Etuma provides a solution for analyzing unstructured customer feedback to enhance decision-making and predict consumer behavior. By employing machine learning and computational linguistics, Etuma transforms open text into actionable information, allowing companies to quickly adapt to trends and reduce customer churn. The service enables real-time reporting and effective analysis across various feedback channels, leading to increased customer loyalty.

1. Etuma
Customer
Feedback
Analysis
Making sense of
customer emotions
Matti Airas, CEO and Co-Founder, Etuma
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2. 2
Companies Are
Facing Ever
Increasing
Competition
• Brick vs. click
• Competition crossing borders
• Consumer trends are hard to
predict and short lived
• Consumers tend to be less loyal

3. There are things that your
customers would like to tell
you: selection, emerging
trends, operational
problems…

4. If you only
listened
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5. 5
80% of all Data is
Unstructured
“Vos emballages
sont trop fragiles”
Please, send my
purchase in a
stronger container
next time.
My sunglasses
were broken."
“Ensinnäkin
toimitus kesti yli
kolme viikkoa ja
lisäksi tilaamani
aurinkolasit olivat
vahingoittuneet."
“Your website does
not have the
information to
make a purchase
decision”

6. Etuma turns
open text
into
structured
intelligence
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7. 7
Etuma has solved the key
problems in customer
feedback analysis
Real-time
Reporting
Actionable
Information
Ambiguous
Language
Results can be used
directly in decision
making and are
consistent over time for
trend analysis.
Results are available
immediately after the
customer submits the
feedback.
Language is a living thing. Etuma
uses a combination of machine
learning and manual optimization
work by Etuma computational
linguistics experts to keep the
system always up to date.

8. 8
Text to
Statistics

9. 9
language the same way a
TOPIC-LEVEL
SENTIMENT
SEMANTICS
Etuma understands
SYNTAX
human does
MORPHOLOGY
PART OF
SPEECH
LANGUAGE
RECOGNITION
Optimized for
customer
experience!
Relevant and consistent
Optimized for customer
experience
Relevant and consistent
analysis results
Fast adaptation to any
feedback channel and type
analysis results!
Fast adaptation to any
feedback channel and type!

10. LANGUAGE
RECOGNITION
MORPHOLOGY&
PART OF SPEECH SYNTAX
“Please, send my purchase in a stronger container next
time. My sunglasses were damaged.”
ENGLISH
please (ADVERB)
send (VERB)
my (PRONOUN)
purchase (NOUN)
in (PREPOSITION)
a (ARTICLE)
strong
(ADJECTIVE)
container (NOUN)
send (VERB PHRASE)
my purchase
(NOUN PHRASE)
stronger container
(NOUN PHRASE)

11. 11
Connect
Feedback
Channel(s)
Analyze and
Enrich With
Structured
Information
Correlate, Model
and Recognize
Patterns
Visualize,
“Taskify”

12. Easy to
implement
cloud service
12
1.
Optimize
analysis based
on historical
data.
2.3.
Define roles
and scenarios.
Create users,
design
reports.
Connect
feedback
channels
using web
interfaces.
All you need to do is
participate in one workshop
and implement the
connectors.

13. 13
Lower Churn -
Increased loyalty
NEED
• Lot of customer data but inability
to predict when customers are
about to churn or reduce buying
SOLUTION
• Predicting which customers are
about to leave the service or reduce
buying and do personalized
communication.
RESULTS
• Reduce churn first year 1%, next
year 5%, 3rd year 10%

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Thank You!
To continue discussion please contact
matti.airas@etuma.com
All picture under https://creativecommons.org/licenses/by-nd/2.0/