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•Jolita Bernotiene, Sales Director
Jolita@exacaster.com
Introduction
to household
identification
for telecoms
▪ Why household identification is needed?
▪ Key challenges when building household identification
▪ Exacaster 360 data platform
Let’s start the story - family of 3 living in one house...
…who also share the services
Miguel
Services: mobile rate plan,
iPhone leasing
Sandra
Services: mobile rate plan,
iPhone leasing
Carlos
Services: prepaid SIM
Miguel’s
phone
Sandra’s
phone
Carlos’s
phone
Family uses 8 digital services and spends $184 per month
Shared
home
services
Mobile rate
plan
iPhone
leasing
Sports TV
package
Mobile rate
plan
iPhone
leasing
Miguel
Value: $109
FTTH
basic plan
Sandra
Value: $65
Carlos
Value: $10
Sports TV
package
Prepaid
SIM
FTTH
basic plan
This is how telecoms see their subscribers.Customer fundamental
needs are often missed
Customer #1
• Name: Miguel
• Value: $55
• Services: Mobile rate
plan, iPhone leasing
Customer #2
• Name: Miguel
• Value: $45
• Services: Smart IPTV plan,
Sports TV package, FTTH
Basic plan
Customer #4
• Name: Sandra
• Value: $55
• Services: Mobile rate
plan, iPhone leasing
Customer #6
• Name: Carlos
• Value: $10
• Services: Prepaid SIM
Customer #5
• Name: Sandra
• Value: $10
• Services: Netflix
Customer #3
• Name: Miguel
• Value: $9
• Services: Spotify
premium
Asiloedunderstandingof a customerleadstoineffectivecampaigns,
followedbya negativecustomerexperience
Customer #4
• Name: Sandra
• Value: $65
• Services: Mobile rate
plan, iPhone leasing
Customer #2
• Name: Miguel
• Value: $45
• Services: Smart IPTV plan,
Sports TV package, FTTH
basic plan
Cross-sell with TV services Upsell with Netflix account
Service already shared
in household
Service already shared
in household
Upselling based on single customer view
REJECTED

How to
embrace
customer data
in order to offer
your subscribers
with what they
actually need?
Miguel
Mobile rate
plan $15
Mobile rate
plan $15
iPhone
leasing $40
iPhone
leasing $40
Smart IPTV plan $25,
Sports TV package $5
Prepaid
SIM $10
FTTH basic plan $15 Spotify
premium $9
Netflix $10
$109
$65
$10
Family postpaid
rate plan
Exchange prepaid SIM to
postpaid plan for more
stable revenue
Discount
for new iPhone
Suggest renewing iPhone
devices
More channels:
+ Movie package
+ Kids package
Upsell with channel
packages for families
Higher speed
FTTH plan
Include higher internet speed
plan as a bundle benefit
No VAS
included
Don’t recommend VAS to
manage rate plan margin
Retain customers by targeting them with relevant offers from a
household perspective
Sandra
Carlos
Upsell and
cross-sell
with relevant
services
Device
leasing
Mobile TV Broadband VAS
TOTAL
amount, $
Personalization can bring up to $200
billion in value for Telco sector
1. Consumer packaged goods
2. Healthcare systems and services
3. Pharmaceuticals and medical products
Resource: McKinsey article “A technology blueprint for personalization at scale”, May 2019.
Link: https://www.mckinsey.com/business-functions/marketing-and-sales/our-insights/a-technology-blueprint-for-personalization-at-scale
Retail
CPG1
Travel
Banking
Insurance
Telco
HSS2
PMP3
$1.7-$3.0
0.45-0.8
0.15-0.2
0.3-0.5
0.2-0.45
0.25-0.6
0.15-0.2
0.1-0.15
0.1
Estimated value to be
created by personalization
within sectors, $ trillion
Looks obvious?
The devil is in the
implementation!
▪ Why household identification is needed?
▪ Key challenges when building
household identification
▪ Exacaster 360 data platform
Key challenges to identify a household
Collecting all required
customer data
Information about a customer is held in different silos because it comes from
multiple systems with their own unique data structure and processes. Identifying
information about specific user becomes a complex technical challenge.
Data unification2
Building flexible data
hierarchy for analytics3
1
Significant effort is required to unify all data about a specific customer from
internal company systems and 3rd party sources.
It is a complex task to map all collected data to a model which would be
flexible enough to meet an organizations analytical needs and enable
different use cases.
4
Low return on
investment
Customer data collection and household identification requires a lot of
effort and time, but often it is not used to its full potential or it doesn’t
bring the expected impact for the business.
