This document discusses social desirability effects in market research and how digital and social data can provide additional predictive value compared to traditional surveys. It presents two case studies that show digital behaviors are better predictors of purchase outcomes for younger audiences in movie box office sales and automotive sales compared to surveys, which may be impacted by social desirability bias. The conclusions suggest digital and social data provide more predictive insights for brands and situations where self-monitoring of responses is likely due to social norms.

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SOCIAL DESIRABILITY EFFECTS
IN MARKET RESEARCH
EFFECTIVENESS
9.19.2016

2. MEET
THE TEAM
A BIT OF
CONTEXT
THE PREDICTIVE
VALUE OF
SOCIAL
CASE
STUDIES
CONCLUSIONS
AND NEXT
STEPS

3. MEET
THE TEAM

4. MEET THE TEAM
KELLEY STERNHAGEN
Director, Analytics W2O Group
SETH DUNCAN
Chief Analytics Officer, W2O Group

5. A BIT OF
CONTEXT

6. THE ALLURE OF DIGITAL AND SOCIAL DATA

7. ADDRESSING THE REPRESENTATIVENESS OF SOCIAL MEDIA
While social is not
representative of
the population, the
population is
represented on
social
of people in
developed markets
have active accounts
on their country’s most
popular social
platform (We Are
Social)
of Americans 65+
report using social
media on a regular
basis
Social media
provides insight into
younger audiences,
which have been
more difficult to
understand in the past

8. ADDRESSING THE REPRESENTATIVENESS OF SOCIAL MEDIA
While social is not
representative of
the population, the
population is
represented on
social
of people in
developed markets
have active accounts
on their country’s most
popular social
platform (We Are
Social)
of Americans 65+
report using social
media on a regular
basis
Social media
provides insight into
younger audiences,
which have been
more difficult to
understand in the past

9. ADDRESSING THE REPRESENTATIVENESS OF SOCIAL MEDIA
While social is not
representative of
the population, the
population is
represented on
social
of people in
developed markets
have active accounts
on their country’s most
popular social
platform (We Are
Social)
of Americans 65+
report using social
media on a regular
basis
Social media
provides insight into
younger audiences,
which have been
more difficult to
understand in the past

10. ADDRESSING THE REPRESENTATIVENESS OF SOCIAL MEDIA
While social is not
representative of
the population, the
population is
represented on
social
of people in
developed markets
have active accounts
on their country’s most
popular social
platform (We Are
Social)
of Americans 65+
report using social
media on a regular
basis
Social media
provides insight into
younger audiences,
which have been
more difficult to
understand in the past

11. ADDRESSING THE REPRESENTATIVENESS OF SOCIAL MEDIA
While social is not
representative of
the population, the
population is
represented on
social
of people in
developed markets
have active accounts
on their country’s most
popular social
platform (We Are
Social)
of Americans 65+
report using social
media on a regular
basis
Social media
provides insight into
younger audiences,
which have been
more difficult to
understand in the past

12. PEOPLE POST A RANGE OF POSITIVE & NEGATIVE EXPERIENCES ONLINE

13. SOCIAL MEASUREMENT CAN LACK ACTIONABILITY FOR MARKETERS

14. ONLY A SMALL NUMBER OF PEOPLE POST CONTENT ONLINE
1% CREATE
CONTENT
9% SHARE AND
REPACKAGE
90% LISTEN
AND LEARN

15. ONLY A SMALL NUMBER OF PEOPLE POST CONTENT ONLINE
1% CREATE
CONTENT
9% SHARE AND
REPACKAGE
90% LISTEN
AND LEARN

16. ONLY A SMALL NUMBER OF PEOPLE POST CONTENT ONLINE
1% CREATE
CONTENT
9% SHARE AND
REPACKAGE
90% LISTEN
AND LEARN

17. ONLY A SMALL NUMBER OF PEOPLE POST CONTENT ONLINE
1% CREATE
CONTENT
9% SHARE AND
REPACKAGE
90% LISTEN
AND LEARN

18. LEVERAGING DIGITAL BEHAVIORAL TRACES IN ADDITION TO CONVERSATION

19. LEVERAGING DIGITAL BEHAVIORAL TRACES IN ADDITION TO CONVERSATION

20. LEVERAGING DIGITAL BEHAVIORAL TRACES IN ADDITION TO CONVERSATION

21. THE PREDICTIVE
VALUE OF
SOCIAL

22. SOCIAL AND DIGITAL DATA IS SOMEWHAT PREDICTIVE OF…

23. SOCIAL AND DIGITAL DATA IS SOMEWHAT PREDICTIVE OF…
BOX OFFICE RECEIPTS
(Asur & Huberman, 2010;
Noseworthy, 2013; Panaligan
& Chen, 2013)

