Strategies For Survival in Telecom\'s Perfect Storm

Strategies for Survival from a
Perfect Storm in Telecom

Ryan Hendricks
Campaignist, Inc.

September 2010

Survival Strategies for Telecom’s Perfect Storm
Rising infrastructure costs and falling margins

• Global telecom businesses are
under pressure to transform
themselves by a “perfect 3G/4G
ARPU
storm” of business, technology Addressable
Market
and market pressures;
– Addressable Market saturation at
high-end ARPU segments;
– Falling voice and VAS margins; 3G/4G-
enabled
– Pending number portability; Services

– Telecom handsets are becoming VAS /
Data
the platform of choice for converged Margins
media for the masses (Phone + TV
+ PC + Cinema); Voice
Margins
– New skills and revenue model
strategies are critical.

2 Copyright Campaignist, Inc. ®

Five (5) Key business transformation drivers
• Quantity Focus becoming a Quality Focused Strategy
– Customer relationship is moving up the value chain
– Volume of acquisitions will not be sufficient to support new business
models – especially given falling margins for traditional services

Old Business Drivers New Business Drivers
1. Voice and VAS 1. Content and Context

Becoming
2. Customer Acquisition 2. Customer Cultivation
3. Who, What 3. How, Why, When, Where
4. Product excellence 4. Insight Process excellence
5. Network coverage 5. Network applications

Quantity focus becoming a quality focus


Business transformation success factors
• Successfully competing in this transformed market will require
new skills in understanding customers, anticipating their needs and
wants, and developing new products and services rapidly to meet
these needs;
– Today’s consumers have no time for SPAM and are increasingly exercising
their right to not be disturbed by irrelevant promotions and communications
–On average >50% of subscribers are on Do-Not-Disturb – blocking direct promos

3G/4G Business Drivers 3G/4G Success Factors
1. Content and Context Partnership strategies
2. Customer Cultivation Listen, learn, apply insights
3. How, Why, When, Where 3G Master Data Roadmap
4. Insight Process excellence Align sales, marketing, retail
5. Network applications Leverage network capabilities

3G/4G business drivers and key success factors


Multi-media converged “Monetization of Time” (MOT)

• Successful media businesses (telecom, internet, television, cinema
and traditional publishing) compete to make the most revenue out
of every minute of a customer’s available time and are proxies
for emerging smart phone driven telecom’s 3G/4G battle:
• With the advent of 3G/4G networks and the mobile phone
becoming the platform of choice for convergent media, telecom
companies have to quickly move up the maturity curve on MOT;
– And take advantage of the always on, always available nature of the
broadband cell phone by providing the customer with targeted, relevant,
instant access to what they need, what they want, and productivity tools
that free up more time …
– The moments in the morning, at lunch, in the evenings, on
weekends, during holidays and even sick-days when a consumer can
decide “what do I want to do now?” are the focus of media
businesses everywhere;


Understanding both sides of the CVM coin
• Customer Value Management (CVM) is often viewed through a
one-dimensional lens – a company’s value of their customer.
– Effective CVM includes our value of them and their value of us

INSIDE-OUT (our value of them): OUTSIDE-IN (their value of us):
How They Satisfy Our Needs How We Satisfy Their Needs
1. Revenue 1. Value-for-money
2. Age-on-Network 2. Customer Satisfaction
3. Higher credit rating 3. Flexible credit limits
4. Lower Cost-to-Serve (CTS) 4. Easy, multi-channel self-service
5. Increasing number of product/service 5. Single trusted vendor for all desired
subscriptions products/services, everywhere
6. High-end, high-volume, right time 6. High-performance, high-value, timely
product/service users product availability
7. Social Network ARPU value 7. Social Network app’s and services
8. Recommendations and referrals 8. Pride of product/service ownership
9. Providing insights for new products 9. Providing incentives for feedback

