#sngular1112

1. Voice of Customer
in a rapidly changing
environment
Jose C. Gonzalez
jgonzalez@sngular.team

2. Pillars of a Customer Centric Culture
 Better customer insights
 Superior value proposition
 Better customer experience
Mohan Sawhney
Kellogg School of Management
2

3. Customers are very active on
social media
call centers
emails to support sites
responses to survey sites
online reviews
Making sense of the information overload 3

4. “Interest rates associated to the credit card
are only too high”
.

5. “Fed up with the “hold the line please” at the
call center”
.

6. “A friend of mine got free WiFi
with BankX. Have you got
something like that?”
.

7. “One of the many reasons I hate #BankX.
Bank is supposed to open at 9am.
Doors open at 9:05 and then
only one teller is available”

8. “The reception staff are very rude
and speak to you as if you do not know
what you are on about”
.

9. Businesses that listen can…
9

10. improve retention and decrease churn
10
Businesses that listen can

11. spot them on their customer journey
to uncover sales opportunities
11
Businesses that listen can

12. discover what customers think about my brand, my
products…
12
Businesses that listen can

13. detect and leverage opportunities to boost
recommendations
This is what NPS is about
13
Businesses that listen can

14. Businesses that listen can
detect problems
14

15. Businesses that listen can
know how to help customers
15

16. detect reputation threats
16
Businesses that listen can

17. avoid consumer complaints
17
Businesses that listen can

18. figure out what competitors are doing
18
Businesses that listen can

19. The good news!
19

20. Good news!
we humans are very good at extracting meaning and
insights from texts
20

21. The bad news!
we don't scale well!
21
37 million books If I read
one book
a day
60.000
YEARS
!!!!

22. What if…
Oh, I'm gonna try with a little help from my friends
22

23. Semantic technology is here to help us scale when
extracting value from human texts and voices
analyzing massive data quickly
the way a person would
23

24. How?
24

25. 1. Voice of the Customer Analytics
• Customer Journey (buying signals, loyalty, advocacy)
• Corporate reputation, brand personality
• Alarms: Reputation crisis / Customers requiring attention
• Product and Services (aspect-oriented sentiment analysis)
• Discovery of desirable product attributes
• Discovery of new voice
• Customer demographics and Customer segmentation
• Customer channels
25

26. Semantics can also help at…
26
BTW

27. 2. Voice of Employee is almost like VoC
– Internal data:
• Employee satisfaction surveys
• Training evaluation forms
• 360-evaluations and assessment forms
• Year-end employee reviews
• Exit interviews
• Focus group responses
• Live feeds
27

28. – External data:
• External/benchmarking data
• Most up-to-date, easiest-to-access data on employees’ work
history, accomplishments and competencies on their public
professional profiles (LinkedIn, GitHub, About.com,
Indeed.com...)
28
2. Voice of Employee is almost like VoC

29. Listen to the real needs of the citizens and find the
way to incorporate them into decision making
29
3. Voice of the Citizen = VoC

30. Identifying patients' needs, values, preferences, and
expectations in order to deliver an exceptional
experience
30
4. Voice of Patient

31. Semantics can also help at…
31
BTW

32. U.S. Dodd-Frank (2010 law)
all electronic communications at financial institutions—email,
chats and instant messages—should be monitored
32
Other areas: Compliance and fraud detection

33. How to perform TEXT analytics?
A five steps methodology
33

34. Identify a problem worth solving:
 Bottom line: reduce costs, reduce complaints, reduce human
classification errors,
 Top line: solve problems, anticipate threats, new opportunities…
34
1.

35. Set up data reliability
35
2.
Data sources
Data access
Data security
Data cleaning

36. Determine what needs to be extracted:
36
3.
 Entities
 Themes-concepts
 Sentiment
Time to perform some intelligent tuning

37. Analytics proper
37
4.
 Link structured and unstructured data
 Insight discovering
 Predictive analytics

38. Kaizen: continuous improvement
38
5.
 Plan
 Implement
 Measure
 Tune

39. And finally, text analytics tools
39

40. meaningcloud.com
 SaaS business
 Text analytics APIs
 Customization
40

41. meaningcloud: for developers or analysts
Love
34%
Fear
11%
Joy
11%
Disgust
11%
Neutral
33%
Emotion
8.2
7 7.5
6.7
5.5
6.3
Top Products & Services by average
satisfaction level
0% 50% 100%
Survey
Twitter
Web
Call Center
Offices
Sentiment by source
P+ P NEU N N+ NONE

42. Selected references
 VoC analysis in Banking: ING Direct
 Social media monitoring: SocialBro
 Pharma: Pfizer
 Defense: Thales
 Market intelligence: Digimind
 Media: Unidad Editorial / Vocento / Prisa
 Safety: Telefonica

43. Spain | United States | Mexico
www.sngular.team
@sngular_team