Upload
-
View
1.643
Download
0
Embed Size (px)
Citation preview
©TNS
Overall, Russian consumers are…
More money conscious
Less happy about
standards of living
Are worried about the price
increase
1
©TNS
The shoppers are becoming more money conscious…
3
50%
58%
49%
43%
25%
35%
45%
55%
65%
2008/1 2009/1 2010/1 2011/1 2012/1 2013/1 2014/1 2015/1
% of population
+8ppSilly to spend money on luxury goods
–6 pp Do not go to cheap stores
2015 vs. 2008
Source: TNS, Marketing Index / TGI, Russia (cities 100+), Base: 18+ y.o.
©TNS
…and are better planning their purchases
4
48%
50%
37%
29%
47%
56%
25%
35%
45%
55%
65%
2008/1 2009/1 2010/1 2011/1 2012/1 2013/1 2014/1 2015/1
% of population
+2ppMake no unexpected expenditures
–9 ppSpend money without thinking
2015 vs. 2008
+9ppAlways read carefully the product ingredients
Source: TNS, Marketing Index / TGI, Russia (cities 100+), Base: 18+ y.o.
©TNS
Claiming changes in consumption people tend to save money in different ways:
5
reduce budget… …or leave categories
Focus on promo and sales
Change price segment
Lapse some categories
Switch to DIY
©TNS
Building a pricing system around better data
6
"When we started to take pricing seriously, we realized that we needed not only to collect better data but to be more systematic about using it.“
(Petr Partsch – sales chief for Linde Gases, Czech Republic)
©TNS
Better data with Technology Enabled Research
7
We’re listening, but are we learning?
We’re collecting data, but are we listening?
/ ˈlɪsn / [verb]
to hear what someone has said and understand that it is serious and important
/ lɜːn / [verb]
to improve your behaviour as a result of gaining greater experience or knowledge of something
©TNS
A behavioural framework of consumer choice
8By 2017, 87% of connected devices will be smartphones or tablets
Behavioural framework of
consumer choice
Choice Model
Intelligent interviewing
Behavioural Economics
The expanded model puts buying decisions into context:
Consumers actively “build” their choice sets
Buying habits, price knowledge and brand images inform sets and choices
©TNS
Intelligent communication with active consumers
9
...
Task 1
Intervieweemakes her choice
New scenario is designed on the fly
Task 2 Task 3
utilitybalance
utilitybalance
Individual context data - habits- knowledge- perceptions
Intervieweemakes her choice
Design algorithm computes a tailored choice scenario with relevant products
New scenario is designed on the fly
©TNS
Two-fold innovation
10
Behavioural Economics
Habits, heuristics and cognitive limitations of decision makers inform the design
Context information is treated as signal, not noise
Intelligent interviewing
Rather than survey passive respondents, we interact with individual consumers
We get better data from shorter, simpler interviews
©TNS
A case study
12
Market simulations are the key output of our pricing tool:
How strongly will buyers react to new pricing scenarios?
In our case study we look at the German beer market in
the first 26 weeks of 2015.
©TNS
Weekly market simulations for Krombacher 20x0.5 ltr
13
w1 w2 w3 w4 w5 w6 w7 w8 w9 w10 w11 w12 w13 w14 w15 w16 w17 w18 w19 w20 w21 w22 w23 w24 w25 w260%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
market share
©TNS
Weekly market simulations for Krombacher 20x0.5 ltr
14
w1 w2 w3 w4 w5 w6 w7 w8 w9 w10 w11 w12 w13 w14 w15 w16 w17 w18 w19 w20 w21 w22 w23 w24 w25 w260%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
market share
conventional method
Conventional choice models tend to overestimate the impact of price changes
©TNS
w1 w2 w3 w4 w5 w6 w7 w8 w9 w10 w11 w12 w13 w14 w15 w16 w17 w18 w19 w20 w21 w22 w23 w24 w25 w260%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
market share
conventional method
new method
Weekly market simulations for Krombacher 20x0.5 ltr
15
Mean deviation is reduced by
22%
The new method predicts the impact of price changes on consumer choice much more accuracy
©TNS
Listen to each respondent and learn
16
Our behavioural framework implies that the individual
context of choice matters:
Does the individual respondent know prices?
Which brands are in her purchase repertoire?
©TNS
The role of price knowledge
17
We expect that buyers with little or no awareness of
prices in the category are less price-sensitive.
Do we find that in our market simulations?
©TNS
The role of price knowledge
18
9.99 € 10.99 € 11.99 € 12.99 € 13.99 €
with awareness
without awareness
Conventional method
9.99 € 10.99 € 11.99 € 12.99 € 13.99 €
New individually adaptive method
25%
Differential impact leads to realistic predictions of price elasticity
Krombacher changes
in price, all others
remain constant
5%
©TNS
The role of brand repertoires
19
We expect that consumers do not change their habits easily.
They will be price-sensitive if a particular brand is in their
purchase repertoire. If they never bought a brand in the
past, they will ignore price changes of that brand.
Do we find that in our market simulations?
©TNS
The role of brand repertoires
20
9.99 € 10.99 € 11.99 € 12.99 € 13.99 €
occasionally bought
never bought
9.99 € 10.99 € 11.99 € 12.99 € 13.99 €
25%
Krombacher changes
in price, all others
remain constant
Differential impact leads to realistic predictions of switching behaviour
Conventional method New individually adaptive method
5%
©TNS
Better data in a mobile world
21
By 2017, 87% of connected devices will
be smartphones or tablets
When interviewed on mobile devices
50%interrupt the interview at least once.
After 10 minutes on a smartphone
40%drop out.
Mobile devices need shorter, smarter communication.
©TNS
Fewer data in a mobile world
22
Smaller displays, shorter attention spans
Fewer questions, fewer data per respondent
©TNS
Weekly simulations for Krombacher 20x0.5 ltr
23
w1 w2 w3 w4 w5 w6 w7 w8 w9 w10 w11 w12 w13 w14 w15 w16 w17 w18 w19 w20 w21 w22 w23 w24 w25 w260%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
market share
new method PC/Laptop
new method MOBILE
…Simulations from mobile data are slightly less accurate, but still very close to real market shares
©TNS
Building a pricing system around better data
24
Behavioural Economics
teaches us that context matters: Habits and heuristics inform buying decisions
helped us to build a behavioural framework around our choice models
Intelligent interviewing
Saves time and gives us better data
enables mobile surveys even for demanding prediction tools