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Transforming
Now
_AI for smooth-running
contact centres
Customer Care
Udanda vel molore
nonsenitae. Et exerori
tinctat que niatum,
sitis sapienis.
Each year globally,
companies lose $300bn
due to poor CX
How much is
your firm
losing?
“SentiSquare AI
is a great saver
of people & time”
—Vojtěch Vycudilík
Cxpert @ T-Mobile
Udanda vel molore
nonsenitae. Et exerori
tinctat que niatum,
sitis sapienis.
AI-as-a-
Service
Since 2014
• 5 years on the market
(CZ,SK,PL,DE)
• Investors
Luboš Černý
Former CEO of eBanka
Michael Fehn
Former CEO of E.ON CZ
• StartupYard, E.ON :agile,
& Poland Prize alumni
doc. Josef Steinberger,
Ph.D.
Michal Konkol,
Ph.D.
Tomáš Brychcín,
Ph.D.
Most Precise NLP engine on the market:
1st & 2nd place at SemEval San Diego 2016
Dev Team
Tomáš Hercig,
Ph.D.
2 100+ citations in NLP
Solution
Portfolio
THE OLD WAY
Udanda vel molore
nonsenitae. Et exerori
tinctat que niatum,
sitis sapienis.
LEGACY
FILTER
MANAGER
?
FLOODS OF CUSTOMER-GENERATED TEXT
REPETITIVE
WORK
THE NEW
WAY
Udanda vel molore
nonsenitae. Et exerori
tinctat que niatum,
sitis sapienis.
LEGACY
FILTER
MANAGER
?
AI-
POWERED
ANALYTICS
FLOODS OF CUSTOMER-GENERATED TEXT
CREATING
VALUE+REPETITIVE
WORK
OR
Customer Care ops clean-up
1 INTELLIGENT ROUTING
• Query category & customer
identification
• Reduces handling time
2 AGENT JET-PACK
• Auto-fill suggestions based
on relevant past replies
• Increases agent productivity
3 NOTE-TAKING
• Automated summary generation into
CRM
• Saves time, boosts morale
4 PERFORMANCE &
COMPLIANCE
• Good/Bad interaction
recognition
• Upgrades agent training
5 CHURN ALERT
• Identifies churn candidates
• Reduces churn
TASK: Routing messages
It takes time to dispatch emails
(2 min 39 sec per email; 12 FTE per 500k emails)
SOLUTION: NLP-driven automation
Automatic dispatching to 280 queues
Accuracy: 1st attempt >70%; 2nd attempt >80%
Finding messages that matter
1,250,000
60 %
Every year, client center asks 1.250.000
customers for SMS feedback.
60 % clients text back
( >10,000 SMS / month)
?
Customers are glad to receive a reply –
but which ones should get it?
Dissatisfied
customers
Lucrative
customers
Churn alert
CHALLENGE: Difficult to identify churn candidates
OUR SOLUTION: Assessing churn risk based on data from past
interactions, picking out customers for extra care
BENEFITS: Reduced churn
Revealing what customers talk about and what they want improved
OUR SOLUTION: Identification of topics, keywords and sentiment — clearly visualized trends over time
Deep Insight
Read and classify one verbatim
Quarterly chart ready in
How would you use 120 MD?
Deep Insight: Delivering Value
Before
2 min 24 sec …………… ….
3 weeks
Tagging verbatims
Immediately …. …..
2 days
Increasing NPS
CLIENT: (retailer); TASK: Analyze 40k feedback pieces each quarter
• Our AI learns the language of any specific market
(e.g. German Automotive)
• Our AI learns the language of any specific channel
(e.g. SMS vs emails vs call transcripts)
• Solutions deployed in German, English, Czech,
French, Hungarian, Chinese, Japanese & more
• Language-agnostic tech: Words are reduced to
numbers and vectors – Our Natural Language
processing works in any language
Language
Independence
• Words occurring in similar contexts have similar
meanings
• Meaning = point in a high-dimensional space
• Unsupervised machine learning: No human input
Distributional Semantics
• XYZ is made of barley and hops.
• There is a pint of XYZ on the table.
• XYZ can make you drunk.
• Let’s go grab a XYZ!!