Companies focus mostly on just 1 side of the Customer Value coin

A best-practice approach to segmentation maturity

High
Value Segmentation Capability WHY
WHERE
Maturity Model Self-Learning
Segmentation
WHEN
Value Delivered

Predictive Modeling

HOW
Delivery Decision Rules

WHAT
Customer Event Triggers

HOW MUCH
Customer Behavior

WHO Customer Profile
Low
Value Reactive Request Mgmt

Aware Developing Practicing Optimizing Leading
Level of Maturity


A best-practice approach to segmentation maturity
• Financial/Value Segmentation • Interaction & C-SAT Segmentation
– Mostly ARPU & Credit context – Issues and touch-point context
Cred it limit in tact

New Segmentation
HAPPY DOPEY SNEEZY

Very High Usage High Usage Sporadic Usage

No C-SAT Issues Lots of Issues In termitten t Issu es
L-1 L-2 L-5
Large Social NW Loves VAS Negative WOM

DOC BASHFUL GRUMPY

High Usage Low-Mediu m Usage Freq uen t complaints

Queen Bee Worker Bee C-4 Usag e Stead ily Falling
L-3 L-4
Pays on Last Day Paymen ts on time Paymen ts o n time

New segmentation will be common across all areas; GSM/ CDMA,
• Propensity to XYZ across Businesses
Prepaid/post paid/ and Segmentation • Lifecycle & Lifestyle Segmentation
– Deciles of likely-to-churn context – Spending, time-of-day, geo & products
10 51.7 10 46.7 10 44.2 ID EXAMPLES OF LIFESTYLE-DRIVEN USAGE SEGMENTS LIFESTYLE USAGE CATEGORY
9 46.2 9 31.4 9 43.4
CS-1
ABOVE HALF-TANKERS: Very active high credit balance Subscribers who rarely allow their credit lim it to fall
CREDIT AND SPENDING PROFILES
below half the m axim um.
8 36.7 8 42.2 8 55.7
RUNNING ON FUMES: Heavy users who regularly use services while at the edge of their disposable credit,
CS-2 CREDIT AND SPENDING PROFILES
7 43.0 7 24.1 7 31.9 once in a while falling into suspension m ode.
Decile

Decile
Decile

6 33.6 6 16.6 6 34.4 TD-2
WHILE-AT-WORKERS: Subscribers who use services during working hours but not before or after (business
TIME AND DAY USAGE PROFILES
users or hom em akers talking to friends or vendors).
5 26.2 5 19.1 5 29.5
WHILE-AT-PLAYERS: Subscribers who use services after working hours and on weekends and avail of
TD-3 TIME AND DAY USAGE PROFILES
entertainm ent VAS (astrology, jokes, sports, etc…).
4 18.8 4 22.0 4 19.2

NI HNI NHNI
GO-1 MOBILE PROFESSIONALS: Frequently roam away from their Hom e State. GEOGRAPHIC USAGE
3 10.3 3 7.0 3 13.5
GO-2 AWAY-FROM-HOME WORKERS: Frequently m ake STD calls. GEOGRAPHIC USAGE
2 4.0 2
0.6 22.1
PU-1 DATA CARD USERS: People who use Data Cards for internet access (and VOIP) PRODUCT USAGE – DATA CARD
1
1.1 1
0.0 1
0.6
PU-2 MULTIPLE SUBSCRIPTIONS: People who have m ore than one RCOM service. PRODUCT USAGE – MULTIPLE RCOM
POPULAR QUEEN BEES: Subscribers who receive m uch m ore inbound contact from m any different people
0 20 40 60 0.0 20.0 40.0 60.0 0.0 20.0 40.0 60.0 SN-1
than the outbound contacts they initiate.
SOCIAL NETWORK PROFILES

Do Not Disturb Do Not Disturb Do Not Disturb SN-2 LONELY WORKER BEES: Subscribers who m ake m uch m ore outbound contact than they receive from others. SOCIAL NETWORK PROFILES

• Interest-Driven Segmentation • Social Networking Segmentation
– Entertainment, interaction, commerce … – Network ARPU, calling patterns, CLV

Religion

There are 1,000’s of Potential Addressable Micro-segments based on existing data.


