Mr. Pareek from Maruti Suzuki India Limited shares his views on the criticality to embrace analytics in organizational decision making and the role it plays in high performance organizations. He also discusses its need in the India subcontinent and the way forward for enterprises to propel - the usage of analytics for competitive advantage in today's dynamic market place.

1. make connections • share ideas • be inspired
India’s Largest Analytics Forum
Mr. Mayank Pareek
Managing Executive Officer - Marketing & Sales
Maruti Suzuki India Limited
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2. make connections • share ideas • be inspired
India’s Largest Analytics Forum
“Analytics for High Performance Organizations”
Mayank Pareek
Managing Executive Officer (Marketing & Sales)
Maruti Suzuki India Limited
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3. Flow of Presentation
Why India Need Analytics
Analytics @ Maruti Suzuki
Way Forward
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4. Why India Need Analytics?
Change
Environment Consumers Scale
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5. Why we need Analytics Analytics?
Why India Need
Environment
10 Growth Story of India 8.5
8 7.3
GDP Growth (%)
5.6 5.7
6
4 3.5
2
0
1950s-70s 1980s 1990s 2000s 2004-10
Fastest growing economy
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6. Why India Need Analytics?
Environment
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7. Why we need Analytics Analytics?
Why India Need
Environment Not a homogenous Market
Income Population
Incom (US Income Population
e class PPP) Million % Country (US PPP) (Million)
Highest 46212 8 0.7 Singapore 48520 5
High 30050 16 1 Australia 33400 21
Upper
7522 73 6 Thailand 7880 64
Middle
Lower
3046 286 25 Indonesia 3580 226
Middle
Lowest 1081 748 67 Sub-Saharan Africa 1870 800
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8. Why India Need Analytics?
Incredible but Diverse India
States- 29 States & 7 Union
Territories
Population – 1.21 Billion
Total Languages – Over 120
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9. Why we need Analytics Analytics?
Why India Need
Environment
Rural Urban
70% of the Population 30% of the population
Rising farm and non farm Top 10 cities make up
incomes around 10% of the population
but generate 30% of income
Policy measures like NREGA
reducing unemployment Increase in migration
Villages->Towns->Cities
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10. Why Companies Need Analytics?
Change
Environment Consumers
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11. Why we need Analytics Analytics?
Why India Need
Consumers
Share in world population, Population below 25 years,
Countries 2010 (%) 2010 (%)
Africa 15.0 60.5
India 17.6 50.1
China 19.6 36.8
USA 4.6 34.3
Europe 10.6 28.1
Japan 1.8 23.1
Young Consumers need
young and new products
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12. Why we need Analytics Analytics?
Why India Need
Consumers
100%
Necessities Discretionary Savings
As incomes rises
Discretionary
75% Spending goes up
50%
25%
0%
1980-81 1985-86 1990-91 1995-96 2000-01 2005-06 2009-10
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13. Why India Need Analytics?
Consumers
Aware
Bold, Expressive
Spontaneous
Ambitions
Demanding
experience
Indulgent
Choice seeker
Brand Conscious
Empowered
Attention
Seeking
individuality
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14. No Single India
Nation of Over a Billion Dreams.
Wide Geography , 29 States
70 % of the population in Rural India.
Social Transition, Urbanization .
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15. Why India Need Analytics?
Change
Environment Consumers Scale
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16. Why we need Analytics Analytics?
Why India Need
Scale is Changing
In 2010-11
Maruti Sales Enquires :55 Million
1200000
1000000 Sold : 1.3 Million
800000
Insurance :2 Million
600000
400000 Vehicles Serviced :
200000
1 Million
0
2005-06 2006-07 2007-08 2008-09 2009-10 2010-11
Entire Scale of operation is changing for Maruti &
Industry
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17. Why Companies Need Analytics?
