FAQs
What is the minimum qualification required for this role?
The minimum qualification required is a Bachelor's degree or equivalent practical experience.
How much experience is necessary for applicants?
Applicants need to have at least 8 years of experience in digital or offline advertising.
Is experience with Marketing Mix Modeling (MMM) required?
Yes, experience with Marketing Mix Modeling (MMM) is necessary for this position.
What preferred qualifications are sought after for this role?
Preferred qualifications include experience in a consultative capacity within MMM, managing and influencing decision makers, knowledge of ad effectiveness and brand measurement, and understanding of the digital ad ecosystem and recent privacy changes.
Will this position require interaction with customers?
Yes, the role involves excellent customer-facing, consultative, and communication skills to work with advertisers and stakeholders.
What responsibilities does the Marketing Effectiveness Lead have?
Responsibilities include identifying business growth opportunities, developing consultative measurement support strategies, partnering with cross-functional teams, uncovering measurement-related challenges, and driving advancement of high-quality MMMs.
Is there collaboration with third-party measurement partners?
Yes, the role includes leading relationships with critical third-party measurement partners to ensure accurate measurement of Google media.
Is this role focused exclusively on Google products?
While the focus is on Google media, it also involves understanding marketing investments overall and how Google fits into that landscape.
Are there opportunities for product innovation in this role?
Yes, partnering with cross-functional teams to identify opportunities for product innovation is part of the responsibilities.
What is Google’s stance on equal employment opportunity?
Google is proud to be an equal opportunity workplace and is an affirmative action employer, committed to equal employment opportunity regardless of various factors, including race, gender, and disability status.