choice modelling in lower income countries

24
How to predict choice of lower income consumers Robert Dossin Mike Mabey SKIM Europe SKIM USA A mobile study about painkillers choices in Indonesia, Brazil & South Africa

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Page 1: Choice modelling in lower income countries

How to predictchoice of lowerincome consumers

Robert Dossin Mike Mabey

SKIM Europe SKIM USA

A mobile study about painkillers choices

in Indonesia, Brazil & South Africa

Page 2: Choice modelling in lower income countries

Lower & Middle classIn Emerging markets

70.000.000each year BRIC+ 7 trillion

2015 20 trillion

2025

Source: McKinsey & Company ‘The great rebalancing, 2010’

Page 3: Choice modelling in lower income countries

Developing research methods

Source: GRIT report 2015 – Greenbook/methods

Page 4: Choice modelling in lower income countries

More demanding - faster

Page 5: Choice modelling in lower income countries

Mobile Connects the Unconnected

Page 6: Choice modelling in lower income countries

PC ownership of mobileusers

PC at Home

37%No PC at Home

63%

Page 7: Choice modelling in lower income countries

Mobile surveys in most emerging markets are for 16-44

5%

21%24% 23%

17%

10%

16 to 17 18 to 24 25 to 34 35 to 44 45 to 54 55 to 64

On Device Sample Census

Source: n=2060 On Device Profiler 2015

Page 8: Choice modelling in lower income countries

Access to lower social class

0

10

20

30

40

50

60

70

Female Male 18-34 35-44 45+ LSM 1-4 LSM 5-7 LSM 8-10

AMPS 2014 (Census) On Device Sample

Page 9: Choice modelling in lower income countries

Mobile beats face to face alternatives

0.89

0.83

0.94

0.91

0.76

0.8

0.84

0.88

0.92

0.96

Malaysia India

Correlation of tracking data with actual

market share data 1 = Perfect Correlation

Face to Face

Mobile

Page 10: Choice modelling in lower income countries

Robust sample in days n=1260

n = 600

~ 60% 18-25 y/o

80% earn 3000 R or less

n = 38 feature phones

n = 380

~ 50% 18-25 y/o

46% earn Rp 10.000 or less

n = 127 feature phones

n = 280

44% 18 – 25 y/o

48% R. 8999 or less

n = 30 feature phones

Page 11: Choice modelling in lower income countries

So what did we do?Painkillers Study

Page 12: Choice modelling in lower income countries

Predict choice using trade offsOutput are preferences per consumer to be used for predictions

Brand Units per pack Dosage (in mg) Price (local R) Format

Top 3 (combination

large manufacturer &

local)

- Tylenol

- Novalgine

- Anador

3 options:

- 24

tablets/capsules

- 20

- 16

3 dosages:

- 200 mg

- 300 mg

- 500 mg

3 different prices:

- 7.19

- 10.99

- 12.49

2 different formats:

- Tablets

- Capsules

Painkiller ChoiceWhat is the most appealing attribute for consumers?

Page 13: Choice modelling in lower income countries

13 taps on a mobile phone

Choice Tasks

Consumers have completed 7 different

choice tasks, each task varying the

attributes of the product (brand, units,

dosage, price & format)

In each task, respondents chose one

concept that they preferred most

For this study, there were 2 or 3 concepts

shown on screen at a time

Page 14: Choice modelling in lower income countries

Setup Brazil

Additional insights

Understand why concepts are motivating

and other insights

Open ended question:

‘For what purpose consumers

normally buy painkillers?’

Additional options

Select questions for specific sizes or flavors

Additional price analysis

Page 15: Choice modelling in lower income countries

Key findings

Brand is the most importantattribute

7%

13%

15%

19%

47%

Type

Price

Dosage

Pieces

Brand

Page 16: Choice modelling in lower income countries

Brand preference

17%

23%

60%

Novalgina

Anador

Tylenol

Page 17: Choice modelling in lower income countries

Brazilians like it big

13%

25%

62%

10pieces

20pieces

30pieces

19%

26%

56%

100mg

300mg

500mg

Page 18: Choice modelling in lower income countries

Latent Class analytics

• 45% prefer Novalgina (SA),

but could switch to Tylenol as

they give more importance to

other attributes such as

• high dosage and high number

of pieces.

• They are not price sensitive

• Extremely loyal to the Tylenol

brand

• Prefer capsules over tablets

• Motivated by a high number of

pills and mid dosage

• Tylenol lovers are price sensitive

• Very loyal to the Anador brand

• Tablets are preferred over

capsules

• Motivated by a midsize quantity

and high dosage

• Anador lovers are very price

sensitive

Novalgina likers 45% Tylenol lovers 36% Anador price buyers

19%

Page 19: Choice modelling in lower income countries

The most common usesof painkillers

Page 20: Choice modelling in lower income countries

Country nuances

Tablets preferred

Pricesensitive

Package & dosage important drivers

Page 21: Choice modelling in lower income countries

Predictionpower

Page 22: Choice modelling in lower income countries

Prediction

In all countries our models predict significant

better compared to random chance (33%)!

65.8% 70.3% 76.8%

33%

x 2 !

Page 23: Choice modelling in lower income countries

Art or Science

Page 24: Choice modelling in lower income countries

You want to know more?

Mike Mabey

[email protected]

Robert Dossin

[email protected]