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Smart Customer Assistance PlatformCatalyst Project
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Catalyst Champion and Participants
Catalyst Champion
Catalyst Participants
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Catalyst Objective
• To demonstrate the effectiveness of a smart customer assistance platform which leverages network context, natural language processing and artificial intelligence to automate customer service resolution.
• Taking advantage of subscriber intel to further enhance the experience by automating relevant and personalized product offering delivery, in context, as part of a digital customer journey.
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Artificial Intelligence Why Now?
DATA
44 Zettabytes by 2020*
CLOUD
Cheap, scalable compute
DATA SCIENCE
Data scientist is the sexist job
INTERNET OF THINGS
212B connected things by 2020*
STORAGE
Access to cheap, abundant storage
ALGORITHMS
Open Source and democratized
*IDC Digital Universe report, 2014 http://www.emc.com/infographics/digital-universe-2014.htm
**Data Scientist: The Sexiest Job of the 21st Century, Oct 2012 https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century
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Benefits of using AI
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Use Case - 1 : Automated Customer Service Resolution
• Turk Telekom has to handle 6.000 customer emails per day
• 11.000 large account customers served
• 130 agents employed for handling customer emails
• Monthly OPEX: 1.950k TL (~400k €)
• Average processing time per email: 15 mins
• Turk Telekom willing to utilize AI/ML/NLP to automate the resolution of common business issues
Business Drivers:
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Use Case - 1 : Automated Customer Service Resolution
• As a Customer Service Representative
• I need to assist my customers by replying their emails in an autonomous and self-service manner
• so that I can assist my customers in a more efficient, automated, standard and cost effective way
• To do this I need to build a smart customer assistance platform that is capable of interacting, helping and guiding customers with no or limited human intervention by leveraging Artificial Intelligence, Machine Learning and Natural Language Processing techniques
• I know that I am successful when through the use of the smart customer assistance platform, customers can mostly accomplish their requests automatically, without having to dial a call center or go to a store.
User Story:
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Use Case - 1 : Automated Customer Service Resolution
Customer Emails Emails Received
Emails Replied
Email ServerPull Emails
Auto Reply Emails using NLP & AI
AI Driven CustomerService Management
CRM
Billing
Order ManagementTM Forum
Open APIs
BILLING NETWORK
DATA
PROFILE
SUBSCRIBER
HISTORYANY DATA
SOURCE
SMART DATA MANAGER
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AI Driven Customer Service Management
1. Customer inquiry initiated via social media, email, web form
2. Etiya CSM reads the ticket, infers the customer’s intent & selects best response based on historical trends
3. Answers with high accuracy are returned directly to customer
4. Answers with high accuracy are returned directly
5. Agent responses and any customer followups are fed back to AI to improve future results
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How AI Driven Customer Service Management Works?
Incoming Message
Natural Language Processing & Categorization
Category Product SentimentCustomerRequest
Priority
Integrations & Recommendation Engine
Generate Ticketand Route
Feedback Machine Learning
RecommendResponse
Account & Network Context
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Development Cycle of Machine Learning
Problem Analysis
Solution Development
Preprocessing
Solution Test
WebService
Updating TrainingData Set
Dataset Creation Model Training
1 2 3
45
?
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Etiya CSM Functional Architecture
WEB PAGES FACEBOOK
Etiya CSMFRONTEND
Etiya CSMBACKEND
Etiya CSM API Etiya CSM SOCIAL
Etiya AI Engine AWS SQS
MAILCRAWLER
2.W
EB FO
RM
2. S
UB
SCR
IBE
PA
GES
3.FEED
4.PO
STs &C
HA
T
1.A
DD
PA
GES
1.R
egis
ter
Snip
pet
3. Pro
cessedFo
rm1.TIC
KET 2.
TAG
S
4.P
ULL
E-M
AIL
REST CALL1.Register
Mail Channel
3.PUSHE-MAIL
2.COLLECTE-MAIL
MAILSERVER
Recommendation Engine
Sentiment Analysis
Predictive Analytics
NLP
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AI Capabilities
Smart Categorization, Abuse Detection
Intelligent Routing
Emotional and Contextual Analysis
Solution Proposition via Machine Learning
Prioritization and Duplicate Detection
Entity Recognition
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0%
5%
10%
15%
20%
25%
30%
35%
Customer Service Request Types
Service Fault Account Issue New Purchase Order Package Change Order Move Order
Information Request Suggestion Appreciation Spam
Use Case - 1 : Automated Customer Service Resolution
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Use Case - 1 : Automated Customer Service Resolution
• Automated customer service resolution
• Auto categorize, prioritize, route emails
• Reduce number of agents by 30% (130 90)
• Save 600k TL (~120k €) per month
• Average processing time per email reduced from 15 mins 7 mins (53% save)
• Up to 95% accucary in AI predictions
Turk Telekom Business Value Propositons:
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Use Case - 1 : Automated Customer Service Resolution
Advantages attained for Users & Customers:
Customer service representatives willspend less time to
respond customers.
