DRIVERS OF MARKETING CAREER SUCCESS

Figures & data

Table 1. Success factors for marketers mentioned in interviews with top marketers (““= literal quotes).

Learning & Curiosity	Communication
Understanding consumers “Boundless curiosity” “Passive wisdom/knowledge”	“Talk a lot” “Read your colleagues and the board” “Convince people in your company” Social-emotional intelligence “Need political skills”
Experience	Experimentation
“Experience helps” Different jobs “Must have done groundbreaking stuff”	“Experiment, just try” A/B testing Agility/autonomy/less hierarchy
Capabilities	Independence/determination
Analytics and creativity “Power of intuition” “McKinsey and engineers are too rational” “Gut feel”	Guts, independent minds “Be a bit arrogant” Commitment Strong in execution “Not only plan, do!”
Nature or Nurture	Support
“Need genetic code” “Marketing is an art” “Marketing can be learned” “More nurture than nature”	Mentors or role models (mentioned several times)

Figure 1. Research model.

Table 2. The “Big five” Personality factors (Costa & McCrae, 1992.).

Openness to new experiences (inventive/curious vs. consistent/cautious)

Conscientiousness (efficient/organized vs. easy-going/careless)

Extraversion (outgoing/energetic vs. solitary/reserved)

Agreeableness (friendly/compassionate vs. challenging/detached)

Neuroticism (sensitive/nervous vs. secure/confident)

Table 3. Summary of the questionnaire.

Intro letter

Personal background information (age, gender, study, etc.)

Summary of career, with for each job (up to ten jobs)

− job title

− year of start and end

− tasks/responsibilities

− firm/organization

− nationality of organization

− functional area

− industry

Scales for personality, learning style, and career orientation

Additional questions about the current job (position, company size, annual pay package, etc.) to determine objective career success

Scales for subjective career success

Table 4. Profile of the respondents in our study (n = 146).

Gender	Male/Female	74%/26%
Bachelor	From same school as master’s	71%
Major Specialization
Marketing Management		35%
Strategic Management		47%
Business Information/InnovationManagement		18%
Nationality Dutch		85%
Age (average)		38 years
Years out (average)		11.6 years
Number of different jobs (average):		2.98
Number of years in current job (average)		3.53

Table 5. Results of the multiple regressions.

	Dependent Variable Objective Career Success			Dependent Variable Subjective Career Success
Independent Variables	1 Marketing Jobs N = 52	2 Management Jobs N = 55	3 All Jobs N = 146	4 Marketing Jobs N = 52	5 Management Jobs N = 55	6 All Jobs N = 146
Personality Traits
Openness to new experiences						0.243 (.00)
Conscientiousness
Extraversion	0.368(.01)
Agreeableness
Neuroticism					0.339 (.02)	0.179 (.02)
Learning Styles
Concrete Experience			0.266 (.00)
Reflective Observation				-0.351 (.01)	−0.418 (.01)
Abstract Conceptualization						0.168 (.03)
Active Experimentation
Career Orientation
Protean Career Orientation	0.292 (.04)		0.237 (.00)	0.536 (.00)		0.334 (.00)
Work-Life Balance			−0.217 (.01)
Other Personal Variables
Gender 1=male 0=else
Gender x Work-Life Balance					−0.304 (.04)
Nationality 1=Neth 0=else
Bachelors 1= Same school 0=else		−0.391 (.00)
MajorMKT 1=yes 0=else
MajorSM 1=yes; 0=else
Career development
Steepness Early Career	0.292 (.02)
# Different Organizations	0.342 (.01)
# Different Nationalities			−0.165 (.05)
# Different Domains
# Different Industries		−0.486 (.00)
Total Experience
Mentor 1=yes 0=no
Postgrad Education Univ
Postgrad Education NonUniv		−0.456 (.00)
Control variables
# Years Out		0.950 (.00)	0.336 (.00)
Company Size (# employees)			−0.232 (.00)
Extra for Subj Car Success
Objective Career Success	n.a	n.a	n.a.			0.243 (.00)
R2 -adjusted	0.484	0.656	0.384	0.466	0.376	0.453

Notes: Numbers are standardized (beta) regression coefficients, with significance (p, two-sided) in brackets.

Empty cell: variable not included in the model.

Criteria for variables selection: Pin: 0.10; Pout: 0.15; only variables with p < .05 included in regression.

Table 6. Bivariate correlations.

	Dependent Variable Objective Career Success			Dependent Variable Subjective Career Success
	1 Marketing Jobs N = 52	2 Management Jobs N = 55	3 All Jobs N = 146	4 Marketing Jobs N = 52	5 Management Jobs N = 55	6 All Jobs N = 146
Personality Traits
Openness to new experiences			0.158*	0.385**	0.420**	0.459**
Conscientiousness	−0.292*		−0.161*			0.189**
Extraversion	0.491**		0.199**	0.346*	0.341*	0.308**
Agreeableness
Neuroticism					0.370**	0.358**
Learning styles
Concrete Experience		0.394**	0.404**
Reflective Observation			−0.213**	−0.472**	−0.484**	−0.352**
Abstract Conceptualization				0.373*		0.206*
Active Experimentation
Career orientation variables
Protean Career Orientation	0.461**		0.217**	0.615**	0.282*	0.559**
Work- Life Balance					−0.294*
Other personal variables
Gender 1=Male 0=else					−0.254*
Gender x Work Life Balance				−0.252*	−0.351**
Nationality 1=Neth 0=else
Bachelors 1=Same School 0=else			0.162*
MajorMKT 1=Yes 0=else
MajorSM 1=Yes; 0=else
Career Development
Steepness Early Career		0.420**	0.287**
# Different Organizations	0.451**		0.240**
# Different Nationalities
# Different Domains
# Different Industries
Total Experience	0.355**					0.179*
Mentor 1=Yes 0=No					0.293*	0.159*
Postgrad Education Univ	0.399**		0.163*
Postgrad Education NonUniv		−0.252*
Control variables
# Years out	0.368**	0.621**	0.460**		0.295*
Company Size (# employees)		−0,281*	−0.305**
Extra for Subj Car Success
Objective Career Success	n.a	n.a.	n.a.	0.447**	0.335*	0.340**

Empty cell= no significant correlation.

+=positive correlation; -= negative correlation.

*=p < .05; **=p < .01 (one-tailed)

Table 7. Summary results for Objective Marketing Career Success.

Variables in the model (with beta-coefficient and p-value)
Extraversion	0.368 (.01)
#Different organizations	0.342 (.01)
Protean career orientation	0.292 (.04)
Steepness early career	0.292 (.02)
R2 (adjusted) = .484 n = 52

Table 8. Independent variables appearing in the model for objective career success for all jobs.

Variables in the model for all jobs only (see Table 6, Model 3, with beta- and p- values) n = 146		Bivariate correlations of these variables with objective career success for marketing jobs
Concrete experiences	0.266 (.00)	0.205 (.11)
Work-life balance	−0.217 (.01)	−0.218 (.11)
#Different nationalities	−0.165 (.05)	0.039 (.40)
Years out	0.336 (.00)	0.368 (.01)
Company size	−0.232 (.00)	−0.102 (.25)
R^2 (adjusted) = 0.384 n = 146

Costa, P. T., & McCrae, R. R. (1992). Revised NEO personality inventory (NEO-PI-R) and NEO five-factor inventory (NEO-FFI). Manual. Odessa, FL: Psychological Assessment Resources.

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