metadata Fidelity

3. Customer Journey

4. Conversational Coverage

5. Semantic Analysis

Comprehensive Coverage Metrics

There are several components to the “Content Coverage Metric” –a well-formed coverage plan addresses each of these, and is a great predictor of future success…

Checklist Available



6

Why is Content Coverage Important?

The goal of Speech Analytics is to expose ACCURATE business intelligence contained in the contact center to the business at-large in a TIMELY fashion.

Accurate and Timely business intelligence drives the success of the following operations:

❑ Agent Quality Scoring

❑ Contact Center Training and Best Practices

❑ Knowledge Base Creation and Delivery

❑ Product Problem/Failure Analysis and Resolution

❑ Marketing Decisions

❑ AI Prediction Models for Churn, C-Sat, FCR, Upsell/Cross-sell Recommendations

ACCURATEDependable and definable

TIMELYQuick to create/define (out-of-the-box) Quick to mine/take action on (post-call/real-time)



7

Contact Sampling – How much is enough?

Contact Sampling (mining and measuring less than 100% of your interactions) is acceptable in ONLY a few specific use cases:

✓ General Topic Discovery

✓ Call Disposition Ratios

✓ Finding Anecdotal Training Examples

ACCEPTABLE

× Regulatory Script Compliance

× Fraud Detection

× Customer Journey Analytics

× FCR/Churn Prediction

× Agent QA Scoring ***

NOT ACCEPTABLE



8

Metadata Fidelity – How good is our metadata?

Questions to ask -1) How much do we know “about / around” the call or chat?

2) Is it useful structured data? OR does it require interpretation or transformation?

3) Is it clean and verified? When is it available? Is there a lag?

ACD/Channel Information

Speaker Information

Business Hierarchy

Disposition codes

MUST HAVES

❑ Customer/CRM information

❑ External Channel information

❑ Post-call Outcome/Results

BONUS POINTS !!!



9

Customer Journey – Where have we been?

Having the “WHOLE PICTURE” of a customer’s interactions with your contact center is VITAL in use-cases such as Customer Sales Journey, Fraud Discovery, FCR, and Churn

Can we link an interaction to its previous and subsequent siblings (full journey)?

How are we treating contact interruptions like holds, transfers, and hang-ups?

Can our analysis span the “width” of your problem, like annual subscriber churn

Do we have the right amount of “analytical retention” versus “anecdotal retention?

Customer Journey Checklist



10

Conversational Coverage – What is being SAID?

Speech Analytics depends on “speech” – the ability to have accurate speaker content to analyze and discover what is actually happening in the call center is directly predictive of your success

Full transcription versus word or phrase spotting

Acoustic Fidelity → Transcription Accuracy

Stereo Separation and Agent Identification

Foreign Language Coverage

Speaker/Speech Analysis (Tempo, Tone, Emotions/Emoticons)

The SWEET SPOT for driving a successful Speech Analytics implementation



11

Semantic Analysis – What did they MEAN?

Speech and Text are simply the mechanisms by which humans communicate – However, we tend to think in concepts and pictures (i.e. images , emoticons , and relations →). So that is what we must analyze

❑ PROCESS / SCRIPTS

( Greeting, Verification, Disclosures, Closing )

❑ CALL REASONS

( IVR Intents, Disposition Codes, Problem statement or Customer Request )

❑ BEHAVIORS

( Escalation, Dissatisfaction, Politeness, Engagement, Understandability, Profanity )

Semantic Building Blocks

❑ BRANDING

( Product, Competitor Mentions, Marketing Message, Social Buzz )

❑ SENTIMENT

( Positive / Negative )

❑ OUTCOME / RESOLUTION

( FCR, CustSat, Churn, Sales/Collector Effectiveness )

❑ QUESTION-ANSWER LOOPS

( Upsell/Cross-Sell, Technical Support, Customer Service, Fraud Discovery, Financial Collections )



12

Semantic Coverage – Who’s Saying What?

• SILENCE vs NOISE?

• What is CONVERSATION versus JUST TALK?

• Who is TALKING?

( IVR / Agent / Customer )

TALK METRICS



13

Semantic Coverage – Where is our GAP?

For a given set of calls, the Semantic Coverage Index can be measured in several ways:

❑What types of Semantics are being represented?

❑ Does each call have a reason, behavior, and outcome captured?

SEMANTIC TAGGING ANALYIS

❑What sections of the call are covered most/least?

❑ Can we target Discovery at those areas?

SEMANTIC TAGGING LOCATIONS



14

Semantic Coverage – Semantic Tagging Locations

What parts of the call are currently covered well?

Need more work HERE !!!



15



16

Filling in the blanks…Once you have measured WHAT you already have and WHERE, you can use AI/Machine Learning to expose WHAT ELSE…

Entity Extraction

Topic Analysis

Auto-Correlation / Root Cause Discovery



17

Summary

❑ Measure Everything ‒ Both INSIDE and OUTSIDE of your contacts

❑ Measure Twice, Cut Once‒ Measure and track what you HAVE

❑ Fill the GAP‒ Create what you DON’T

Keys To SuccessComprehensive Content Coverage Metrics are a great predictor of success in a Contact Center Speech Analytics implementation or an AI/ML-based Prediction project…



Visit the CallMiner Learning Center!

