Post on 16-Aug-2020
transcript
Etech Global Services – Booth #14Tuesday October 9th | Workshop B | 10:30 AM – 12:30 PM
Jim Iyoob, Chief Customer Officer, Etech Global Services
Shawndra Tobias, Sr. Director Customer Experience, Etech Global Services
Jeffrey Arnold, Sales Chat Operations Consultant, Verizon Wireless
Professor Customer: Empower Your Customer to Teach You CX Delivery they Crave
www.etechgs.com | Confidential
Jim IyoobChief Customer Officer
jim.iyoob@Etechgs.com
936.371.2640
about.me/jiyoob
@jiyoob
facebook.com/jim.iyoob
linkedin.com/in/jimiyoob
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Agenda
• Who is Etech • What is Customer Experience • How to approach implementing CX today?
• Voice of Customer and how to use it?• What and how do you measure it – Tools?
• Human Intelligence meets Artificial Intelligence • Tip of the Iceberg
• Are you really listening?• Case Study • Fun and Prizes – Q&A
• How to get a 360-Degree View of Customers
• Why focus on CX & How to Improve it
• Provide Better Coaching for Better Outcomes
• How to take unstructured data and make it actionable utilizing AI & HI
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Top Takeaways
Etech’s Commitment To Culture
Servant Leadership Approach
Assume AccountabilityPeople Driven Philosophy
People First Focus Performance Development
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JUNE3 Days before the closing of the
Nacogdoches operations, Dilip Barot, Matt Rocco and the other investors from Etech
acquire the asset of the call center from Bellsouth Saving over 400 much needed jobs
SEPTEMBERIn addition to the headquarter center in Nacogdoches, Etech opens its back-office/ BPO center in Gandhinagar, India and now provides solutions for 4 major Telecom clients
2002Bell South made
a decision or divest its
internal call center asset in
Nacogdoches Texas
2004Launched Lufkin center with 325
Seats and 500 employees
2006Launched
Vadodara, India center with 200
Seats and 13 clients
2008Launched Rusk center with 100 Seats and 16 clients. Etech reached
1500 Employees
2010Launched Jamaica
center with 150 Seats and launched
Software and Development
services
2012Launched Dallas center
with 220 Seats
2014Launched Florida center with
150 Seats Etech launched Chat and email product ICE and software Implementation
service
2016Currently
serving 31 clients
20032018Etech family reached over 3000 employees and together serving around 43 clients
ETECH GREW FROM 400 TO MORE THAN 3000 EMPLOYEES
NO MERGERS NO ACQUISITIONS
Etech’s Journey
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Customer Engagement SolutionsInbound/Outbound, Customer
Service, Tech Support
Etech Technology SolutionsSoftware/Application Development
Custom Reporting (Internal/External)
Etech’s Business at a Glance
Etech InsightsActionable Insights for Total Quality
Management to enhance operational efficiency & customer experiences
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Etech’s Clients
Cable
Retail
Telecommunication
EducationInsuranceEnergy
Travel
Finance Real Estate
Banking
HotelInternet
Customer Experience Management
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Evolution of Trends
Marketing
Pre 1970s
70s-80s
80s-90s
99-2007
‘07-’15
2015+
Face to Face
Letters
Phones
Chat / Email / Web
Social Media
Mobile Apps
Now
IoT
Customer Service
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81%
of customers first turn to self-service to
address issues
End of an Era
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86%of buyers will pay more for a better customer experience
@!#%$@!!!
1/26Only 1 out of 26 unhappy customers complain
91%Of non-complainers will simply leave
66%Consumers switch brand due to poor
experience
75%Brands do not know what engagement is, but are measuring “it”
=It takes 12 positive customer experiences to make up for ONE negative customer experience
42%Of agents are unable to efficiently resolve customer issues due to disconnected systems, archaic user interfaces, and multiple applications
70%Companies that deliver the best in class customer experience “USE” their customer’s feedback 70% of the time
Versus industry average of 50%, and 29% for those who lag on CX delivery
Impact of Customer Experience
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What is Customer Experience?