A segment behavior personification example

Five (5) Examples Likely-to-Churn Behavior Segments

TERMINATED IN JAIL SNEEZY

Voluntary Suspended Sporadic Usage
C-1 C-2
Involuntary Grace Intermittent Issues
C-5
Migration Negative Balance Negative WOM

COMATOSE GRUMPY

Active then asleep Frequent complaints

C-3 Open Issue C-4 Usage Steadily Falling

Credit limit intact Payments on time

A simple example for illustration purposes only.


A segment behavior personification example

Five (5) Examples of Likely-to-Remain-Loyal Behavior Segments

HAPPY DOPEY SLEEPY

Very High Usage High Usage Always low usage
L-5
No C-SAT Issues Lots of Issues No complaints
L-1 L-2
Large Social NW Loves VAS Payments on time

DOC BASHFUL

High Usage Low-Medium Usage

Queen Bee Worker Bee
L-3 L-4
Pays on Last Day Payments on time



A segment behavior matrix example
Credit Time & Day Social Geographic Product
Churn-Loyalty &Spending Usage Networks Usage Usage
Segment Lifestyle Lifestyle Lifestyle Lifestyle Lifestyle

C-1: Terminated CS3, CS-4 GO-2 PU-3

C-2: In Jail CS-2, CS-3 TD-3 SN-1 PU-5, PU-8

C-3: Comatose CS-5 TD-2 GO-1, GO-4 PU-2, PU-4

C-4: Grumpy CS-2 TD-1 SN-2 PU-4, PU-7

C-5: Sneezy CS-5 GO-3 PU-3

L-1: Happy CS1, CS-4 TD-3 SN-1, SN-2 GO-1, GO-4, PU-1, PU-2,
GO-5, GO-6 PU-4, PU-8

L-2: Dopey CS1, CS-4 TD-1 SN-2, GO-2 PU-1, PU-2,
PU-4, PU-8

L-3: Doc CS1, CS-4 TD-2 SN-3 GO-5, GO-6 PU-1, PU-2,
PU-4, PU-8

L-4: Bashful CS-5 SN-4 GO-4 PU-1

L-5: Sleepy CS-4 TD-3 SN-2 GO-1 PU-8



Adding interests creates 1000’s of micro segments

Adding financial,
lifestyle, interest
and other data
further extends
the targeting to
1000’s of micro
segments.


Untargeted promos closing key contact channels

• Poorly segmented, untargeted campaign tactics have resulted in a majority
of subscribers closing key promotional channels (DNC/DND*)
– Those who value their time the most (the busiest) subscribe to DNC/DND fastest;
– As a result, ARPU per Value-Added-Service (VAS) Subscriber Sale has fallen steadily

If High Value Subscribers DND First
As the Net DND Base Increases …
High Low No of
ARPU Subs

DND

DND
NUMBER of Subscribers

DND
ARPU per Subscriber

DND
ARPU

ARPU

ARPU

ARPU
Low A high number of Low value subscribers High No of
ARPU remain in this part of the pyramid. Subs

Eventually mostly Low value subscribers remain The ARPU per Value-Added Sale Falls.

*DND is Do Not Disturb (Do Not Call)

Revenue impact of advanced segmentation
• A recent Gartner article highlighted the need to move beyond the traditional static
promotions we use today to dynamic, interactive, value-focused ones with higher
response and conversion rates (ROI). The response rates for each level are:
• LEVEL 1 generates a 2% response – Traditional static promotions (1-way):
– A. traditional segmentation with promotions based on demographics like geo area and spend

• LEVEL 2:generates a 10-15% response – Dynamic promotions (individual):
– Active real-time listening of customer behavior with triggers generating personal promotions.

