This document discusses how mobile network operators can generate more revenue from data services in competitive markets. It provides examples of using customer data and analytics to improve pricing models, introduce new service offerings, and identify opportunities to increase data usage and upgrade customer data bundles. The document also notes the large number of pricing plans operators maintain and suggests using analytics to reduce costs by streamlining plans, migrating customers to new plans, and removing unprofitable plans. It introduces cVidya as a supplier of revenue analytics solutions and describes its product modules for collecting, enriching, analyzing customer data to provide insights across business objectives like data monetization and price plan optimization.
2. Let’s Connect Back to
The Provider…
Insights
Correlation, relationships, patterns,
habits
–
Data Available
XDRs, customer details, device,
location, account number, point of
sale, revenues…..
2
–
–
–
Needs and communication habits as a
group and as individuals
Patterns of use - profile enrichment
Influencers
Correlations - Friends/family
members/SMEs
3. Analytics is Crucial for Mobile Data Pricing
Understanding your data as well as
customer usage and needs mean:
• Creation of relevant pricing models and
campaigns
• Innovation and “out of the box” pricing
models with 3rd parties partnerships
• “Trial and Error” mode of operation
• Optimization of legacy pricing plans to
reduce costs and resources
3
4. Operators’ Reality
“Telcos are sitting on a huge pile of data. But they can only efficiently use a small portion.
Leveraging it effectively requires a very targeted approach to gain usable outputs.”
(Deutsche Telekom)
“Pricing models are about moving from one-size-fits-all to consumption-based models
with much more flexibility and customization built in to allow the end user to make the
choices they want to make based on what they need at that moment in time.”
(Alicia Dietsch, AT&T)
4
5. Opportunity loss potential
of 230B USD in 2013-2015
Improve
CLTV
Manage the
OTT challenge
Maximize returns
from LTE
Investments
5
Underpin
Advanced
Segmentation
Mobile broadband connections reached $1.6B users in 2012, a 43% growth year-over-year
Mobile broadband revenues reached $244.2 billion in 2012, a 21% growth year-on-year
Ovum, wireless Intelligence
6. CMOs’ Pains
Multiple data sources
Access, collection, analysis
Poor alignment between siloed
departments (e.g., marketing, sales, IT,
network, etc.)
Lack of subscriber insight for personalized
user experience
Near real-time data insight make better
informed decisions about new propositions
Tools to support the decisions of next
best actions per single customers
Quick and cost-effective new services
launch
6
* Market Research 222 CMOs (CMO council), Jan 2013
7. Use Case Example - Maximize Data
Revenue & Improve Data Experience
7
8. Increase & Expand Usage of Data Services
Increase customers’ data usage volume and expand their usage to additional data services,
to increase data revenue, drive the need for data bundle upgrades, and prevent bundle downgrades
• Identify customers with:
- Non-steady data usage or
- Usage that doesn’t justify
current data package
• Incentivize these customers
to increase data usage
volume
• Introduce these customers to
additional data services, per
identified interests
8
• Identify customers using only
a single/ few data services
(e.g., Facebook)
• Find what data services are
typically used in conjunction
with the used services
• Incentivize these customers
to start using additional data
services - those most related
with the services they use
• Identify customers using data
services only during business
hours/ for business purposes
• Find what leisure data
services are most used by
users of business services
• Incentivize these customers
to also use those leisure data
services
9. Identify Best Candidates for Data Bundle Upgrade
•
•
Use sophisticated, typically-hidden insight to identify the best candidates for data bundle upgrades
Focus your bundle upgrade efforts on these customers to maximize success rate
What customers have exceeded
their current data bundles for X
consecutive months?
What customers have purchased
one-time data packages X times in
the past few months?
What customers are using tethering
(connecting to a bundle by multiple devices)?
Offer these customers bigger, cross-device
bundles
9
What combinations of customer
profile/ handset/ usage/ status
attributes are most indicative of
bundle upgrade/ high data
usage?
What is the impact of OTT service usage on
customers of different usage patterns?
Identify these customers to avoid targeting
them with data upgrades in order to prevent
cannibalization
10. Improve Data Usage Experience
Offer customers relevant service-driven, rather than volume driven, data proposition, for premium Quality of
Experience and as additional source of data revenue
Customers with high-volume of Facebook/
Twitter usage
Customers who are frequently using video
streaming/ gaming
Offer video optimization service for additional fee, or
direct to video optimization guidelines
Customers with high-volume of sports/ music
streaming
Offer the operator’s sports/ music application,
or one promoted by the operator, for a discount
Customers frequently using VoIP on their
mobile
Offer guaranteed Quality of Experience for VoIP calls,
for an additional fee
Customers constantly using data services on an
older-generation device
10
Offer unlimited Facebook/ Twitter usage, for a
fixed monthly fee
Offer subsidized upgrade to an advanced device, for
better quality of data services, encouraging higher
usage
12. Price Plan
Migration
• CSPs create numerous price plans & features
to meet subscribers’ demands, fight
competition and generate new revenues
– A medium-sized operator may have tens
of thousands of price plans.
– The cost per price plan varies between
different CSPs, and range between
$1,000 -$20,000 per price plan annually
– Maintaining price plans requires
numerous cross organization and
platform activities
12
13. Price Plan
Migration
Significantly reduce the cost of operations
and increase efficiency by:
• Marking unprofitable price plans based on
available cost information
• Defining price plans and products that need
to be removed
• Calculating expected financial impact of the
migration
• Building a detailed migration plan for each
individual customer according to business needs
• Cleansing of data
• Impact of new price plans on the revenues
13
14. What You Should Know - cVidya
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
Globally processing 150 Billion xDRs per day, 55 Trillion xDRs per year
Saving over $12 Billion to providers annual revenue
Partnering with world leading vendors
14
16. cVidya Enrich™ - Product Modules
Product Platform
Data Collection
Data Correlation &
Enrichment
Business Analysis &
Modeling
Visualization &
Presentation
Cross-business, 360° Executive View
An included set of always-relevant data analytics
Modular Data-Sets (Select any combination)
Pre-modeled + Create Your Own Analysis
Sets of on-line reports, to support strategy of 7 specific business objectives:
Accelerate
Data
Penetration
Maximize
Data
Revenue
Monetize
Data with
3rd-Parties
Optimize
Price Plan
Mgmt.
Pre- to
Post-paid
Migration
Improve
Acquisition
& Retention
Optimize
Roaming
Proposition
Present specific insight for: Influencers/ customer groups (families, small businesses)
16
(Optional) Advanced Data Models