• Propensity scores
• Demographic and lifestyle
predictions
• Sentiment scoring
• Price sensitivity
• Household
• Etc.
Multiple data sources have to be collected and connected
for full customer understanding
Internal
non-traditional data
External data
Predicted data
• Billing, CRM data
• CDRs, XDRs
• Call center logs
• POS logs
• Network quality data
• Personal surveys
• Etc.
• Location data
• Hardware logs (set-up box)
• Content consumption: IPTV
logs, browsing logs, etc.
• Digital channels logs
(mobile apps)
• Campaign logs: SMS, email.
• Government databases
• Credit bureaus and
financial databases
• Social media
• External data from other
industries: retail,
banking, etc.
• Etc.
Internal traditional data
1
Overcome data consistency and quality challenges by
unifying customer data
Mobile service CRM
Fixed service CRM
Data inconsistency
can be solved with
predefined business
logic and algorithms
Data inconsistency can
be solved with manual
data quality review or a
customer survey
Customer name
J. Johnson
Customer name
John Johnson
Customer name
John Johnson
Customer name
Frank Johnson
Perfect data match
Customer name
John Johnson
Customer name
John Johnson
Partial data match Data mismatch
2
Data inconsistency
can be solved with
predefined business
logic and algorithms
Different customer views enable proactive service
management for quad players
Household
Customer
Service
subscriptions
• Cross-sell and upsell
with subscriptions
• Retain subscriptions
• Cross-sell and upsell
to customers
• Retain customers
• Cross-sell to
households
Level Enablement
• Analyze and manage individual
service subscriptions: mobile, TV,
internet, fixed line plans, devices,
VAS, etc.
• Analyze service and product usage.
Description Key questions to be answered
• Enhance customer understanding
by mapping them with services.
• Identify cross-sell and upsell
opportunities on customer level.
• Enhance household understanding
by mapping them with customers.
• Identify cross-sell and upsell
opportunities on a household level.
• What is the probability of subscription churn?
• Can we upsell users with more expensive
plan for the same service?
• Can we upsell users with additional packages
or VAS?
• What type of active services the customer has?
• What services bundle would be most suitable to
upsell to each customer?
• What is the probability of customer churn?
• How many customers in the household have our
services?
• What type of active services the household has?
• What services bundle would be most suitable to
upsell to each household?
3
Customer data platform with out-of-the-box customer views and
KPIs can lower time to market and improve the ROI of an initiative
Campaign
manager
NBO engine
CDRs
CRM data
Web activities
Mobile app
Other data
Customer 360
data platform
Data integration
Identity
management
Calculation
engine
AdWords
Facebook ads
Email
Website
personalization
SMS
Paid channels
Owned channels
4
• Why household identification is needed?
• Key challenges when building household identification
• Exacaster 360 data platform
Customer Data Platform
for Telecoms
Automate customer data collection
and cleaning
Connect offline and online
customer data
KPIs and segmentations for
telco use cases
Get insights from traditional telco
data sources (CDRs)
Capabilities enabled by the Exacaster Customer 360 data platform
Build a golden record of a customer
Clean customer data, build the golden record and distribute it across all business applications.
Create views for every subscription, customer and household
Get multiple customer views - subscription, customer and household - to proactively manage the services.
Get insights from 1000s of telco specific KPIs
Mobile, TV, broadband, fixed-line and household profiles are available with 1000s of preconfigured KPIs (lifetime, dropped calls, friends,
open tickets in call center, average movie buffering time, etc.) for the digital marketing, BI and AI applications.
Leverage extremely accurate predictions and recommendations
Use built-in prediction algorithms such as churn score and next-best-offer to run proactive marketing campaigns and create valuable
experiences for the consumers. Algorithms are pre-trained using deep learning techniques that guarantee exceptional accuracy of targeting.
Activate customers in multiple channels
Expose data for personalization to all marketing channels and customer touchpoints.
Customer data platform (CDP) features enable robust large-scale data
management with low maintenance efforts
Data quality alerts
The platform comes with automated data tests and data quality alerts (identification of
outliers, data type changes, etc.) to reduce maintenance costs
Large-scale dataset
management
CDP uses the latest big data technology (Spark 2.3) to handle large datasets
Efficient creation and
update of KPIs
Adding a new KPI or updating the existing one doesn’t require recalculation of all
available information. Our solution recalculates only the required information for the
selected KPI
Flexible to data
source changes
The calculation process is not impacted by the majority of data source changes (new
values, new columns, etc.)
Works in on-premise
and cloud environments
The platform can be set up in on-premise or cloud environments depending on the
telecom’s current infrastructure
Jolita Bernotiene
Sales Director
+370 636 06360
jolita@exacaster.com
What about the household
view in your telco?