• LEVEL 3:generates a 20-30% response – Super micro-segmentation (network)
– Leveraging viral marketing through social networks to optimize network ARPU and CVM

• LEVEL 4 creates brand new incremental revenue streams from Partner promotions
– Leveraging customer insights to generate new sources of incremental revenue from location-
and time-based targeted mobile advertising and content subscriptions with partners.

http://www.gartner.com/technology/media-products/custom_multimedia/rate_integration.html


Recommendations for immediate next steps

• Examples of initiatives that should be initiated or expanded;

1. Product usage behavioral clustering studies: Grouping subscribers
based on their known behavior;
2. Customer Lifetime Value Studies (statistical models): Estimation of
direct and indirect customer value for improving prioritization and
ROI of CRM investments;
3. Macro-level behavioral segmentation (using location data):
Identification of housewives, professionals, office staff and laborers
based on location-based tracking and usage data;
4. Micro-segmentation-based propensity targeting: Using existing
CDR and other granular usage data, apply predictive modeling
tools to identify high-propensity 3G/4G targets from existing and
prospective customers (and prioritize them based on CLV);


An example of telecom behavioral clustering
OUT- OUT- All Bill
Avg Cost Per # OUT- IN-Calls IN-SMS IN-SMS IN-SMS
Cluster # IN-Calls Calls Bill Roam OUT-ILD IN-ILD Complaint Complaint
ARPU Unit Calls Bill Dur All Local STD
Dur Dur s s
1 10 9 10 10 10 10 10 9 9 10 5 10 10 10
2 9 6 9 9 8 9 9 8 5 8 3 8 8 8
3 8 7 6 7 9 7 7 6 8 9 4 9 9 9
4 7 2 4 8 4 8 8 5 4 7 8 4 4 6
5 6 5 5 4 5 5 5 4 6 6 7 6 5 7
6 5 1 2 5 1 6 6 3 1 4 9 1 1 2
7 4 8 7 6 6 3 2 7 2 3 2 7 6 4
8 2 3 3 2 3 4 4 1 3 5 10 3 3 5
9 1 4 1 1 2 2 3 2 7 2 6 2 2 3
10 3 10 8 3 7 1 1 10 10 1 1 5 7 1

OUT- OUT-
Avg Cost Per #OUT- IN-Calls All Bill IN-SMS IN-SMS IN-SMS
Cluster # IN-Calls Calls Bill Roam OUT-ILD IN-ILD
ARPU Unit Calls Bill Dur Complaints Complaints All Local STD
Duratn. Dur
1 504.77 17.58 75.18 75.02 106.75 127.32 8.4 0.92 0.05 0.82 0.2 38.97 12.36 3.54
2 673.42 3.06 196 173.71 308.22 278.2 13.26 1.29 0.08 0.88 0.21 63.16 27.58 7.84
3 927.21 5.8 215.48 335.96 306.99 610.73 34.86 2.17 0.05 0.87 0.2 62.65 25.83 7.79
4 951.06 1.48 425.6 318.26 723.1 511.54 21.76 2.58 0.09 0.9 0.19 117.87 68.1 17.37
5 1243.19 2.89 398.02 604.33 562.67 1013.07 49.98 2.99 0.07 0.93 0.19 94.19 47.7 13.32
6 1289.07 0.96 801.13 547.21 1511.51 935.43 35.93 3.69 0.14 0.97 0.17 195.6 124.15 33.55
7 1294.39 14.53 215.25 541.19 410.75 2168.21 184.86 1.46 0.12 1.03 0.26 93.9 42.26 25.77
8 1732.47 2.1 693.4 1002.96 948.38 1577.06 62.45 4.51 0.11 0.96 0.17 138.64 78.23 20.05
9 1971.42 2.61 915.11 1458.19 1342.06 2847.41 90.57 4.15 0.06 1.07 0.19 186.01 114.52 28.45
10 1358.64 26.76 196.74 720.16 385.33 5645.82 326.26 0.6 0.01 1.1 0.35 104.51 36.33 42.45