CSRs will require lesstraining.
CSRs will be dealingwith less tools and
complexities.
CSRs will show a happier and healthier
attitude towardscustomers.
BetterUser
Experience!
Customer will waitless and their problemwill be solved faster.
Customer will get thecorrect treatment at
the first contact.
Customers will havemore alternatives tocontact and will get a
consistent service fromall channels.
Customer will be greeted and served
properly.
BetterCustomer
Experience!
Etiya will populate allthe information and
make it ready for yourcustomer service representative.
Etiya will guide theticket resolution flowand suggest the best
resolution/respond forthem.
Etiya will collect therequests from differentchannels and present
them to CSRs in a similar fashion.
Etiya will do all therepetitive and
monotonous tasks.
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Give Jane a personal online experience in real-time
Use Case - 2: Offer Personalized Products
Pre-emptive Recommendations Through Unified Experience Across all Digital Channels
Persona32, mother of 2, entrepreneur,
lives in city, postpaid
ContextTravels a lot, now in New York for work. Tomorrow in Miami
for holidays.
Analytics/ModelsIn the last 3 months has
travelled across USA. Streams a lot, loves watching movies
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Also personalize John’s experience in real-time
Use Case - 2: Offer Personalized Products
Persona Context Analytics/Models
Pre-emptive Recommendations Through Unified Experience Across all Digital Channels
Almost never travels, takes public transports, mostly
connects to hotspots
Has subscribed to 3 online news. Listens to music, has a
corporate limited subscription
35, single, lives in rural area, prepaid, works hard for a city
corporation
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Use Case - 2: Offer Personalized Products
• Offer personalized products to its subscribers
• Improve customer loyalty & satisfaction
• Enable the same omni channel customer experience at every touch point
• Increase revenue
• Gain competitive advantage
Business Drivers:
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Use Case - 2: Offer Personalized Products
• As a Customer Sales Representative
• I need to sell the best fit, personalized offers to my customers
• so that I can ensure that my customers buy exactly what they really need
• To do this I need to build a smart customer assistance platform that is capable of offering personalized products to customers based on usage, social media entries, history and customer journey by leveraging Artificial Intelligence, Machine Learning, Predictive Analytics and Natural Language Processing techniques
• I know that I am successful when customers are satisfied with their products and feel that the offered products are tailored for them
User Story:
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Use Case - 2: Offer Personalized Products
ETIYA
Order Capture
ETIYA
Recommendation Engine
SMART DATA MANAGER
Subscriber Activity Monitoring
INNOVA
Payment SolutionsB
SSO
SS
REAL-TIME
OFFER
MANAGER
Contextual engagement
TM Forum Open APIs
TM Forum Open APIs
TM Forum Open APIs
TM F
oru
m
Op
en A
PIs
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Segmentation to Personalization
• Today any customer facing offers should be real-time and context-aware. Old-fashioned offers with pre-planned/pre-configured schedules, and off-line processing based on historic activity continue to deliver terrible uptake rates for offers
• Openet’s Real-time Offer Manager enables real-time offer presentation after intelligent offer mapping, andpresentation of contextually appropriate offers enhancing an operators inbound campaign management capability.
• Real-time Offer Manager also provides, orchestrated offer provisioning, and simplified offer management and reporting.
• Our experience with operators has shown that offer uptake is up to 75% higher when offers are sent to the right customer, with the right context at the right time
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Virtualized, Scalable, Massively Parallel
23
Mobile Devices
Network
Incidents Sub.
Data -
Static
Customer Centre
Records
Alarms
Billing
Information
Smart
Data
Manager
Analytics
AI
NLP
• Openet solution is fully virtualized, scalable as per customer needs.
• Replicated dynamically on demand for different types of input, volume and complexity
• Completed events are delivered to multiple downstream platforms
• All of above is performed in real-time by multiple parallel instances in memory.
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Innova PayFlex Payment Management System
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Innova PayFlex Payment Management System Features
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Use Case - 2: Offer Personalized Products
• Increase in revenue
• Improve customer satisfaction & loyalty
• More upsell, cross sell, new sale
• Enable omni channel experience
• Predictive analytics facilitates offering customers the right product, at the right time
Turk Telekom Business Value Propositons:
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TM Forum Frameworx/Assets Used & Contributions
• Information Framework (SID)
• Business Process Framework (ETOM)
• Open APIs
• Business Metrics
• *** New Open API Contribution “Text Analyze API” that analyzes a given text by leveraging Natural Language Processing and Artificial Intelligence and returns sentiment analysis, recognized entities, category and priority.
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Thank you