How can big data help us look differently at our customer base? A presentation by Elan Rosenberg, Business Development Director, Marketing Analytics at cVidya
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A leading supplier of Revenue Analytics solutions to
communications and digital service providers
Founded: 2001
300 employees in 15 locations worldwide
Deployed at 7 out of the 10 largest operators in the world
150 customers in 64 countries
Processing 2.45 Billion subscribers in deployments globally
Saving over $12 Billion to providers annual revenue
Partnering with world leading vendors
What You Should Know ABOUT US
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How can big data help us look differently at our customer base?
What if you identify that these are
all one family with different kind of data users?
Daughter
Mother
FatherSon
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And what if you knew that they are mainly interested
in Football?
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So, how can this optimize our marketing activities?
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Tools to support a non-technical marketer with
quick path from ideation to actionable results
Complexity of getting near real-time data
insight supporting informed decisions
Lack of subscriber insight for personalized user
experience
Multiple and disparate data sources
Access, collection, enrichment, analysis
Quick, relevant and cost-effective launch of new
services and propositions
Base Management
Challenges & Needs
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How does the CSP see the Williams family today?
Debra
− Private account
− Plan: bundle of 3 GBs data,
unlimited nat’l/int’l voice/sms
− Silent roamer (mainly WiFi)
Colin
− On a student plan in a competitor network
Mike
– Prepaid SIM
– No visibility on demographics
– Plan: recurrent bundle of 500MBs
data, 500 minutes, 500 SMS
– Occasionally exceeds data allowance
George
– SOHO account
– Plan: bundle of 5 GB data,
unlimited nat’l voice/sms
– Never exceeds data allowance
?
Jessica
− On the same account as Debra
− Plan: bundle of 1 GB data,
unlimited nat’l voice/sms
− Regularly exceeds data
allowance
?
Debra
Jessica
George
Mike
Colin
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Top-up stimulation offers
Mobile data dongle
Cloud storage
Standard roaming package
Extra SIM for a tablet
Bridge data bundle
Data bundle upsell
…and what can it offer them?
?
Debra
Jessica
George
Mike
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Utilizing big data
analytics
Data Available
Customer attributes, XDRs, DPI,
device, location, data bundle
utilization, point of sale, invoice, top-
ups, etc…
Insights
Correlations, relationships, patterns,
habits
Correlations – social circles, families,
SMBs
Patterns of use – profile enrichment
Interests
Gender and age groups
Influencers (new offers, retention)
Needs and communication habits as
individuals and as a group/segment
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What can big data analytics reveal about the Williams family?
?
?
Family Circles
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What can big data analytics reveal about the Williams family?
?
Age Group
(8-13)
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What can big data analytics reveal about the Williams family?
?
Gender
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What can big data analytics reveal about the Williams family?
Interests
Family Circles
?
?
Age
Gender
Devices
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What can big data analytics reveal about the Williams family?
?
?
Now what can we offer them?
Shared, multi-device, data family plan
Acquisition campaign – add another family member
Migration of prepaid to post-paid
Special data roaming rates
Device upgrade supporting LTE *
Promotions on a special occasion to a sports event
1 month free offer for a Mobile HDTV sports pack
* “Apple to be the
most desired brand among
American teenagers”
(Piper Jaffray’s 25th
bi-annual teen survey)
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Let’s zoom out to a full customer base family analysis
Tethering and multi-device usage
Correlation between # data users
and family ARPU/Usage
Families data usage characteristics
Family size distribution
Influencers
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cVidya Enrich – Your Guided Path to Actionable Insights
Self-service environment for Telecom
marketers
Pre-modeled customer data analytics with
use cases focusing on different business
objectives
Identifies potential target micro-segments
for different marketing activities
Impact analysis of potential offers on
targeted segments
Combines advanced analytical models,
based on machine learning sophisticated
algorithms
Greater visibility of meaningful data