Behavioral clusters example


An example of telecom behavioral clustering
Cluster 1: 9th or 10th in Cluster 10: #1 IN 10/34
everything except - #5 Measures,#1 SMS, Local IN -
10 #1 in BILL COMPLAINTS, #1 in
in BILL COMPLAINTS 1
ARPU per MOU, #10 in ILD,
Cluster Avg. #8/9 in OFF-net-IN
No. ARPU
Cluster 2:8th or 9th in all 2
1 504.77
except ILD-IN - #3 in
2 673.42
BILL COMPLAINTS 3 927.21
9
4 951.06 Cluster 9: #1 in 13/34
3 Measures and #1/2/3 in 30/34,
5 1243.19
Cluster 3:8th or 9th in all
6 1289.07 #4 in ARPU per MOU, #7 ILD-
except ILD, NLD and #4 7 1294.39 IN, #6 in BILL COMPLAINTS
in BILL COMPLAINTS 8 1732.47 8
4 9 1971.42
10 1358.64
Cluster 8: #1 ILD-OUT MOU,
Cluster 4: #4/5 in 14/34
#2/3 in 20/34 Measures - #2 in
Measures - #2 ARPU
7 OUT, ARPU and #10 in BILL
per MOU and in #3 in 5 COMPLAINTS
IN-Local Onnet MOU 6

Cluster 7: #2 in ILD-IN
Cluster 5: #4/5 in 19/34 and ILD OUT (all) and
Measures - #3 in Local Cluster 6: #1/2/3 in 19/34 NATIONAL ROAM - #2
OUT Calls MOU Measures - #1 ARPU per in BILL COMPLAINTS
MOU, INCOMING - ILD,
NLD, ON-OFFNET, SMS

Behavioral clusters example


Customer Lifetime Value (CLV) Study example:

AC : Acquisition Cost (one time)
Rt : Revenue at time “t”
SCt : Servicing Cost at time “t”

CLV calculation formula example


Product usage by time-of-day points to needs
• To monetize subscriber time better than our competitors, we need to know:
– Whether they use our services for work, play, family or a combination;
– When and where they use our services;
• So if we know what they use our services for, we need to know how and when
we should try to promote something to them based on:
– Their Supply of available time and attention
– When they’re more likely to Listen
– Their Demand for what we’re offering (probability of additional needs and wants)
– And our ability to provide them

10
8
6
4
2 At Work
0 At Play


Product usage by time-of-day points to needs
WEEKEND BTS-01 BTS-02 BTS-03 BTS-04 BTS-05 BTS-06 BTS-07 BTS-08 BTS-09 BTS-10

While at Play Segments: 00:00-01:00
02:00-03:00
03:00-04:00
04:00-05:00
Weekend While-at-Play – Use by BTS
• End-of-the-day, early morning calls home or 05:00-06:00
06:00-07:00
two fellow party-goers; 07:00-08:00
08:00-09:00
09:00-10:00

• Planning the weekend, evening, lunch, 10:00-11:00
11:00-12:00

outings with friends/co-workers, etc…; 12:00-13:00
13:00-14:00
14:00-15:00
15:00-16:00
• Calling local friends, planning the evening, 16:00-17:00
17:00-18:00
chatting, web-surfing; 18:00-19:00
19:00-20:00
20:00-21:00

• Subscribers making and receiving calls from Sat/Sun by BTS
21:00-22:00
22:00-23:00
23:00-24:00
friends or relatives overseas (in/out); WEEKDAY BTS-01 BTS-02 BTS-03 BTS-04 BTS-05 BTS-06 BTS-07 BTS-08 BTS-09 BTS-10
00:00-01:00

