Consumer Querimetrix

Option 1
presents
New Rules, NewTools!

CONVENTION TODAY. INVENTION YESTERDAY

An illustration—the Beer Can
PULL-TAB

Today’s convention—the Pull Tab

The Moral—not about beer cans
But the story:
- not about beer cans
The main plot:
-The obsolete tool
(churchkey)
TODAY’S CONVENTION
was
YESTERDAY’S
INVENTION

New Rules, New Tools
WHEN RULES CHANGE,
TOOLS NEED TO CHANGE!

CHANGING GROUND RULES ARE CHANGING

The India story—a ‘digital’ consumer story
Source: IAMAI, IMRB International, TRAI

Search queries—capture the Zeitgeist

EXAMPLE: THE EVOLVING CAR-BUYING JOURNEY

Car-buying journey—Then and Now!

The New Consumer Decision Journey
PURCHASING FUNNEL— a simple straight route
NEW CONSUMER DECISION JOURNEY—more complex and
unpredictable

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

Google searches—in evaluation phase
40%
YoY growth in car queries
100+
queries every second on Google
search
8-10 times daily
On 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

DECODING GOOGLE TRENDS: BIG DATA PROBLEM

Solving A Big Data Problem
• Are search queries related to real-world activity?
• If so, which search categories/queries are relevant?
Consumer activity needs to be associated with search queries

In A Big Data World
QUANT
OLD
TOOLS
BIG
DATA
WEEK #1

Big Data—solution or problem?
1) ADAPTABILITY
TRADITIONAL DECISION SUPPORT TOOLS
SHORTCOMINGS:
GAME-CHANGER?
INFORMATION OVERLOAD?
2) SCALE

QUERIMETRIX: BIG DATA MEETS MACHINE
LEARNING

Consumer Querimetrix
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 Learning
ADAPTABLE: multi-
utility
SCALABLE: ASIMO to
Predictive text

• Identifies proxy indicators
• Delivers on-ground insights
• Nowcasts to stay ahead of the herd
• Catches inflection points earlier
• Derives business insights using digital
footprints

• 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 indicator
• OLX is a clear leader from Google Trends data
OLX leads Quikr in auto-related queries on Google
Normalized query trends for India car classifieds, 2004-current
Source: Google Trends, Kotak Institutional Equities
0
20
40
60
80
100
120
Jan-04
Jun-04
Dec-04
May-05
Nov-05
Apr-06
Oct-06
Mar-07
Sep-07
Feb-08
Aug-08
Jan-09
Jul-09
Dec-09
Jun-10
Nov-10
May-11
Oct-11
Apr-12
Sep-12
Mar-13
Sep-13
Feb-14
Aug-14
Jan-15
Jul-15
Dec-15
carwale cartrade olx quikr

The Maruti Baleno car launch
21,000+
Bookings in 10 days after launch
56,000
footfalls in 10 days of launch
9,000
November 2015 sales (>i20)
40,000+
Bookings since launch

Querimetrix—an ear to the ground
0
20
40
60
80
100
Nov-11
Jan-12
Mar-12
Jun-12
Aug-12
Oct-12
Dec-12
Mar-13
May-13
Jul-13
Oct-13
Dec-13
Feb-14
May-14
Jul-14
Sep-14
Nov-14
Feb-15
Apr-15
Jun-15
Sep-15
Nov-15
Honda Amaze Ford Ecosport Hyundai Creta
Maruti Suzuki S-Cross Hyundai Xcent Renault Kwid
Car model launches result in large online inquiry of launched model
Google Trends search volumes of recently launched cars in India, 2011-15
Kwid
Second-best launch
Baleno
Best launch of the year

Querimetrix—on ground insights
A linear relationship is evident between advance bookings and search volumes
The relationship between search queries and advance bookings during car launches
0
10,000
20,000
30,000
40,000
0 20 40 60 80 100
Maruti S-Cross Hyundai Creta Hyundai Xcent Honda Amaze
Ford Ecosport Trend Maruti Baleno Linear (Trend)
Indexed Google query volumes
Advancebookings
higher
search-
share
higher
bookings

Querimetrix—an ear to the ground
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
0
20,000
40,000
60,000
80,000
100,000
0 20 40 60 80 100
Maruti S-Cross Hyundai Creta Hyundai Xcent
Indexed Google search share
Advertisingspends(Rs.'000)
Notes:
(a) Advertising spends are based on TAM estimates of TV and Print spends during launch week.
NO
linear relationship

Querimetrix—nowcasting
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
0
50,000
100,000
150,000
200,000
250,000
Jan-09
Jul-09
Jan-10
Jul-10
Jan-11
Jul-11
Jan-12
Jul-12
Jan-13
Jul-13
Jan-14
Jul-14
Jan-15
Jul-15
Jan-16
Total passenger cars (units) Passenger car sales nowcasts (units)
23%
Reduction in prediction
error (MAE) over
traditional models
performs better near
Inflection
points

Querimetrix—Business insights
1
3
2
1. Evaluation
2. Car loans
3. Car
exchange

Car finance—moves up the ladder
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
Jan-04
Sep-04
May-05
Jan-06
Oct-06
Jun-07
Feb-08
Nov-08
Jul-09
Mar-10
Nov-10
Aug-11
Apr-12
Dec-12
Sep-13
May-14
Jan-15
car loan (IN) compare cars (IN) emi calculator (IN)

Used car markets—influencing car sales
1
1
+223%
yoy growth in used car queries
Online classifieds
queries impede
new car
sales
Trade-in
an important retention
strategy
Online
Substitute
Entry-level car with a second-hand car

Evaluation—landscape gets competitive
0
20
40
60
80
100
120
2010 2015
Maruti Suzuki Hyundai
Maruti Suzuki and Hyundai have both lost search-share since CY2010
Normalized query trends for Indian car OEMs, 2004-current
All options
are being evaluated

Evaluation—mindshare gets costlier
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
0
1,000
2,000
3,000
4,000
5,000
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
2012 2013 2014 2015
Maruti Udyog Ltd Hyundai Motor India Ltd
Honda Siel Cars India Ltd Total passenger cars
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 Suzuki
How
has Maruti maintained
market-share?
Great
strategy
is what helped retain
market-share

Relating search queries and car sales
CAR
SALES
SEARCH
QUERIES
• More model searches (i10 & i20), more salesSIMPL
E
SIMPLER • More potential car buyers, more Maruti
demand

Querimetrix: just warming up!
0
10
20
30
40
50
60
Dec-04
Dec-05
Dec-06
Dec-07
Dec-08
Dec-09
Dec-10
Dec-11
Dec-12
Dec-13
Dec-14
Hero MotoCorp Bajaj Auto TVS Motor Company
honda 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

Consumer Querimetrix

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