Let‘s turn it to a golden record!
Our Headquarters
B NORDIC 26 Business Factory
Basanaviciaus st. 26
Vilnius, Lithuania, EU
www.exacaster.com

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Household identification for telcos by exacaster

  • 1. •Jolita Bernotiene, Sales Director Jolita@exacaster.com Introduction to household identification for telecoms
  • 2. ▪ Why household identification is needed? ▪ Key challenges when building household identification ▪ Exacaster 360 data platform
  • 3. Let’s start the story - family of 3 living in one house... …who also share the services Miguel Services: mobile rate plan, iPhone leasing Sandra Services: mobile rate plan, iPhone leasing Carlos Services: prepaid SIM Miguel’s phone Sandra’s phone Carlos’s phone
  • 4. Family uses 8 digital services and spends $184 per month Shared home services Mobile rate plan iPhone leasing Sports TV package Mobile rate plan iPhone leasing Miguel Value: $109 FTTH basic plan Sandra Value: $65 Carlos Value: $10 Sports TV package Prepaid SIM FTTH basic plan
  • 5. This is how telecoms see their subscribers.Customer fundamental needs are often missed Customer #1 • Name: Miguel • Value: $55 • Services: Mobile rate plan, iPhone leasing Customer #2 • Name: Miguel • Value: $45 • Services: Smart IPTV plan, Sports TV package, FTTH Basic plan Customer #4 • Name: Sandra • Value: $55 • Services: Mobile rate plan, iPhone leasing Customer #6 • Name: Carlos • Value: $10 • Services: Prepaid SIM Customer #5 • Name: Sandra • Value: $10 • Services: Netflix Customer #3 • Name: Miguel • Value: $9 • Services: Spotify premium
  • 6. Asiloedunderstandingof a customerleadstoineffectivecampaigns, followedbya negativecustomerexperience Customer #4 • Name: Sandra • Value: $65 • Services: Mobile rate plan, iPhone leasing Customer #2 • Name: Miguel • Value: $45 • Services: Smart IPTV plan, Sports TV package, FTTH basic plan Cross-sell with TV services Upsell with Netflix account Service already shared in household Service already shared in household Upselling based on single customer view REJECTED 
  • 7. How to embrace customer data in order to offer your subscribers with what they actually need?
  • 8. Miguel Mobile rate plan $15 Mobile rate plan $15 iPhone leasing $40 iPhone leasing $40 Smart IPTV plan $25, Sports TV package $5 Prepaid SIM $10 FTTH basic plan $15 Spotify premium $9 Netflix $10 $109 $65 $10 Family postpaid rate plan Exchange prepaid SIM to postpaid plan for more stable revenue Discount for new iPhone Suggest renewing iPhone devices More channels: + Movie package + Kids package Upsell with channel packages for families Higher speed FTTH plan Include higher internet speed plan as a bundle benefit No VAS included Don’t recommend VAS to manage rate plan margin Retain customers by targeting them with relevant offers from a household perspective Sandra Carlos Upsell and cross-sell with relevant services Device leasing Mobile TV Broadband VAS TOTAL amount, $
  • 9. Personalization can bring up to $200 billion in value for Telco sector 1. Consumer packaged goods 2. Healthcare systems and services 3. Pharmaceuticals and medical products Resource: McKinsey article “A technology blueprint for personalization at scale”, May 2019. Link: https://www.mckinsey.com/business-functions/marketing-and-sales/our-insights/a-technology-blueprint-for-personalization-at-scale Retail CPG1 Travel Banking Insurance Telco HSS2 PMP3 $1.7-$3.0 0.45-0.8 0.15-0.2 0.3-0.5 0.2-0.45 0.25-0.6 0.15-0.2 0.1-0.15 0.1 Estimated value to be created by personalization within sectors, $ trillion
  • 10. Looks obvious? The devil is in the implementation!
  • 11. ▪ Why household identification is needed? ▪ Key challenges when building household identification ▪ Exacaster 360 data platform
  • 12. Key challenges to identify a household Collecting all required customer data Information about a customer is held in different silos because it comes from multiple systems with their own unique data structure and processes. Identifying information about specific user becomes a complex technical challenge. Data unification2 Building flexible data hierarchy for analytics3 1 Significant effort is required to unify all data about a specific customer from internal company systems and 3rd party sources. It is a complex task to map all collected data to a model which would be flexible enough to meet an organizations analytical needs and enable different use cases. 4 Low return on investment Customer data collection and household identification requires a lot of effort and time, but often it is not used to its full potential or it doesn’t bring the expected impact for the business.