• Families making and receiving calls from
02:00-03:00
03:00-04:00
04:00-05:00
Weekday While-at-Work – Use by BTS
overseas. 05:00-06:00
06:00-07:00
07:00-08:00
08:00-09:00
While at Work Segments: 09:00-10:00
10:00-11:00
11:00-12:00

• Weekday business calls, conference calls, 12:00-13:00
13:00-14:00

sales calls, vendor calls, etc… 14:00-15:00
15:00-16:00
16:00-17:00
17:00-18:00
• Saturday first-half and Sunday last-half of the 18:00-19:00
19:00-20:00
day business calls 20:00-21:00

Mon-Fri/Sat by BTS
21:00-22:00

•
22:00-23:00
Except for those who work all day Saturday and 23:00-24:00

those that are off Saturdays Home BTS = local cell transmitter Work
Usage: Low/No Medium High


Daily mobility patterns identify type of user (home/work)
WEEKDAY BTS-01 BTS-02 BTS-03 BTS-04 BTS-05 BTS-06 BTS-07 BTS-08 BTS-09 BTS-10 WEEKDAY BTS-01 BTS-02 BTS-03 BTS-04 BTS-05 BTS-06 BTS-07 BTS-08 BTS-09 BTS-10
00:00-01:00 00:00-01:00
02:00-03:00 02:00-03:00
03:00-04:00
04:00-05:00
Weekday While-at-Home – Use by BTS 03:00-04:00
04:00-05:00
Weekday While-at-Work – Use by BTS
05:00-06:00 05:00-06:00
06:00-07:00 06:00-07:00
07:00-08:00 07:00-08:00
08:00-09:00 08:00-09:00
09:00-10:00 09:00-10:00
10:00-11:00 10:00-11:00
11:00-12:00 11:00-12:00
12:00-13:00 12:00-13:00
13:00-14:00 13:00-14:00
14:00-15:00 14:00-15:00
15:00-16:00 15:00-16:00
16:00-17:00 16:00-17:00
17:00-18:00 17:00-18:00
18:00-19:00 18:00-19:00
19:00-20:00 19:00-20:00
20:00-21:00 20:00-21:00

Mon-Sun by BTS Mon-Fri/Sat by BTS
21:00-22:00 21:00-22:00
22:00-23:00 22:00-23:00
23:00-24:00 23:00-24:00

WEEKEND BTS-01 BTS-02 BTS-03 BTS-04 BTS-05 BTS-06 BTS-07 BTS-08 BTS-09 BTS-10 WEEKDAY BTS-01 BTS-02 BTS-03 BTS-04 BTS-05 BTS-06 BTS-07 BTS-08 BTS-09 BTS-10
00:00-01:00 00:00-01:00
02:00-03:00 02:00-03:00
03:00-04:00
04:00-05:00 Weekend While-at-Play – Use by BTS 03:00-04:00
04:00-05:00 Before & After Work – Use by BTS
05:00-06:00 05:00-06:00
06:00-07:00 06:00-07:00
07:00-08:00 07:00-08:00
08:00-09:00 08:00-09:00
09:00-10:00 09:00-10:00
10:00-11:00 10:00-11:00
11:00-12:00 11:00-12:00
12:00-13:00 12:00-13:00
13:00-14:00 13:00-14:00
14:00-15:00 14:00-15:00
15:00-16:00 15:00-16:00
16:00-17:00 16:00-17:00
17:00-18:00 17:00-18:00
18:00-19:00 18:00-19:00
19:00-20:00 19:00-20:00
20:00-21:00 20:00-21:00

Sat/Sun by BTS Mon-Fri/Sat by BTS
21:00-22:00 21:00-22:00
22:00-23:00 22:00-23:00
23:00-24:00 23:00-24:00

