customer data management and marketing automation - … · 2019-10-01 · • billing, crm data ......
TRANSCRIPT
•Jolita Bernotiene, Sales Director
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: $109FTTH
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
A siloed understanding of a customer leads to ineffective campaigns, followed by a negative customer experience
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 sharedin 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?
MiguelMobile 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
leasingMobile 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
HSS2PMP3
$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
0.1-0.150.1
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.
4Low 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
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 customerClean customer data, build the golden record and distribute it across all business applications.
Create views for every subscription, customer and householdGet multiple customer views - subscription, customer and household - to proactively manage the services.
Get insights from 1000s of telco specific KPIsMobile, 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 recommendationsUse 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 channelsExpose 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 alertsThe platform comes with automated data tests and data quality alerts (identification of
outliers, data type changes, etc.) to reduce maintenance costs
Large-scale dataset
managementCDP 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
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