Dozens of webinars, guides, videos, case studies, and blogs on all contact center and

customer experience best practices.

Sign up for a Test Drive!

Experience the true power of CallMiner Eureka.

Get an Efficiency Audit, and identify other opportunities for improvement and insights!

callminer.com/demohttps://bit.ly/2CLGxzI

http://callminer.com/try-eureka-analytics/utm_source=webinarslide

http://learn.callminer.com/?utm_source=webinarslide

http://callminer.com/try-eureka-analytics/utm_source=webinarslide

© 2018 NICE Nexidia. All rights Reserved. CONFIDENTIAL

ANALYTICS: SPEECH, TEXT, AND AI

Troy Surdick

Manager, Product Management

© 2018 NICE Nexidia. All rights Reserved. CONFIDENTIAL 20

BY 2020 CUSTOMER EXPERIENCE WILL OVERTAKE PRICE AND

PRODUCT AS THE KEY BRAND DIFFERENTIATOR

1Customers 2020 report by Walker Information2Lee Resources

80% of companies

say they deliver "superior"

customer service

8% of people

think these same companies

deliver "superior" customer

service2


Major Challenge:

Customers’ Expectations

1

KNOW MY STORY

SOLVE IT NOW

MAKE IT EFFORTLESS

MAKE IT RELEVANT


Major Challenge:

Meeting Expectations with Analytics

8+GROWING

INTERACTION

CHANNELS

ACCESS TO DATA

SOURCES

THE ANALYST

BOTTLENECK

HOW TO

OPERATIONALIZE


Businesses should

demand the full view:

micro level insights

on masses of individual

interactions, alongside

macro level understanding of the

customer’s entire

journey.


The interactions

the customer has

with the enterprise

in order to complete

a specific goal

WHAT IS THE

CUSTOMER JOURNEY?


Demo

25


Contact Us

www.nice.com/analytics

@Nexidia

26

Man, machine and the customer experienceSeptember 2018

4 AI prediction dangers

MIT Technology Review: The Seven Dedly Sins of AI

Predictions Rodney Brooks - October 6, 2017

Overestimating

and

underestimating

Imagining

magic

Performance

versus

competenceSpeed of

deployment

https://www.technologyreview.com/s/609048/the-seven-deadly-sins-of-ai-predictions/

“Humanity is acquiring all the right technology for all the wrong reasons.”

R. Buckminster Fuller

Iconic firms are 20%

more likely to have a CX-driven strategy than an efficiency-based one

“There is no customer experience without anemployee experience.

You can invest everything you want in technology but nothing will happen if you do not care about people.”

Richard Branson

32Genesys confidential and proprietary information. Unauthorized disclosure is prohibited.

Distraction

o Thousands of calls to your contact

center

o Millions of online visits

o Can you identify and predict when and

how to engage with your customers?

o Can you shape their journeys for the best

outcomes for both you and them?

The challenge

Knowledge

1. MonitorSegment customers and apply real-time

journey analytics on your website

4. AlertNotify sales and lead development reps of hot

leads or important visitors via Slack or PureCloud

5. InformProvide insights about the customer’s journey to

the sales rep or agent’s omnichannel desktop

2. AnalyzeUse AI & machine learning to determine the

outcome probability for business goals

3. EngageIdentify when to

proactively engage with

chat, callback, or content

offer at the right time

6. LearnAutomatically adjust and

improve the models over time

Addressing the distractions

36

Challengeso Smyths is the largest independent toy retailer in the UK

& Ireland with 100 store locations and 20 million website visitors per month.

o They were concerned about increasing online sales conversions.

o Altocloud software was used to focus on identifying and engaging those customers with large shopping cart values who were at risk of abandoning.

o 30% reduction in cart abandonment

o 3% increase in high-value conversions

Solution

Results

37Genesys confidential and proprietary information. Unauthorized disclosure is prohibited.

For a full demonstration of Genesys Altcocloud click here

To try Genesys Altocloud free for 30 days click here

Or to download our white paper: Analyzing and shaping

customer journeys click here

https://try.genesys.com/plays/digital-sales-and-retention/

https://www.genesys.com/webinars/genesys-altocloud-demo?utm_medium=referral&utm_source=Play4LP&utm_campaign=Play_4_-_Altocloud_Sales_and_Marketing

https://www.genesys.com/resources/analyzing-and-shaping-customer-journeys?cid=7010d000001G9KC

ROUNDTABLE

September,

2018

Q&A

Michael Dwyer ,

Vice President,

Research, CallMiner

www.callminer.com

Troy Surdick, Senior

Product Manager,

NICE Nexidia

www.nexidia.com

Joseph Ciuffo, Lead

Demonstration

Consultant, Technical

Sales, Genesys

Brendan Dykes,

Global Director

Product Marketing,

Genesys

www.genesys.com

Analytics –

Speech, Text,

and AI

roundtable michael dwyer , troy surdick, senior joseph ...€¦ · segment customers and apply...

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