Breaking the Marketing Code in the
Era of Media Convergence
Ryan Li
Deputy Director
CTR Media & Consumption Behavior Research
September 16, 2015 Shanghai
How best to Integrate Offline and Online Data
in the era of Media Convergence?
Questionnaire data
CNRS-TGI whole year data
Annual sample size: ~100,000
Projected population: 180 million
Metered data
Continuously metered online behavior
of Internet users recruited from
amongst the CNRS-TGI samples
CNRS
CLICKSTREAM
Focus on offline media
habits, consumption and
lifestyle data
Focus on PC and mobile
network clickstream data
TV Radio
Newspaper Magazine
Internet Cinema
Other new
media
OOH
200+ product
categories / 6000+ brands
220+ lifestyle
360° Consumer Research + Internet Clickstream Monitoring
Demographics Media Habits
Product Consumption Lifestyles
Metered Data
Rich PC Website Clickstream Metrics
Overall
Category website
Specific
website
Clickstream(PC meter)
Metrics
Reach
Visited in past 4 weeks (P4W)
Visited in past 7 days (P7D)
Visited yesterday
Frequency # of days visited in P4W/P7D
Frequency of visits in P4W/P7D/yesterday
Duration
Effective time of visit in P4W/P7D/yesterday
Effective time per visit in P4W/P7D/yesterday
PV Page views in P4W/P7D/yesterday
Page views per visit in P4W/P7D/yesterday
APP
Overall
APP Category
APP Specific
Clickstream(APP )
Metrics
Reach
# of App users in P4W
# of App users in P7D
# of App users yesterday
Frequency
# of days launched in P4W/P7D/yesterday
Frequency of launches in P4W/P7D/yesterday
Duration
Effective time of use in P4W/P7D/yesterday
Effective time of use per launch in P4W/P7D/yesterday
Rich APP Usage Metrics
Core Values of CNRS-CLICKSTREAM
all media exposure
both online and offline
The only single source database with metered data
for PC & mobile
Inherited in full the powerful
lifestyle statements from
CNRS-TGI
A Case Study
Background
Issue
Client’s need
• Market demand for SUV continues to heat
up and SUV market keeps expanding.
• Market leader brand A has mediocre
performance recently with downward trend.
• Brand B is gaining in market share at the
expense of Brand A.
• How to help Brand A optimize its marketing
communication strategies to drive up sales?
Who are the Key Target Consumers?
销售渠道驱动 .
品牌广告驱动
知晓 Attention
兴趣 Interest
欲望 Desire
行动 Action
认知-销售转化模型
销量
预购率
认知率
AIDA model
Awareness
Purchase
intent
Sales
Brand
marketing
driven
Sales
channel
driven
.
10.
20.
30.
40.
50.
15-24 25-34 35-44 45+
SUV intender Non SUV intender
How to identify SUV Core Purchase Intenders?
Sex Age Brand
Male 62%
Female
38%
Male 57%
Female
43%
34
31
35
33
32
33
CR-V
RAV4
X-TRAIL
Tiguan
ix35
Total
Avg. Age of Purchase
Intenders %
%
%
%
%
Data source: CNRS-Clickstream 2015
Shift focus from basic demographic
attributes to values
Demographic attributes only tell if consumers can afford to buy.
It’s the deep-rooted personal values and beliefs that dictate
which brand consumers will buy
Similar demographic attributes, but different
choice of cars
Lamborghini Gallardo
Benz Marco Polo
Sex: Male
Age: Post-‘70s and Pre-’75s
Occupation: Well-known performer
Income: High-end individual
——Very similar in background, but starkly different in consumption choice
Family-centered
From a value-based perspective, pinpoint
where SUV purchase intenders concentrate
I will sacrifice time with family for personal improvement
I w
ant
to g
et t
o t
he
ver
y t
op
in
my c
aree
r
Strongly
disagree Strongly
agree
Strongly
agree
Individualism
Career-minded Career-family
balance
Area concentrated with
SUV purchase intenders
totaling:
2,744,000
which accounts for
45.7%
of all SUV intenders
Data source: CNRS-Clickstream 2015
More brand A purchase intenders lie to the left of
the encircled area. Inside the encircled SUV
intender concentrated area, brand A lags behind
by 4.2 percentage points.
0.8% 4.3% 6.6% 6.6% 5.5%
0.7% 9.3% 13.7% 22.1% 3.3%
0.6% 4.0% 11.3% 5.8% 0.4%
0.6% 2.1% 1.5% 0.3% 0.3%
0.3% 0.0% 0.0% 0.0% 0.0%
2.4% 6.3% 2.8% 4.7% 4.1%
1.7% 10.8% 13.2% 17.9% 3.9%
0.8% 7.6% 9.4% 5.4% 1.2%
0.8% 2.0% 1.0% 2.4% 0.0%
1.2% 0.5% 0.0% 0.0% 0.0%
Comparison of SUV purchase intenders’ distribution: Brand A versus Brand B
Distribution of brand B intenders matches that of
the total SUV category. Moreover, it is 2 points
ahead in the encircled SUV intender concentrated
area.