24. SOCIAL AND DIGITAL DATA IS SOMEWHAT PREDICTIVE OF…
ELECTORAL OUTCOMES
(DiGrazia et. al., 2013; Maldonado
& Sierra, 2016; O’Connor et. al.,
2010; Tumasjan et. al., 2010)

25. SOCIAL AND DIGITAL DATA IS SOMEWHAT PREDICTIVE OF…
INFLUENZA OUTBREAKS
(Ginsberg & Mohebbi, 2009)

26. SOCIAL AND DIGITAL DATA IS SOMEWHAT PREDICTIVE OF…
ECONOMIC INDICES
(Choi & Varian, 2012)

27. SOCIAL DESIRABILITY MEANS DIGITAL AND SOCIAL DATA MAY
PROVIDE ADDITIONAL VALUE FOR YOUNGER AUDIENCES

28. SOCIAL DESIRABILITY MEANS DIGITAL AND SOCIAL DATA MAY
PROVIDE ADDITIONAL VALUE FOR YOUNGER AUDIENCES
Young & McCoy, 2015

29. SOCIAL DESIRABILITY MEANS DIGITAL AND SOCIAL DATA MAY
PROVIDE ADDITIONAL VALUE FOR YOUNGER AUDIENCES
Pearson, Henryks & Jones, 2011
Young & McCoy, 2015

30. SOCIAL DESIRABILITY MEANS DIGITAL AND SOCIAL DATA MAY
PROVIDE ADDITIONAL VALUE FOR YOUNGER AUDIENCES
Pearson, Henryks & Jones, 2011
Reifman, Klein & Murphy, 1989
Visser & Krosnick, 1998
Tesch, 1983
Young & McCoy, 2015

31. CASE
STUDIES

32. CASE STUDY #1: AGE EFFECTS IN
PREDICTIONS FOR BOX OFFICE SALES

33. ABOUT THE STUDY

34. ABOUT THE STUDY
GOALS

35. ABOUT THE STUDY
SAMPLE

36. ABOUT THE STUDY
INDEPENDENT
VARIABLES

37. ABOUT THE STUDY
DEPENDENT
VARIABLES

38. ABOUT THE STUDY
ANALYSIS
TECHNIQUES

39. PREDICTIVE VALUE OF SOCIAL AND DIGITAL METRICS ACROSS
MOVIE-GOING AGE BANDS
Digital is a better predictor of purchase behavior among those 18-44
39%
28% 28%
35%
54%
37%
55%
49%
41%
19%
13 - 17 18 - 24 25 - 34 35 - 44 45 - 54
Digital Metrics
Non-Digital Metrics
PREDICTIVE(R2)CONTRIBUTION

40. CASE STUDY #2: AGE EFFECTS IN
PREDICTIONS FOR AUTOMOTIVE SALES

41. ABOUT THE STUDY

42. ABOUT THE STUDY
GOALS

43. ABOUT THE STUDY
SAMPLE

44. ABOUT THE STUDY
INDEPENDENT
VARIABLES

45. ABOUT THE STUDY
DEPENDENT
VARIABLES

46. ABOUT THE STUDY
ANALYSIS
TECHNIQUES

47. PREDICTIVE VALUES FOR HIGH PRICE AUTOMOBILES
Lower predictive value for intent to purchase among younger
audiences suggests aspirational responses
27% 24% 25%
38% 36%
10% 13% 14%
14% 15%14% 12%
13%
15% 15%
18 - 24 25 - 34 35 - 44 45 - 54 55 - 64
Behavioral Metrics
Survey (Intent)
PREDICTIVE(R2)CONTRIBUTION
Conversational Metrics

48. PREDICTIVE VALUES FOR MID-PRICED AUTOMOBILES
12%
18% 22% 19% 19%
30%
32%
30%
30% 31%
52%
45% 43% 45% 45%
18 - 24 25 - 34 35 - 44 45 - 54 55 - 64
Survey (Intent)
PREDICTIVE(R2)CONTRIBUTION
Digital and social signals far exceed prediction values for self-reported intent
Behavioral Metrics
Conversational Metrics

49. PREDICTIVE VALUES FOR LOW-PRICED AUTOMOBILES
Results suggest those with more financial flexibility could be exhibiting
self-monitoring around intent to make fiscally responsible choice
37% 31% 26% 26% 26%
51% 65% 71% 71% 70%
18 - 24 25 - 34 35 - 44 45 - 54 55 - 64
Digital & Social Metrics
Survey (Intent)
PREDICTIVE(R2)CONTRIBUTION

50. CONCLUSIONS
AND NEXT
STEPS

51. SITUATIONS WHERE SELF-
MONITORING IS LIKELY
BRANDS THAT FALL INTO
LOWER PRICE TIERS
SITUATIONS WHERE DIGITAL AND SOCIAL CAN ADD ADDITIONAL
PREDICTIVE VALUE

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