Main takeaways: - How to transition from a business analyst/consulting role into a PM role - Internalizing data-informed product decision making - How data interpretation and metrics change over the product life cycle

1. www.productschool.com
Leverage Data for Product Decisions
by Google Prod. S&O Lead

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6. Leverage Data for
Product Decisions

7. Hello, I am Sunny Mehrotra
Working with Google Pay helping enable
financial inclusion for next billion users in
India and Globally

8. Agenda:
- Role of Data in life of a PM
- PMs approach to data at different stages of Product Life Cycle
- Live Case Study

9. “Data is the new oil”
“In God we trust, all others please bring Data”
“You can have data without information, butyou cannot have information without data”
“If we have data, let’s look at data. If all we have are opinions, let’s go
with mine.”

10. Role of Data in life of a PM
- Common misconception:
“I am the CEO of the product”
- Empower the entire team to take
decisions
- Aligning every team member on
North Star Metrics, KPIs and
Data transparency
- Data is people, not numbers

11. Data Vocab that every PM should resonate with
● Product Market Fit
● North Star Metric, Counter Metrics
● Funnel Analysis
● Cohort Analysis
● Segmentation Analysis
● Experimentation
● Conversion
● Engagement
● Retention
● Causation vs Correlation
● Qualitative Data
● Analytics Roadmap - Every PM should have one

12. Case Study
ABC E-Commerce Company
ABC E-Commerce company
believes there is a market gap in
supply and demand for office and
casual apparels catering to
oversized individuals. Idea is
validated and you are hired as the
head PM to build an E-com
experience

13. Product Lifecycle:
Early Stage
- Qualitative UXR Studies
- Only think of Core Experience
And build out a MVP
- Set up Objectives and Key results
before you enter next phase
- Set up event, action tracking
- Validate Product Market Fit through
NPS, Retention and Cohort analysis
- Track broad user journey, reach out
to users, read play store reviews
“UXR Studies suggests that user’s
biggest complain is to find the
right size of apparels”
“Competition Analysis suggest
that there are higher than
average returns than other
products, not a viable business”
Qualitative:
Quantitative:
Experiment:
Domain Expert

14. Product Lifecycle:
Growth Stage
- Higher a Product analyst and Invest
in Analytics tools
- Positioning and GTM strategy to
unlock growth
- Invest in Demand Channels and
track channel performance
- Experimentation for maximum
features
- Keep tracking growth metrics - set
up a dashboard TV in office
- Build out your analytics roadmap
“Built an experience to try and
buy offline at door step”
“It will save on delta logistics
cost. It will help user save on
time with back and forth on buy
and returns”
Qualitative:
Quantitative:
Experiment:
Growth Hacker

15. Product Lifecycle:
Mature Stage
- Experimentation should be used as
much as possible
- Doubleclick on Retention Metrics
- Build Inhouse analytics tools to save
on cost and flexibility
- Identify growth opportunities
through mature segmentation
analysis and funnel analysis
- Focus on Customer loyalty and
delight
“Solve for more use cases of
oversized consumer”
“Partners with organizations
chasing the same cohort”
“Do more with less”
Qualitative:
Quantitative:
Experiment:
Retention Expert

16. Parting Thoughts:
Don’t Be Data Driven , Be Data Informed
1
Get to know your Data Org
Structure
How to Start your Data Driven PM Journey:
2
Get comfortable with your
existing data tools
3
At the least, get SQL
trained
4 Get on top of your KPI 5
Test out data tracking
before a product launch
6 Then, Question Everything

17. www.productschool.com
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