The concentrated area amasses 45.7% of
the total SUV purchase intenders, which
is a huge potential leverage
Data source: CNRS-Clickstream 2015
B品牌预购人群 A品牌预购人群
Diagnosis of the Marketing Problem
SUV总体预购人群
0.0%-5.0% 5.0%-10.0% 10.0%-15.0% 15.0%-20.0% 20.0%-25.0%
Weakness area: career-minded type
63.3% of the total SUV intenders only
contributes 53.5% of the potential brand A
purchasers.
Strength area: balanced type
19.6% of the total SUV intenders
contributes 29% of the potential
brand A purchasers.
Strength area: career-minded type
63.3% of the total SUV intenders
contributes 66.2% of the potential brand
B purchasers.
Brand A
Intenders Brand B
Intenders
SUV total
Intenders
Data source: CNRS-Clickstream 2015
Target Audience Optimization Take career-minded consumers as the core
target consumers
Optimize advertising
strategy
Data source: CNRS-Clickstream 2015
Cross-Media advertising budget allocation ——Rational budget allocation based on the media habits of the core SUV
purchase intenders
Media category
% of total ad budget in 2014
Internet 59%
Radio 18%
Newspaper 11%
OOH 7%
TV 4%
Magazine 1%
Brand A advertising budget -
current budget allocation
Magazine
[值]
Radio
[值]
TV
19%
OOH
27%
Internet
26%
Newspaper
15%
Optimized budget allocation
Data source: CTR MI advertising monitoring data
Data source: CNRS-Clickstream 2015
OOH Advertising Strategy ——Transportation ads and LCD TV ads were underrepresented and
spend on these two types of ads should be increased
Daily reach - total Daily reach – Brand A
core intenders Index
Transportation ads 83% 84% 102
LCD TV ads 77% 81% 105
Big screen LED ads 80% 78% 98
Other OOH ads 88% 88% 100
Index: 100 is the benchmark,>100 indicates more likely than average to see the ad; <100 indicates less likely to see the ad
Data source: CNRS-Clickstream 2015
TV Advertising Strategy ——The variety & talent shows have high advertising value and increased
purchase of TV spots on these shows is recommended
News broadcasting is far
ahead of other TV programs
in audience reach
23%
Variety & talent shows
Sports
Foreign film and TV drama
Finance
Documentary
Index>=117
Daily coverage of
core consumers Type of programs core consumers
are more likely to watch
Index: 100 is the benchmark,>100 indicates more likely than average to watch the show; <100 indicates less likely to watch the show
Data source: CNRS-Clickstream 2015
TV Advertising Strategy ——Channel 1 and Channel 3 are prone to be overrated. Channel 2 covers the
highest percentage of core consumers and deserves more consideration.
23%
16% 15%
Channel 1 Channel 2 Channel 3
Daily reach - total
16% 14%
10%
Channel 2 Channel 1 Channel 3
Daily reach – Brand A core
consumers
Data source: CNRS-Clickstream 2015
Website Visited in P4W
(by Index) Effective average time
on site
141 91 minutes
138 105 minutes
129 80 minutes
Online Advertising Strategy ——Focus on high traffic websites visited by core consumers
Data source: CNRS-Clickstream 2015
Which sub-domains can better draw their attention?
Visited in P4W (by Index)
CAR 229
TECHNOLOGY 151
SPORTS 138
FASHION 110
EDUCATION 193
CAR 125
FASHION 124
SPORTS 106
HEALTH 219
SPORTS 129
ENTERTAINMENT 111
NEWS 92
Data source: CNRS-Clickstream 2015
13.5
9.2
5.7
3.6 3.6 3.4 2.8 2.6 2.4
1.8 0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
Which car websites do they visit more often? Visited in P4W (%)
Data source: CNRS-Clickstream 2015
107 PAGES 58 PAGES
8 PAGES
3 PAGES
6 PAGES 11 PAGES
+24%
+33%
-85%
0% -27%
+100%
How often do they visit the car websites?
Data source: CNRS-Clickstream 2015
Which websites do they visit to watch streaming videos?
Data source: CNRS-Clickstream 2015
24 minutes
10 minutes
6 minutes
13 minutes
4 minutes
4 minutes
How long do they stay on the video website each
time?
Data source: CNRS-Clickstream 2015
More details are available in the latest CNRS-Clickstream Database
To be released in September 2015!
Release date Data period City coverage Sample size
09/2015 01/2014-03/2015 All 60 CNRS-TGI cities 92,900
12/2015 07/2014-09/2015 All 60 CNRS-TGI cities 92,900
03/2016 10/2014-12/2015 All 60 CNRS-TGI cities 92,900
06/2016 01/2015-03/2016 All 60 CNRS-TGI cities 92,900
09/2016 04/2015-06/2016 All 60 CNRS-TGI cities 92,900
12/2016 07/2015-09/2016 All 60 CNRS-TGI cities 92,900
Thank you |
28
Top Related