PROCESS
(VIABILITY)
TECHNOLOGY
(FEASIBILITY)
PEOPLE
(DESIRABILITY)
Process Innovation• Efficiency• Profitability• Consistency
Functional Innovation• Product Features• Web Presence• Automation
Emotional Innovation• Branding• Relationships• Marketing
Customer Experience• Interactions• Product/Services• Communication
The Perception that the customers have of their engagement with the company
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CUSTOMER DISLOYALTY
CUSTOMER EFFORT
RepeatContacts
Channelswitching
Transfer/ Repeat info
CUSTOMER’S FEELING
Roboticservice
Hard policiesor procedures
Hasslefactors
==
HIGH EFFORTEXPERIENCE
LOW EFFORTEXPERIENCE
9%
96%
Why make it “Effortless”?
SPREAD THE WORD!
78%
BUY MORE!!
68%
REFUSE TO BUY OTHER PRODUCTS
54%
Effortless Customer Service is the Best Customer Experience
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Having the option to pay a bill online.
How easy it is to pay a bill online.
How well an in-store representative answers a customer’s question.
The ease of navigating the store, the availability of desired products, the range of options available, and the speed of checkout.
How quickly a customer’s issue is resolved.
Why the customer had an issue or question to begin with, and how often they have issues with your business.
How a car dealership’s service center representative communicates to a customer.
The issue that the customer is having with the vehicle and how he/she feels about having to bring it in.
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Voice of Customer
1%
70%
of customer voice data is actually understood
of feedback (Voice of Customer) is shared via phone calls by your consumers!
1% of actual Voice data of VOC is listened to by companies
30%of other VOC is not fully understood due to different systems or lack of tools to integrate all data together
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The Big Rocks
My strategy for improvingcustomer satisfaction is
not producing the desired results
I need to create an internal environment
that nurtures and sustains continuous
customer experience improvement
I need to prioritize the vitalfew versus the trivial many
actions to improve customersatisfaction, loyalty, and
drive business results
I’m required to create a business case to justify
resources needed to achieve meaningful
progress
I’m struggling to make sense of multiple customer
data points... I need to create an integrated view
of all this info
I have a lot of data, but notsure if I’m measuring and
acting on the right things atthe right time
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Maximized Learnings
LISTEN – LISTEN - LISTEN REDUCE AREA OF FAILURES
FIX CUSTOMER ISSUES
LEVERAGE TECHNOLOGY
LEARN WITH H.I. SCALE WITH A.I. GET THE EXPERIENCE
AI Without HI Can Be Disastrous
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www.techrepublic.com/article/the-10-biggest-ai-failures-of-2017/
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Where AI needs HI?
Gather & Prepare Data
Train Model
Apply Model
Capture Feedback
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Tip of the Iceberg
As few as 2%consumers will bother
to complete a questionnaire /
survey
The sample size of QA in contact center is around
2%-5% (Higher the number of calls, smaller
the sample size)
Less than 1% companies involve
in Mystery Shopping.
(Mostly Retail)
Social Media Management while
responded by most, the VOC is not used for business decisions
420BWords are spoken on
recorded calls across the call center
45.4BInbound calls to call centers
per year
92%Of customer service
transactions happen over the phone
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What do you measure?
OTHER TOOLS:
How would you rate this interaction?
CSAT SCORE
EFFORT SCORE
% EASY MINUS % DIFFICULT
AGENT QUALITY
Overall QA score/rating for an agent
CUSTOMER LOYALTY
% PROMOTERS MINUS % DETRACTORS
The company made it easy for me to handle my issue
✓ Greeting?✓ Verified Email?✓ Polite throughout the call?✓ Build Rapport?✓ Assurance of help?✓ Set the right expectations per
policy?✓ Tried to Show Empathy✓ Took Ownership of the issue?✓ Answered all questions?✓ Branding?
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What do you get?
AGENT AAudits: 16/957 calls
CSAT Score: 92%Effort Score: 35%
NPS Score: 25
AGENT BAudits: 16/1021 calls
CSAT Score: 69%Effort Score: 91%
NPS Score: 75
AGENT CAudits: 12/782 calls
CSAT Score: 73%Effort Score: 20%
NPS Score: 46
AGENT DAudits: 14/840 calls
CSAT Score: 89%Effort Score: 66%
NPS Score: 72
%QUALITY
SCORE
GOODBAD
TAGCALL TYPE
DO’sDON’Ts
AGENTFEEDBACK
CIRCLECOACHING
LIMITEDINSIGHTS
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What do you miss?
$$$
REVENUE DRIVERSPREDICTIVE ANALYTICS
VOICE OF CUSTOMER BEHAVIORAL IMPACTSTARGETEDCOACHING
Shawndra TobiasSr. Director Customer Experience
Shawndra.Tobias@etechtexas.com
936.371.1817
facebook.com/shawndra.tobias
twitter.com/shawndra_tobias
linkedin.com/shawndra-tobias
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Steps to Implement a CX Strategy
LISTEN
IDENTIFY
ANALYZE
IMPROVE
PREDICT
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Traditional Approach
Agent Opportunities- High AHT- Dead Air in between- Incorrect Hold Procedure- Reason for Call – Bucketing via call
dispositions- Did the agent cross sell / upsell?
