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Analytics in Action
Case Study on
Paytm
February 2018
S.GAUTAM
R.BHATNAGAR
K.CHELANI
Introduction
©2016 L. SCHLENKER
Structure
Introduction
Business Model
Why Data Science ?
Techniques and Decision Making
Data Science Team
Lessons Learned
• What is the organization’s business
model?
• Why does the organization focus on
data?
• Which data science techniques does
the organization favor ?
• What is the link between data science
and decision making?
• How is the Data Science team
organized?
• How does the organization use Data
Science to propel growth
Case Study Questions
Technology
Reference: https://expandedramblings.com/index.php/paytm-statistics-facts/
• Started in 2010, Founder – Vijay Shekhar
Sharma
• CEO – Renu Satti
• India's Largest mobile commerce
• At Paytm, you have the option of
recharging and shoping from whenever,
anywhere and are equipped with a
secure online wallet called Paytm Cash.
• Revenue: Rs. 813.88 Crore
• Value: Rs. 2,376.6 Crore
• 280 million registered users, 5 million
daily transactions
• SoftBank, SAIF Partners, Alibaba Group,
Ant Financial (Alipay) and Mediatek.
Introduction
Technology
Reference: https://www.feedough.com/paytm-business-model-how-paytm-makes-money/
• Recharge
• Bill Payments
• Marketplace
• Wallet
• Digital Gold
• Paytm Bank
Business Model
Technology
Business Model
Recharge
Bill
Payments
Marketplace
Wallet
Digital Gold
Paytm Bank
Paytm Payment Bank
Technology
Reference: https://analyticsindiamag.com/paytm-unveils-payments-bank-data-science-core
• Fraud Detection: Hadoop
• Advertising
• User behaviour
• Customer acquisition
• Build credit score models
• Reach last mile customers
• Quick summarization, plots and
prototypes
• Text mining, production models and
scalable solutions
Why Data Science ?
Technology
• Predictive Analytics (Future
needs)
• Facebook Analytics (Reactive
marketing)
• Google Analytics (Track and
monitoring)
Techniques and Decision Making
Technology
• Social Media Sites –
Facebook, Twitter, etc.
• Mobile application
consumption pattern
• Users Worldwide
Data Sources
Technology
• Paytm Labs – Toronto
• Head – Harinder Takhar
• 18 Engineers, 5 Machine
learning engineers, 12 system
engineers.
• Labs with Highly Qualified team
with 52% Bachelors, 45% Masters
& 3% Doctorate Degree.
• People from Different countries
speaking 18 languages
• Innovation Lab – Canada
• 50 engineers, developers and
data scientists
Data Science Team
Technology
Lessons learned
Technology
• Data Science is helping Paytm to know
consumer behavior.
• Analytics is helping Paytm to detect frauds
and cope with them.
• Analytics helped them to increase their
product portfolio.
• https://analyticsindiamag.com/paytm-unveils-
payments-bank-data-science-core
• https://expandedramblings.com/index.php/paytm
-statistics-facts/
• https://successstory.com/companies/paytm
• https://www.feedough.com/paytm-business-
model-how-paytm-makes-money/
• https://www.paytmlabs.com/
Bibliography
Next Steps
Paytem

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