BTS = local cell transmitter Usage: Low/No Medium High


Overlaid type of usage by channel (www, voice, text)
WEEKDAY BTS-01 BTS-02 BTS-03 BTS-04 BTS-05 BTS-06 BTS-07 BTS-08 BTS-09 BTS-10 WEEKDAY BTS-01 BTS-02 BTS-03 BTS-04 BTS-05 BTS-06 BTS-07 BTS-08 BTS-09 BTS-10
00:00-01:00
Weekday While-at-Home – Use by Weekday While-at-Work – Use by
00:00-01:00
02:00-03:00 02:00-03:00
03:00-04:00 03:00-04:00
04:00-05:00
05:00-06:00
Product & BTS 04:00-05:00
05:00-06:00
Product & BTS
06:00-07:00 06:00-07:00 WWW
07:00-08:00 07:00-08:00 WWW S
08:00-09:00 WWW 08:00-09:00 S V V
09:00-10:00 WWW V V V 09:00-10:00 V V S S
10:00-11:00 V S S V 10:00-11:00 WWW V WWW
11:00-12:00 V S V S 11:00-12:00 V V
12:00-13:00 S V V V S 12:00-13:00 V V
13:00-14:00 S S V V 13:00-14:00 WWW S S V
14:00-15:00 WWW V S V 14:00-15:00 WWW S S V
15:00-16:00 V V S S V 15:00-16:00 S S V
16:00-17:00 V V V V S 16:00-17:00 V
17:00-18:00 V S V V 17:00-18:00 S S V
18:00-19:00 V WWW V 18:00-19:00 S WWW V V
19:00-20:00 V V 19:00-20:00 S WWW V V
20:00-21:00 V S 20:00-21:00 WWW V V V V S

Mon-Sun by BTS Mon-Fri/Sat by BTS
21:00-22:00 V 21:00-22:00 V V V S S
22:00-23:00 WWW 22:00-23:00 V WWW WWW
23:00-24:00 23:00-24:00

WEEKEND BTS-01 BTS-02 BTS-03 BTS-04 BTS-05 BTS-06 BTS-07 BTS-08 BTS-09 BTS-10 WEEKDAY BTS-01 BTS-02 BTS-03 BTS-04 BTS-05 BTS-06 BTS-07 BTS-08 BTS-09 BTS-10
00:00-01:00 V V V V V V V V V 00:00-01:00
02:00-03:00
03:00-04:00
S
Weekend While-at-Play – Use by
S S S S 02:00-03:00
03:00-04:00
Before & After Work - – Use by Product
04:00-05:00
04:00-05:00
05:00-06:00 Product & BTS 05:00-06:00 & BTS
06:00-07:00 06:00-07:00 WWW
07:00-08:00 07:00-08:00 V WWW
08:00-09:00 S 08:00-09:00 V V V V V
09:00-10:00 V V S S 09:00-10:00 S V V
10:00-11:00 V V S WWW 10:00-11:00
11:00-12:00 V V S 11:00-12:00
12:00-13:00 V S V V 12:00-13:00
13:00-14:00 V V S V 13:00-14:00 V S WWW
14:00-15:00 V V S V 14:00-15:00 V S WWW
15:00-16:00 V V S V V 15:00-16:00
16:00-17:00 V V V 16:00-17:00
17:00-18:00 V V S 17:00-18:00
18:00-19:00 V S S WWW 18:00-19:00 V V
19:00-20:00 S V WWW WWW 19:00-20:00 V V V
20:00-21:00 V V V V 20:00-21:00 V S S V V V
WWW WWW V S V S V V V
Sat/Sun by BTS Mon-Fri/Sat by BTS
21:00-22:00 21:00-22:00
22:00-23:00 WWW S S S S 22:00-23:00 WWW S S
23:00-24:00 WWW WWW WWW WWW WWW WWW WWW
WWW WWW 23:00-24:00

