Mr. Mayank Sahai presented at SAS Forum 2011 - one of the largest Analytics conference in India. He enlightened the audience on the role Analytics plays in Customer Management and organizations can maximize the value

1. Customer management and role
of Analytics
Mayank Sahai
Additional Vice President – Tata Teleservices Ltd
The only time a Tata phone won’t be accessible. Please switch off your mobile phones during presentations.

2. Agenda
Telecom scenario till recently
Changing dynamics
Role of Analytics in customer lifecycle management

3. Telecom scenario till recently – with huge addressable
market, the growth was primarily acquisition driven
Till now with huge untapped market, growth mostly happened due to incremental
reach & filling the gaps in product offerings
From around 10% in 2005 to almost 50% tele-
density in 2010
Operators expanding their network reach in
the small towns & villages
More than 95% subscribers coming from
prepaid segment
With monthly net-adds of 2-3 millions by Source: TRAI annual report 2009-10
major operators, acquisition was the key
focus up-till recently
As the subscriber base increased and cost to serve started to decline, the
innovation for acquisition happened primarily on tariff & price points

4. Changing dynamics – New opportunities & challenges
With more than 750 MN subscribers, the market is rapidly maturing. Retaining
customer is becoming more and more challenging
With around 13 operators, the competition is fierce.
Declining ARPU trend in an already low ARPU market is
forcing telco to optimize cost to serve – no scope for
missing the shot
Fresh acquisitions at lower ARPUs leading telcos to focus
on revenue enhancement from existing customers
Continuously evolving user behavior pose a challenge to
address customer requirement adequately.
With coarse segmentation, telcos finding tough to target
customers with broad based strategies across segments
Micro-segmentation will form the basis of retention & revenue enhancement
strategies in the near future

5. Segmentation – key for maximizing lifetime value of customer
N=1, R=G :– C K Prahalad
From statistical segmentation to value based segmentation
Influencers, followers, thought leader, calling behavior, broadcaster , online social animal–
new age segmentation is overwhelming
Micro-segmentation clubbed with deep analytics will form the basis of product evolution
Example
Users who want this Segmentation The Product
product
Telecom segment : Up-market handset Product: Kala-Ghoda art
Possible users group profile: Primarily user, high freq. of changing the handset, festival premium plan –
SEC-A, resident of south Mumbai, high ARPU, high data usage, high freq of contents (artists
frequent visitor to art events, active on visiting art related websites in past 3 months, wallpaper, screen savers,
social networking (online & offline), latched to BTSs located in south Mumbai sms alerts on event
tech savvy, an influencer region in night time (2100 to 0500 hrs) schedules and artist info)

6. Predictive analysis – prevention is better than cure
Starting with the business objective, Not data…
Business
objective
Predictive analysis & Segmentation and target
impact assessment group identification
A effective mix of Predictive analytics and Business input to be the key differentiating
factor for the telecom industry going forward

7. Product development – a multidimensional maze of variables
Product levers
Churn management
Up-Sell
Cross-Sell Multidimensional product development Product evolution
Acquisition
Market reaction
Product bonding
SMS
IVR
GPRS
USSD
Data (Internet)
Customer bonding
E-mail
SMS
IVR An integrated product development process to enable right
Internet
USSD
product mix for every subscriber – Analytics will decode the maze

8. Communication – Need for accurate & effective communication to all
users
ATL SMS
Right product
Retail Integrated Right
Products USSD
Communication communication
And IBD policy
OBD
Web Right customer
Services
E-mail
Cust. Policy Attributes Right time
care
Regulations
BTL
Internal comm. policy
User tolerance
Access medium
Communication Effectiveness
channels Product bonding
Customer preference
Huge expertise involved in chasing the right communication logic

9. Post intervention analysis
Evaluation of products, marketing & advertising efforts to be integral method for
reverse engineering strategies..
Subscriber
base
Insights from control group to
play a major role in the ‘fact
Target
based reverse engineering’ Segment
process
‘Champion & Challenger’
concepts to take prominence in Control
group
product evolution
Analytics to play key role in assessment of effectiveness of intervention and
course correction process.

10. Analytics to become pivotal – from information to
actionable intelligence
Fact based decision making will form the basis for creating differentiation.
Targeted product offerings for a small group of Life-time value analysis
users Enhance Up-Sell / Cross-sell Analysis
Retention strategies specially carved for
customers with high propensity to churn Customer
Retain Clarify
Engagement
Offerings designed to bridge the gap between
current offerings and customer need Churn / Loyalty Analysis Market segmentation
Customer service Analysis Customer profiling
Acquire
Near real time reaction resulting in instant
gratification Marketing mix analysis
Behavioral Analysis
Providing greater value to customer through
better profiling
Analytics to play an important role in the
entire life cycle of the customer.

11. Institutionalization of analytics based decision making
Key advantages of institutionalized analytics:
Information will become easier to understand and act upon
Reduced time to value
Transformations that are both significant and enduring
Clear focus on highest value opportunities
Factual insights to drive actions and deliver value

12. Integrated view of customer – organization wide
homogeneous understanding of customer
Informational synergies
between internal functions (i. e.
Product, Sales, marketing,
customer care, U&R etc) will
bring alignment toward key
strategic and business objective

13. THANK YOU