What is XYZ?
AI adoption:
Be the front-runner!
Let’s ride
together_

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AI for smooth-running contact centres

  • 2. Udanda vel molore nonsenitae. Et exerori tinctat que niatum, sitis sapienis. Each year globally, companies lose $300bn due to poor CX How much is your firm losing?
  • 3. “SentiSquare AI is a great saver of people & time” —Vojtěch Vycudilík Cxpert @ T-Mobile Udanda vel molore nonsenitae. Et exerori tinctat que niatum, sitis sapienis.
  • 4. AI-as-a- Service Since 2014 • 5 years on the market (CZ,SK,PL,DE) • Investors Luboš Černý Former CEO of eBanka Michael Fehn Former CEO of E.ON CZ • StartupYard, E.ON :agile, & Poland Prize alumni
  • 5. doc. Josef Steinberger, Ph.D. Michal Konkol, Ph.D. Tomáš Brychcín, Ph.D. Most Precise NLP engine on the market: 1st & 2nd place at SemEval San Diego 2016 Dev Team Tomáš Hercig, Ph.D. 2 100+ citations in NLP
  • 7. THE OLD WAY Udanda vel molore nonsenitae. Et exerori tinctat que niatum, sitis sapienis. LEGACY FILTER MANAGER ? FLOODS OF CUSTOMER-GENERATED TEXT REPETITIVE WORK THE NEW WAY
  • 8. Udanda vel molore nonsenitae. Et exerori tinctat que niatum, sitis sapienis. LEGACY FILTER MANAGER ? AI- POWERED ANALYTICS FLOODS OF CUSTOMER-GENERATED TEXT CREATING VALUE+REPETITIVE WORK OR
  • 9. Customer Care ops clean-up 1 INTELLIGENT ROUTING • Query category & customer identification • Reduces handling time 2 AGENT JET-PACK • Auto-fill suggestions based on relevant past replies • Increases agent productivity 3 NOTE-TAKING • Automated summary generation into CRM • Saves time, boosts morale 4 PERFORMANCE & COMPLIANCE • Good/Bad interaction recognition • Upgrades agent training 5 CHURN ALERT • Identifies churn candidates • Reduces churn
  • 10. TASK: Routing messages It takes time to dispatch emails (2 min 39 sec per email; 12 FTE per 500k emails) SOLUTION: NLP-driven automation Automatic dispatching to 280 queues Accuracy: 1st attempt >70%; 2nd attempt >80%
  • 11. Finding messages that matter 1,250,000 60 % Every year, client center asks 1.250.000 customers for SMS feedback. 60 % clients text back ( >10,000 SMS / month) ? Customers are glad to receive a reply – but which ones should get it? Dissatisfied customers Lucrative customers
  • 12. Churn alert CHALLENGE: Difficult to identify churn candidates OUR SOLUTION: Assessing churn risk based on data from past interactions, picking out customers for extra care BENEFITS: Reduced churn
  • 13. Revealing what customers talk about and what they want improved OUR SOLUTION: Identification of topics, keywords and sentiment — clearly visualized trends over time Deep Insight
  • 14.
  • 15. Read and classify one verbatim Quarterly chart ready in How would you use 120 MD? Deep Insight: Delivering Value Before 2 min 24 sec …………… …. 3 weeks Tagging verbatims Immediately …. ….. 2 days Increasing NPS CLIENT: (retailer); TASK: Analyze 40k feedback pieces each quarter
  • 16. • Our AI learns the language of any specific market (e.g. German Automotive) • Our AI learns the language of any specific channel (e.g. SMS vs emails vs call transcripts) • Solutions deployed in German, English, Czech, French, Hungarian, Chinese, Japanese & more • Language-agnostic tech: Words are reduced to numbers and vectors – Our Natural Language processing works in any language Language Independence
  • 17. • Words occurring in similar contexts have similar meanings • Meaning = point in a high-dimensional space • Unsupervised machine learning: No human input Distributional Semantics
  • 18. • XYZ is made of barley and hops. • There is a pint of XYZ on the table. • XYZ can make you drunk. • Let’s go grab a XYZ!! What is XYZ?
  • 19.
  • 20. AI adoption: Be the front-runner!