Customer Experience Approach
Traditional QA Insights +- WHY are customers calling?- What was satisfaction level for the customer?- Did the customer share high effort experience?- Was this an FCR? Was there a Self-Serve
opportunity?- Did the customer use other tools before calling?
Said & Unsaid
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What works!
-6% -1% 4% 9% 14% 19% 24% 29%
C: How Do I?
Military/Government
Partner E
Bereavement
Partner D
Call to Add Baby
Web Support Walk-Thru
Cust. Upgrade
Repeat Information
Partner C
C: Frustration
Partner B
Trying to Use Miles
Refund
Channel Switch - Email
Proactive Guidance - Do Online
Trying to Use Card
Unused Credit
Partner - Other
Partner A
Calling to Book
A: Effort Driver B
Voucher
Apply Credit
Paper Voucher/Discount
Proactive Guidance - Education
Ask For Sale
A: Effort Driver A
A: Effort Driver C
16.3
52.1
Avg Rate Opportunity
Confirmed Conversion Ratebased on this sample
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Proactive Improvement in:
People:- Agent Performance- Overall Communication- Customer Expectations
Process: - Enterprise Systems- Policies and Procedures- Production and Marketing
Technology:- Self Serve Options- Support Delivery- Service Delivery
Fix what matters!
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Industry: Subscription Services
Finding 1: When a customer is offered a subscription service that they do not use, Agent use FREE Trial as a rebuttal for 90% of the time
Finding 2: 85% of these customers churn within the free trial period
You have a free 90 day trial
I do not listen to lot of Orange Music
Controlling Outcomes
Analytics
Predictive Analytics
Prescriptive Analytics
What happened?
What will happen?
How can we make it happen?
Case Study - Exploring The Data
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Enterprise wide Data:168,771 Calls ingested
2 million Spoken wordsTranscribed for both agent and customer side with 140+ categories
Charts and trendsCreated within the AI tool based on dates, times, markets, vendors etc. (Metadata)
SO HOW TO USE IT?Primary challenge is to how to utilize all these amazing insights to get targeted business decision making done!
Now What?
Goal: 30%
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MTD Conversion: 29%
25
39
37
73
41
05
32
34
22
33
32
78
34
53
37
63
35
63
40
19
30
76
21
96
35
02
34
27
31
88
31
63
33
36
29
90
22
37
30
82
31
04
30
36
30
38
30
47
25
15
19
97
31
04
31
43
28
37
28
62
31
44
10
92
14
95 15
75
10
09
87
8
14
18
14
09 14
96
15
45 1
62
9
11
88
10
11
15
25
14
46
13
62
12
65
14
63
10
46
87
0
13
23
12
69
13
44
12
37
12
42
99
0
88
9
13
84
13
37
12
63
12
00 13
11
30%
28%28%
24% 28%
30%29%
28%
30%29%
28%
31%30% 30% 30%
29%
31%
26%
28%
30%29%
31%
29% 29%
28%
31% 31%30%
31%30% 30%
0%
5%
10%
15%
20%
25%
30%
35%
0
1000
2000
3000
4000
5000
6000
Non-converted Calls Converted Calls Conversion % Benchmark - 30%
• Etech filtered the total volume of 168,771 calls using the “ Number of Adult – Verification” Category to determine the potential sales calls
• Total Call Volume Represented in the Graph: 135,495• Total Calls Converted: 39,511
Customers & Agents
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No Sale Break Down – Enterprise Level
Total Call Volume : 135,495
Sale, 39511 No Sale, 95984
54
34
9
10
98
2
16
76
0
14
01
5
15
06
2
24
32
7
15
96
7
27
01
52
18
42
93
48
83
64
49
29%25%
31% 31%
32%
27%
Benchmark , 30%
0%
5%
10%
15%
20%
25%
30%
35%
0
10000
20000
30000
40000
50000
60000Call Outcome - Vendor Wise Analysis
Potential Sales Calls Sold Conversion % Benchmark
Vendor 1 Vendor 2 Vendor 3 Vendor 4 Vendor 5 Vendor 6
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Successful Behaviors
• Co-efficient Value shows a correlation between the observed outcomes and the observed predictor values. The value of co-efficient is always between +1 and –1. The closer it is to +1 the stronger the correlation.