BTS = local cell transmitter Usage: Low/No Medium High


Micro-segmentation-based targeting (model based):
• Lifestage, Lifestyle, Segmentation tracking for each new and high-
value 3G/4G target subscriber
– To optimize incremental revenue and retention (See following 2 slides)
• A "What's Your Interest" Behavior Segmentation study based on 7-
digit SMS numbers and keywords to outside vendors;
– A data mining exercise to understand subscriber purchases and the
interests they reflect for our subscribers – to improve targeting
• The Next-Best-Offer(s) study
– Identifying 1-5 high-propensity-to-purchase Offers (in priority sequence)
– To include 3G/4G offering models to identify highest-propensity targets
• Credit rating (for new subs) through their Network Credit Score (NCS)
based on the credit of known subscribers they call in their first weeks;
– A study of the assumption that a new subscriber’s credit score / default
propensity rating will be similar to that of his/her friends and/or co-workers
with whom he/she speaks;
– Very useful in the first weeks/months of a subscriber’s relationship when direct credit
history is not available


Revenue & retention strategies by lifecycle & segment
Rchg Amt
First Experience Includes Action/Offer
1. First Sales & • Prospect Acq. • Right Plan?
Mktg Contact • Lead Source • Multi-SIMs?
2. First Cust. • CAV-CV-AV • Interests?
Documents • Demographics • Referrals?
C
U 3. First Call- • QA Monitoring • Credit needs?
SMS-Data • Roam-STD-ISD • Referrals?
S
4. First Voice • On-Net-SMS • Call Patterns?
T Promotion • Roam-STD-ISD • Offers?
O
5. First Data, H/S • Data, VAS • Handset?
M or VAS Promo • GPRS, WAP • Get email add?
E
6. First Cust. • Issue • Billing?
R Care Contact • Request • Quality?

7. First Outgoing • Usage high • Extend credit ?
T Call Barring • Payment late • Solve Issue ?
R 8. First Churn • Solve issue • Handset?
A Prevention • Add value • Plan or Pack?
C 9. First Service • Money • Higher limit?
K Reactivation • Documents • Other help?
S 10. First Referral • Contact info • CUG?
Request • Incentives • Cash rewards

11. First Win- • Alt contact • Pre-MNP?
Back Attempt • Solve issues • Post-MNP?
Week-1 Week-2 Month-1 Qtr-1

24
Wk-1 Wk-2 Wk-3 Wk-4
Copyright Campaignist, Inc. ®

Revenue & retention strategies by lifecycle & segment

Strategy Tactics
1. Segment customer base by how 1. Map the behavior of new and
they use and value our services existing high-value customers from
during the day: first contact to better understand:
– Personal usage
– When they use the services
– Family usage
– How they use the services
– Productive usage
– What issues they might face
– Non-usage
– Opportunities for add-on services
2. Track this behavior from first
contact with the customer using 2. Create a Net Customer Value
existing systems and data: (NCV) for each subscriber:
– Optimize return-on-customer – Their social network profile and that of
interaction from both a revenue and their contacts including in/out patterns,
customer satisfaction perspective credit profiles, and more;
(the definition of CVM)
– Automate tracking of key events and – Their network ARPU based on the total
set up proactive solution triggers. revenue at risk x AON (with incoming +
outgoing calls) if they port out;



• A series of 2-5 day workshops can be run with a qualified facilitator
for each of the 5 key success factor areas for the purpose of:
– Gathering, analyzing and reporting on the current state of readiness vis-à-
vis competitors and global best-practices;
– Informing and transferring knowledge of how leaders in other 3G/4G-
enabled markets achieved and maintained leadership;
– Suggesting a desired best-practice state for teams given existing
capabilities and resources;
– Detailing the critical-path actions required to ensure organizational
readiness and implementation;



• Workshops would then be followed by implementation support as
needed to create:
– Roadmap and Best-practice process documentation
– Project and program governance
– Training and implementation support
– 3G/4G product and service development
– Content and context partner strategies


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