How to turn mult i-language customer

feedback into actionabl e information

in one language?

CUSTOMER AWARENESS

PURCHASE

SUPPORT

CHURN

UPSELL

Facebook Twitter

Product reviews

Customer forumsSurveys

Web analyticsOnline feedback

Online chatSurveys

Customer service centersTransactional dataOnline feedback

Call centerCRM SystemsSurveysSocial media

Customer reviewsEmails Research

N P S C O R E HA S D R O P P E D I N O NE P R O D U C T L I NE

W H Y ?

shipping

packaging

damage

0 400 800 1200 1600

negative neutral positive

P r o b l e m s w i t h

l o g i s t i c s

“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."

A c t u a l c u s t o m e r c o m m e n t s ?

LANGUAGE RECOGNITION

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)

“Please, send my purchase in a stronger container next time. My sunglasses were damaged.”

MORPHOLOGY SYNTAX

1. 2. 3.

SEMANTICS

send: a keyword related to the topic shipping!stronger container: a keyword related to the topic packaging!broken: a keyword related to the topic damage

SENTIMENT4. 5.

“Please, send my purchase in a stronger container next time. My sunglasses were damaged.”

English

SEMANTICS

toimitus: a keyword related to the topic shipping!kestää: a keyword related to the topic speed of service!vahingoittuneet: a keyword related to the topic damage!

SENTIMENT4. 5.

"Ensinnäkin toimitus kesti yli kolme viikkoa ja lisäksi tilaamani aurinkolasit olivat vahingoittuneet."

Finnish

SEMANTICS

emballage: a keyword related to the topic packaging!

SENTIMENT4. 5.

“Vos emballages sont trop fragiles”

French

PRESENTATION6.

shippingpackaging

damagespeed of service

ordersunglasses

beltshats

bags

0 400 800 1200 1600

negative neutral positive

E T U MA

L A N G U A G E

T E C H N O L O G Y

I N A

N U T S H E L L

Ten languages

Developed from the 80's: University of Helsinki, Connexor, Etuma

Artificial intelligence: grammars, rules, lexicons and ontologies

Number of ontologies for different industries and functions

Over a thousand topics in each ontology

Hundreds of keywords in each topic

Thousands of feedback messages analyzed in seconds

e t u m a i n s i g h t p o r t a l M A K I N G S E N S E O F C U S T O M E R E M O T I O N S

www.etuma.com