• This Analysis statistically proves the hypothesis that Asking for Sale, Providing Rebuttals, & Creating urgency and directly correlated to the conversion on an Enterprise Level and can be used to fuel a predictive model
10816
10816
271830%
30%
40%
Crucial Behaviors & Success Probability
Ask for Sale Urgency Objection Handeling
Inner Circle: Total Population
Outer Pieces: Success Percentage of the
Behavior
Co-Efficient Value: 0.9435
Statistical Success Rate: 30%
Statistical Success Rate: 40%
Coefficient Value: 0.7029
Co-Efficient Value: 0.7152
Statistical Success Rate: 30%
Note: This model is based on the data collected in the month of July. These analysis will be run quarterly to ensure we have enough data to observe any new patterns or see any visible deviations from the last output.
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No Sale Calls Vs Crucial Behaviors – Creating Urgency
Vendor 1 did not create urgency on 78% of the call resulting in a potential revenue loss
of $1,787,400Vendor 1, 22%
Vendor 3, 57%
Vendor 6, 58%
Vendor 4, 61%
Vendor 2, 65%
Vendor 5, 66%
Vendor Wise Comparison - Creating Urgency on No Sale Calls
Vendor 1 Vendor 2
Vendor 3
Vendor 4 Vendor 5
Vendor 6
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No Sale Calls Vs Crucial Behaviors – Asking For Sale
Vendor 3 lost $552,000 in potential
sales by not asking for sale on 80% of
the No Sale calls
Vendor 3, 20 %
Vendor 1, 38%
Vendor 4, 49%
Vendor 2, 50%
Vendor 5,,52%
Vendor 6, 59%
Vendor Wise Comparison - Asking for Sale on No Sale Calls
Vendor 1 Vendor 2
Vendor 3
Vendor 4
Vendor 5
Vendor 6
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Agent Coaching Packet
Primary opportunity was derived based on the impact that behavior will have on the conversion
Asking for Sale - Impact Bucket
Creating Urgency - Impact Bucket
78%
78%
76%
74%
71%
65%
65%
62%
61%
57%
56%
56%
56%
55%
53%
51%
49%
45%
32%
22%
22%
24%
26%
29%
35%
35%
38%
39%
43%
44%
44%
44%
45%
47%
49%
51%
55%
68%
Kemar Morrison
Tevin Daniels
Adrian Samuels
Tennica Powell
Demar Tomlinson
Shanese Anderson
Lionel Reid
Shelly Whyte
Conroy Field
Akeem Lawrence
Trevaun Hamilton
Matthew Brown
Sydonnie Martin
Cleon Dougherty
Georgina McIntosh
Shekera Bicarie
Malik Thomas
Samantha Campbell
Jardine Lawrence
Ask for Sale Didn't Ask for Sale
65%
62%
52%
50%
0%
35%
38%
48%
50%
100%
SteveWilliams
Sanoy Clarke
Deano Maine
TashayCampbell
Samuel Ellis
Create Urgency
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Drive Quick Improvement
Creating Urgency functioned as a
successful rebuttal for the top 3 objections
Lowest price rebuttal was successful 23% of the
times when customers objected to the price being offered
2%
7%
7%
15%
26%
36%
2%
3%
8%
13%
23%
30%
1%
3%
4%
8%
14%
19%
Holiday
Stay onPhone
CheckOther
Property
FreeCancellati
on
LowestPrice
Urgency
Top 3 Objections Vs Successful Rebuttals
Consult withsomeone
Rates too high
Call back later
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After understanding what behaviors drive success – We can cross-train agents to improve performance
30%
70%
68%
48%
54%
45%
42%
46%
19%
59%
50%
54%
19%
48%
45%
36%
15%
58%
0% 10% 20% 30% 40% 50% 60% 70% 80%
Angela WS3-Jenkins
Reynaldo Nelson
Chaira Ceballos
Dawn WS3-Turmenne
Vielka Alleyne
Winston Archibold
Provide Rebuttal% Ask for Sale% Create Urgency%
31%
55%
44%
48%
40%
52%
0% 10% 20% 30% 40% 50% 60%
Average%
Replicate Successful Skills
23106
24261
26572
30038
34659
$2,163,200
$2,367,702
$2,480,400
$2,593,180
$2,705,797
$2,000,000
$2,100,000
$2,200,000
$2,300,000
$2,400,000
$2,500,000
$2,600,000
$2,700,000
$2,800,000
100015002000250030003500400045005000550060006500700075008000850090009500
