Option 1 present s New Rules, New Tools!
Today’s convention—the Pull Tab
- Before pull-tabs (1935-60)
- made of tin (not Aluminum)- Opened with a churchkey-Churchkey: forgotten tool
Pull-tab = Engineer + picnic + beer – churchkey- First invented in 1960
The Moral—not about beer cans
But the story: - not about beer cans
The main plot: -The obsolete tool
(churchkey)
TODAY’S CONVENTION
wasYESTERDAY’S INVENTION
The India story—a ‘digital’ consumer story
Urban user: 70% access internet dailyRural user: 60% use 2-3 times a week
Source: IAMAI, IMRB International, TRAI
The New Consumer Decision Journey
PURCHASING FUNNEL— a simple straight routeNEW CONSUMER DECISION JOURNEY—more complex and unpredictable
Purchasing funnel theory gives way to complexity
The Active Evaluation Phase
• Active evaluation adds 2-3 more brands to your initial consideration
• Only BUDGET and COLOR are non-negotiable
• At least ONE brand initially considered gets eliminated
• 54% of car buyers change their consideration set during their research phase
The car buyer is unpredictable and price-sensitive
Google searches—in evaluation phase
40%YoY growth in car queries
100+queries every second on Google
search
8-10 times dailyOn average every car buyer uses Google search during his car buying journey
50% car buyers research themselves
25-30%additional car buyers have their friends and family research for the car purchase
Data on consumer behavior—a problem of plenty
Solving A Big Data Problem
• Are search queries related to real-world activity?• If so, which search categories/queries are relevant?
Deriving consumer insights from search queries
Consumer activity needs to be associated with search queries
Big Data—solution or problem?Traditional rule-based systems are not very effective
1) ADAPTABILITY
TRADITIONAL DECISION SUPPORT TOOLSSHORTCOMINGS:
GAME-CHANGER?INFORMATION OVERLOAD?
2) SCALE
Consumer QuerimetrixConsumer insights using Google Trends
TELEMETRY (REMOTE MEASURE)
CONSUMER SEARCH QUERIES
Uses framework proposed by Hal Varian and Steven Scott‘Predicting the Present using Bayesian Structural Time Series’ whitepaper series (2009-14)
The need for Machine LearningThe Swiss Army Knife of Business Intelligence tools
ADAPTABLE: multi-utility
SCALABLE: ASIMO to Predictive text
Consumer QuerimetrixWhat is the value proposition?
• Identifies proxy indicators
• Delivers on-ground insights
• Nowcasts to stay ahead of the herd
• Catches inflection points earlier
• Derives business insights using digital footprints
Consumer QuerimetrixWhat is the value proposition?
• identifies proxy indicators
• Delivers on-ground insights
• Nowcasts to stay ahead of the herd
• Catches inflection points earlier
• Derives business insights using digital footprints
Querimetrix—as a proxy indicatorHow are the online used car classifieds shaping up?• OLX is a clear leader from Google Trends
dataOLX leads Quikr in auto-related queries on Google
Normalized query trends for India car classifieds, 2004-current
Source: Google Trends, Kotak Institutional Equities
3799
038
130
3827
038
410
3855
038
690
3883
038
970
3911
039
250
3939
039
530
3967
039
810
3995
040
090
4023
040
370
4051
040
650
4079
040
930
4107
041
210
4135
041
490
4163
041
770
4191
042
050
4219
042
330
0
20
40
60
80
100
120 carwale cartrade olx quikr
Consumer QuerimetrixWhat is the value proposition?
• Identifies proxy indicators
• Delivers on-ground insights
• Nowcasts to stay ahead of the herd
• Catches inflection points earlier
• Derives business insights using digital footprints
The Maruti Baleno car launchWhat does Google Trends tell us about car launches?
21,000+Bookings in 10 days after
launch
56,000footfalls in 10 days of launch
9,000November 2015 sales (>i20)
40,000+Bookings since launch
Querimetrix—an ear to the groundComparing recent car launches on Google Trends
4085
340
895
4093
740
979
4102
141
063
4110
541
147
4118
941
231
4127
341
315
4135
741
399
4144
141
483
4152
541
567
4160
941
651
4169
341
735
4177
741
819
4186
141
903
4194
541
987
4202
942
071
4211
342
155
4219
742
239
4228
142
323
0102030405060708090
100
Honda Amaze Ford Ecosport Hyundai Creta Maruti Suzuki S-CrossHyundai Xcent Renault Kwid Maruti Suzuki Baleno
Car model launches result in large online inquiry of launched model
Google Trends search volumes of recently launched cars in India, 2011-15
Source: Google Trends, Kotak Institutional Equities
KwidSecond-best launch
Baleno
Best launch of the year
Querimetrix—on ground insightsDoes higher digital curiosity imply anything?
A linear relationship is evident between advance bookings and search volumes
The relationship between search queries and advance bookings during car launches
Source: Google Trends, Kotak Institutional Equities
10 20 30 40 50 60 70 80 90 1000
5,000
10,000
15,000
20,000
25,000
30,000 Maruti S-Cross Hyundai Creta Hyundai Xcent Honda AmazeFord Ecosport Trend Linear (Trend) Maruti Baleno
Indexed Google query volumes
Adva
nce
book
ings higher
search-share
higher
bookings
Querimetrix—an ear to the groundIs it merely a reflection of traditional media spends?
Advertising spends may not always guarantee digital buzz
The relationship between traditional media spend and advance bookings during car launches
Source: Google Trends, TAM, Kotak Institutional Equities
10 20 30 40 50 60 70 80 90 1000
10,00020,00030,00040,00050,00060,00070,00080,00090,000
100,000
Maruti S-Cross Hyundai Creta Hyundai Xcent Honda AmazeFord Ecosport Maruti Suzuki Ertiga
Indexed Google search share
Adve
rtisin
g sp
ends
(Rs.
