My must-measure product marketing metrics: Cozi Namer of Pfizer

In our Executive Insights series, we hear from visionary business leaders as they navigate complex data challenges and uncover valuable insight along the way.

In this edition, we hear from Cozi Namer, a marketing leader who has spent his career at the intersection of digital and healthcare. Not only does Cozi share his marketing insights as Adjunct Professor at CUNY, but he also serves as a board member of the Digital Marketing Advisory Board for Baruch College. We struck gold having him offer data and marketing wisdom here.

Name: Cozi Namer
Company: Pfizer
Title: Head of Strategic Initiatives
Previous roles: Head of Commercial & Product Marketing at Verily Life Sciences, an independent subsidiary of Alphabet, Inc.
Industry: Health Information, Health IT, Consumer Health

What are your top 5 most important KPIs for you and your work?

In my work, I’ve found the following metrics to be the most useful and insightful:

• Customer satisfaction metrics such as Net Promoter Score (NPS) or Customer Satisfaction Score (CSAT)
• Product success metrics such as daily active users to monthly active users ratio (DAU/MAU) + Engagement Rates + App Store Ratings
• Customer Pipeline Metrics; Leads (MQL / SQL)
• Commercial Success Metrics: Bookings + Revenue
• Population Health Impact Metrics (customized per condition. A1C Reduction / Weight – BMI / BP / PHQ9)

Why is data integral to what you do?

Product marketing is led by insights and not instincts. Without the data, we build vaporware that’s not helpful. With data, we can course correct and adjust not only what we build but also the story we tell to explain the impact of what we build. Culturally, data is what connects teams across different functions.

What are the biggest data challenges you face on a daily basis?

When it comes to data, I’ve encountered three major challenges. First, silence is a major challenge if there’s not enough data. Noise is another challenge if the data is there, but not helpful. And finally, bias, when data points are handpicked to tell a story.

What advice would you give to your younger self related to data and metrics?

You’re an engineer, you’ve got this. Lean in and be the person in the room who understands what each metric can do for you.