10000105001100011500120001250013000135001400014500150001550016000165001700017500180001850019000195002000020500210002150022000225002300023500240002450025000255002600026500270002750028000285002900029500300003050031000315003200032500330003350034000345003500035500360003650037000
Current Improvement 5% Improvement 10% Improvement 15% Improvement 20%
Asking for Sale Creating Urgency Revenue
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Predictive Model: Successful Behaviors increase Revenue
Present Rate
$2,367,702
+5% Improvement
+10% Improvement+15% Improvement
+20% Improvement
$2,480,400 $2,593,180$2,705,796
By Improving Asking for Sale and Creating Urgency on an
enterprise level by 20% in
the sample set of 44,374 calls, our predictive model forecasted an increase of
$542,597in the revenue
Note: This model is based on the data collected in the month of July. These analysis will be run quarterly to ensure we have enough data to observe any new patterns or see any visible deviations from the last output.
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APITethr
Etech Database
Parse JSON data based on metadata and
field/categories required
Tethr JSON data
SQL Query
Converts data through SQL queries on “conditionality
mapping of categories” into “Insights Form” tabular format
QEval Database
Call Uploading Call Processing
Tabular format converted into QEval Evaluation Form/Reports
Still want a Score?
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Effectiveness Rating
Evaluated 17k plus calls on scorecard
to give detailed output using AI
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What Happens When You Underestimate the Importance of Transitioning Technology?
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In a world driven by tech…Your people matter more than ever.
Job looks the same butyour customer expectations have changed.
Machine learning is lost without People
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Record your Calls Capture Metadata Define ObjectivesMeasure Effectiveness
Monitor & Evolve Ongoing Refinement
We focus on CX, YOU Decide ToolsIMPLEMENTATION STEPS
Paper Form Excel
Artificial Intelligence & Human Intelligence
TOOLSVolume, Commitment to Customer Experience
DECIDING FACTORS
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Volume Vs Cost (Etech AI)
15,905
31,110
6,075
22,555
51,805
122,490125,490
100%
51%
262%
71%
31%
13% 13%
0%
50%
100%
150%
200%
250%
300%
0
20000
40000
60000
80000
100000
120000
140000
Oct-17 Nov-17 Dec-17 Jan-18 Feb-18 Mar-18 Apr-18
Cost Vs FTE Vs Volume (Major QA Campaign)
Call Count Cost/Audit%
24
20
1413
11
6 6
0
5
10
15
20
25
30
FTEs
Don’t Gamble WithYour Customer Experience
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1. Does your Quality team include CX SMEs?
2. Are your Quality and Training program integrated?
3. Do you have less than 20 parameters on your scorecard?
4. Are you linking Quality with corporate objectives?
5. Are you utilizing your customer to define world class quality assurance?
6. Are your agents bought into the Quality program?
7. Can you prove your Quality Program produce ROI?
8. Does your C-Suite describe your QA program as a “Valued Asset”?
9. Do you leverage your QA results when making process changes?
10. Do you have a close loop feedback process to improve training?
Yes No
Yes No
Yes No
Yes No
Yes No
Yes No
Yes No
Yes No
Yes No
Yes No
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Don’t Gamble WithYour Customer Experience
How Does Your Customer Experience Measure Up?
> 6 Come see us, we’re hiring!
3-5 How we can help you on your journey!
<3 Your Customer called, talk to us!
Yes
Yes
Yes
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Learn how Artificial intelligence isrevolutionizing the contact center.
Demo Drive: Wednesday 9:50 -10:50Book Signing: Thursday 9:50 am
Visit us at booth #14
Contact me at: Jim@etechgs.com