Scale + Competition
3 19
Number of Players in 1980’s Number of Players in 2011
5 107
Number(~) of models in 1980’s Number of models in 2011
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18. Analytics @ Maruti Suzuki
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19. Analytics @ Maruti Suzuki
Single View of
Customer
Car Purchase Continuous
Engagement
Up-Sell
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20. Analytics @ Maruti Suzuki
Single View of
Customer
Sales- Alto
01st Nov 2005
Finance: ICICI
True value
Bank
Name: Mr R K Gupta
Mob :9832626333 7.9 Million
Add: B-10/1234 , Vasant Kunj
City : New Delhi
Service
10 Tiimes, Avg
Pin Code : 110070 Extended
Warranty Nov
Customers
DOB : 21st Feb 1967 2005
Spent 35000
Sex : Male
Marital Status : Married
Corporate Auto Card
Bharti Points: 2443
Insurance
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21. Analytics @ Maruti Suzuki
First Time Additional
Replacement
Customer Retention
29% 44%
Vasudha Goswami
Delhi 27%
Exchange
M800 Purchase - 1998 Customer tendency to
Alto Purchase - 2006
upgrade to higher models, Additional
Next : May be Swift
Exchange
A-Star Purchase - 2010
WagonR Purchase - 2006
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22. Analytics @ Maruti Suzuki
Results Direct Mailers were sent to
5 lakh+ prospects
Foreign Holiday for young
prospects
25%
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23. Why we need Analytics
Analytics @ Maruti Suzuki
Drive Campaigns
Beginning of the last year
•Competition launching new cars
•Price war through price cuts
•Increasing fuel prices
Maruti decided to play on mileage
Top Reason To buy Model A Model B Model C Model D
Style - Looks 2 3 3 2
Mileage 1 1 2 1
Comfort 3 2 1 3
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24. Analytics @ Maruti Suzuki
Brand Positioning
Engine Capacity -1197 cc/1248 cc Engine Capacity - 1197 cc/1248 cc
Platform- Same Platform- Same
Average Age 39.9 Average Age 32
Average Monthly Income Rs 56,000 Average Monthly Income Rs 60,000
Target Customer: Family Car Target Customer: Urban Buyer
Price :4.46 lacs Ex Sh Delhi Vxi Price :4.82 lacs Ex Sh Delhi Vxi
No Cannibalization
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25. Analytics @ Maruti Suzuki
Separating wheat from chaff
Customer Period Vehicle Purchased Qty
1997 Omni 17
1998 M800 28
Mahesh Agarwal
1999 ZEN 10
2000 WAGON R 2
Customer Period Vehicle Purchased Qty
1997 Omni 3
Renu Agarwal
2001 M800 7
Actually an SME
Customer Period Vehicle Purchased Qty not an
Kiran Agarwal 2011 Omni 1
Individual
Customer Period Vehicle Purchased Qty customer
Suman Agarwal 2011 M800 1
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26. Analytics @ Maruti Suzuki
Exchange
Average
Replacement
Cycle is 5
years
Data set of
workshop Result :Sold 2800
2800 Vehicles customers
exchanged with vehicles Vehicles
more than 9
year old Exchange
Penetration :23%
Based on
data Filters
& Tele calling 1,71,000
14,000 Prospects
vehicles
evaluated
Data set of workshop customers with more than 9 year old vehicles contacted.
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27. Analytics @ Maruti Suzuki
Exchange Trends
Mr T raghunathan
Mr Himanshu Porecha
City : Chennai
City : Jamnagar
Age : 39
Age : 47
Occupation : Service
Occupation : Service
•Kilometers Run : 52000 KM •Kilometers Run : 35000 KM
•Services : 16 times •Services : 11 times
•Insurance Claims : 4 •Insurance Claims : 1
Exchanged with Swift Exchange with Swift
Nov 2011 Nov 2011
Non Metro Customer Metro Customer
6 Yrs 3 Yrs 10 months
Non Metro customer replacement cycle is long vis-à-vis metro customer
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28. Way Forward
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29. Way Forward- Knowledge
Information Knowledge from Information
“MAR-TECH”
Marriage between Marketing &Technology
Customer Knowledge is Competitive Advantage
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30. Way Forward- Simple Solutions
Is Analytics an expedition
to cluster formation?
Advanced +Smarter Algorithms
Simple Business Solutions
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31. Way Forward- Marketing for One
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32. Way Forward- One Size Does Not Fit All
eate
•Every Customer is
Different
•Laser sharp precision
to understand customers
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33. Way Forward- Converting C2LC
Analytics
Customers Loyal Customers
Loyalty Program is more than a card
Create exit barriers for customers
Prevent customer flight-
Emotional engagement with customers
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34. make connections • share ideas • be inspired
India’s Largest Analytics Forum
Thank You
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