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3	Strategies	
for
Business	
Innovation	
with
Sentiment	
Analysis	(ML)
Rahul	Ramachandran,	PMP®,	MBA
Amancio	Bouza,	PhD,	ipt,	Innovation	Process Technology	AG
Cloud	Days	2018,	Luzern
2
The	Challenge..
There	has	been	a	paradigm	shift	across	industries
19601900 1990 2010
The	age	of..
MANUFACTURING
INDUSTRIAL	REVOLUTION
What	triggered	it..
The	paradigm..
OWN	PRODUCTION,	
OWN	THE	MARKET
DISTRIBUTION
GLOBALIZATION
&	FREE	TRADE
OWN	DISTRIBUTION,	
OWN	THE	MARKET
INFORMATION
INTERNET
OWN	INFORMATION,	
OWN	THE	MARKET
This	is	no	rocket	science	– Happy	customers	return	and	refer..
..and	what	are	today’s	customers	expecting
..but	speed	alone	doesn’t	cut	itSpeedy	contact	and	response
So	we	want	to	respond,	but..
“Customer	Experience”	
is	EVERYTHING
What	is	the	biggest	challenge	for	
businesses?
So	we	want	to	respond,	but..
“Customer	Experience”	
is	EVERYTHING
Too	many inputs
..and	too	many	platforms	to	read	from
Too	many feedback	
platforms
Need	to	
leverage
“Customer	Experience”	
is	EVERYTHING
BUT
HOW?
The	Opportunity..
In	every	challenge	lies	an	OPPORTUNITY
Customer	Retention
Product	Development
Competition	Analysis
Business	Potential
To	harness	the	potential	– BIG	Data	&	Machine	Learning	(ML)
• Machine	learning is	the	subfield	
of	computer	science	that	gives	
computers	the	ability	to	learn	
without	being	explicitly	
programmed	(Arthur	Samuel,	
1959).	...
• Machine	learning is	closely	
related	to	(and	often	overlaps	
with)	computational	statistics,	
which	also	focuses	in	prediction-
making	through	the	use	of	
computers.
Machines	are	now	able	to	process	natural	human	language	
and	also	derive	the	human	sentiment	within
12 Source:	Stanford	NLP
Machines	are	now	able	to	process	natural	human	language	
and	also	derive	the	human	sentiment	within
13
Natural	Language	Processing	(NLP)	is	very	a	HOT	topic
So	how	did	we	approach	it..
So	how	did	we	approach	it..
..using	Microsoft’s	Azure	ML	and	Cognitive	Services
18
Wrapping	up	– What	we	achieved..
A	detailed	analysis	of	our	customer	feedback
19
Sentiment:	Positive
Entity:	Michael	(Person)
Entity:	Luzern	(Location)
Input:	“Micheal was	a	great	guide	and	we	enjoyed	Luzern	city	very	much”
In	our	initial	POC,	we	received	a	high	accuracy
20
79%accuracy 75% precision 73% recall
“Word	cloud”	on	which	location	are	being	talked	about
21
Enables	business	to:
- Quickly	focus	on	the	“most”	
talked	locations
- Setup	effective	communication	to	
resolve	most	issues
- React	FAST
- Incorporate	feedback	to	Product	
Development
- Understand	what	your	market	
peers	are	doing	right
Contact
Rahul	Ramachandran
Director	Business	Solutions
Viking	Cruises
rahul.ramachandran@vikingcruises.com
22
Amancio	Bouza
Principal	Consultant
ipt,	Innovation	Process	Technology	AG
amancio.bouza@ipt.ch
famous for integration

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