'000
)
Notes:
(a) Advertising spends are based on TAM estimates of TV and Print spends during launch week.
NOlinear relationship
Consumer QuerimetrixWhat is the value proposition?
• Identifies proxy indicators
• Delivers on-ground insights
• Nowcasts to stay ahead of the herd
• Catches inflection points earlier
• Derives business insights using digital footprints
Consumer QuerimetrixWhat is the value proposition?
• Identifies proxy indicators
• Delivers on-ground insights
• Nowcasts to stay ahead of the herd
• Catches inflection points earlier
• Derives business insights using digital footprints
Querimetrix—nowcastingThe BSTS algorithm catches inflection points earlier
Querimetrix nowcasts ~195,00 passenger car sales in January
Consumer Querimetrix nowcasts of total passenger car sales, 2009-16 (units)
Source: SIAM, Kotak Institutional Equities
Jan-
09Ap
r-09
Jul-0
9Oc
t-09
Jan-
10Ap
r-10
Jul-1
0Oc
t-10
Jan-
11Ap
r-11
Jul-1
1Oc
t-11
Jan-
12Ap
r-12
Jul-1
2Oc
t-12
Jan-
13Ap
r-13
Jul-1
3Oc
t-13
Jan-
14Ap
r-14
Jul-1
4Oc
t-14
Jan-
15Ap
r-15
Jul-1
5Oc
t-15
Jan-
16
0
50,000
100,000
150,000
200,000
250,000Total passenger cars (units) 23%
Reduction in prediction error
(MAE) over traditional models
performs better near
Inflection points
Consumer QuerimetrixWhat is the value proposition?
• Identifies proxy indicators
• Delivers on-ground insights
• Nowcasts to stay ahead of the herd
• Catches inflection points earlier
• Derives business insights using digital footprints
Querimetrix—Business insightsONLINE EVALUATION CHANGING THE RULES
1
3
2
1. Evaluation
2. Car loans
3. Car exchange
Car finance—moves up the ladderSimultaneously assessing cars and loan options online
Car loan searches and car comparisons happening simultaneously
Google Correlate results for the keyword 'car loan' in India and US, 2004-15
Source: Google Correlate, Kotak Institutional Equities
• More loans to be sourced directly Loan origination costs may come down
• Dealer profitability may come down OEMs may need to increase incentive
• Car financing can be a differentiator Captive financing can innovate
3799
038
116
3824
238
368
3849
438
620
3874
638
872
3899
839
124
3925
039
376
3950
239
628
3975
439
880
4000
640
132
4025
840
384
4051
040
636
4076
240
888
4101
441
140
4126
641
392
4151
841
644
4177
041
896
4202
2
car loan (IN) compare cars (IN) emi calculator (IN)
Used car markets—influencing car salesThe effect on—1) New car sales and 2) Trade-ins
1 1+223%
yoy growth in used car queries
Online classifieds queries impede
new car sales
Trade-inan important
retention strategy
Online
SubstituteEntry-level car with a second-hand
car
Evaluation—landscape gets competitiveSearch-share for major car makers has dropped
2010 20150
20
40
60
80
100
120Maruti Suzuki Hyundai
Maruti Suzuki and Hyundai have both lost search-share since CY2010
Normalized query trends for Indian car OEMs, 2004-current
Source: Google Trends, Kotak Institutional Equities
All options
are being evaluated
Evaluation—mindshare gets costlierAdvertising spends for the industry going up
Rising advertising spends indicate costlier mindshare
Estimated ad spends per car sale for OEMs in India, 2012-2015 (Rs/car)
Source: TAM, Kotak Institutional Equities
2012 2013 2014 201501,0002,0003,0004,0005,0006,0007,0008,0009,000
10,000
0
1,000
2,000
3,000
4,000
5,000
Maruti Udyog Ltd Hyundai Motor India LtdHonda Siel Cars India Ltd Total passenger carsAvg. TV unit costs (Rs/sec) (RHS) Avg. Print unit costs (Rs/sec) (RHS)
Notes:
(a) TAM data used for TV and Print advertising spends (discounted from rate card).
(b) Advertising spends are divided over total car and utility vehicle sales.
(c) TAM data available till August 31, 2015.
Quick take—Maruti SuzukiRetaining loyal customers and increasing reach
Howhas Maruti maintained
market-share?
Great strategy
is what helped retain market-share
Relating search queries and car salesThe relationship varies by OEM and models
CAR SALES
SEARCH QUERIES
• More model searches (i10 & i20), more sales
SIMPLE
SIMPLER
• More potential car buyers, more Maruti demand
Querimetrix: just warming up!Two-wheelers and Beauty are next on the cards
Dec-
04Ap
r-05
Aug-
05De
c-05
Apr-0
6Au
g-06
Dec-
06Ap
r-07
Jul-0
7No
v-07
Mar
-08
Jul-0
8No
v-08
Mar
-09
Jul-0
9No
v-09
Mar
-10
Jul-1
0Oc
t-10
Feb-
11Ju
n-11
Oct-1
1Fe
b-12
Jun-
12Oc
t-12
Feb-
13Ju
n-13
Oct-1
3Fe
b-14
Jun-
14Se
p-14
Jan-
15M
ay-1
5
0
10
20
30
40
50
60
Hero MotoCorp Bajaj Auto TVS Motor Companyhonda bikes Yamaha Motor Company Royal Enfield
Two wheelers do not mean Bajaj and Hero anymore!
Normalized 12-month rolling Google Trends for various two wheeler manufacturers
Source: TAM, Kotak Institutional Equities