  • 13. • Propensity scores • Demographic and lifestyle predictions • Sentiment scoring • Price sensitivity • Household • Etc. Multiple data sources have to be collected and connected for full customer understanding Internal non-traditional data External data Predicted data • Billing, CRM data • CDRs, XDRs • Call center logs • POS logs • Network quality data • Personal surveys • Etc. • Location data • Hardware logs (set-up box) • Content consumption: IPTV logs, browsing logs, etc. • Digital channels logs (mobile apps) • Campaign logs: SMS, email. • Government databases • Credit bureaus and financial databases • Social media • External data from other industries: retail, banking, etc. • Etc. Internal traditional data 1
  • 14. Overcome data consistency and quality challenges by unifying customer data Mobile service CRM Fixed service CRM Data inconsistency can be solved with predefined business logic and algorithms Data inconsistency can be solved with manual data quality review or a customer survey Customer name J. Johnson Customer name John Johnson Customer name John Johnson Customer name Frank Johnson Perfect data match Customer name John Johnson Customer name John Johnson Partial data match Data mismatch 2 Data inconsistency can be solved with predefined business logic and algorithms
  • 15. Different customer views enable proactive service management for quad players Household Customer Service subscriptions • Cross-sell and upsell with subscriptions • Retain subscriptions • Cross-sell and upsell to customers • Retain customers • Cross-sell to households Level Enablement • Analyze and manage individual service subscriptions: mobile, TV, internet, fixed line plans, devices, VAS, etc. • Analyze service and product usage. Description Key questions to be answered • Enhance customer understanding by mapping them with services. • Identify cross-sell and upsell opportunities on customer level. • Enhance household understanding by mapping them with customers. • Identify cross-sell and upsell opportunities on a household level. • What is the probability of subscription churn? • Can we upsell users with more expensive plan for the same service? • Can we upsell users with additional packages or VAS? • What type of active services the customer has? • What services bundle would be most suitable to upsell to each customer? • What is the probability of customer churn? • How many customers in the household have our services? • What type of active services the household has? • What services bundle would be most suitable to upsell to each household? 3
  • 16. Customer data platform with out-of-the-box customer views and KPIs can lower time to market and improve the ROI of an initiative Campaign manager NBO engine CDRs CRM data Web activities Mobile app Other data Customer 360 data platform Data integration Identity management Calculation engine AdWords Facebook ads Email Website personalization SMS Paid channels Owned channels 4
  • 17. • Why household identification is needed? • Key challenges when building household identification • Exacaster 360 data platform
  • 18. Customer Data Platform for Telecoms Automate customer data collection and cleaning Connect offline and online customer data KPIs and segmentations for telco use cases Get insights from traditional telco data sources (CDRs)
  • 19. Capabilities enabled by the Exacaster Customer 360 data platform Build a golden record of a customer Clean customer data, build the golden record and distribute it across all business applications. Create views for every subscription, customer and household Get multiple customer views - subscription, customer and household - to proactively manage the services. Get insights from 1000s of telco specific KPIs Mobile, TV, broadband, fixed-line and household profiles are available with 1000s of preconfigured KPIs (lifetime, dropped calls, friends, open tickets in call center, average movie buffering time, etc.) for the digital marketing, BI and AI applications. Leverage extremely accurate predictions and recommendations Use built-in prediction algorithms such as churn score and next-best-offer to run proactive marketing campaigns and create valuable experiences for the consumers. Algorithms are pre-trained using deep learning techniques that guarantee exceptional accuracy of targeting. Activate customers in multiple channels Expose data for personalization to all marketing channels and customer touchpoints.
  • 20. Customer data platform (CDP) features enable robust large-scale data management with low maintenance efforts Data quality alerts The platform comes with automated data tests and data quality alerts (identification of outliers, data type changes, etc.) to reduce maintenance costs Large-scale dataset management CDP uses the latest big data technology (Spark 2.3) to handle large datasets Efficient creation and update of KPIs Adding a new KPI or updating the existing one doesn’t require recalculation of all available information. Our solution recalculates only the required information for the selected KPI Flexible to data source changes The calculation process is not impacted by the majority of data source changes (new values, new columns, etc.) Works in on-premise and cloud environments The platform can be set up in on-premise or cloud environments depending on the telecom’s current infrastructure
  • 21. Jolita Bernotiene Sales Director +370 636 06360 jolita@exacaster.com What about the household view in your telco? Let‘s turn it to a golden record! Our Headquarters B NORDIC 26 Business Factory Basanaviciaus st. 26 Vilnius, Lithuania, EU www.exacaster.com