Presentation on Mobile Commerce by Nicolas Dinh from MasterCard for the Toronto Product Management Association, March 27th, 2013.

1. Mobile Commerce

2. US Thanksgiving / Black Friday 2012
April 4th, 2012
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3. Cyber Monday 2012
• $1.6B in digital sales –
+30% from 2011 CM
• Mobile – 18% of
consumers visited a
retailer site/app (+70%
YoY). Mobile sales 13%
(+96% YoY)
• iPad Factor – generated
majority of mobile traffic
(7% of total traffic)
Source: IBM
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4. What is Mobile Commerce?
Commerce → eCommerce → mCommerce
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5. What is Mobile Commerce?
Commerce
• Being able to
buy/sell
eCommerce
•Using a computing
device
•Connected to an
online network
mCommerce
•Anytime
•Anywhere
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6. Phases of Commerce Model
Inspiration
End Of Life Investigation
Use Research
Transaction Search
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7. Phases of Commerce Model
Inspiration
End Of Life Investigation
Use Research
Transaction Search
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8. Phases of Commerce Model
Inspiration
• Social overlay:
leveraging
End Of Life Investigation
social media
and networks
that support
social
Social interaction and
Use Research contribution to
drive
commerce
Transaction Search
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9. Changing Face of Commerce
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10. Mobile Commerce: Key Components To
Success
• (Frictionless) Payments
• Product / Service Discovery
• Location
• Personalization
– Identity
– Recommendations and Predictive Analysis
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11. Payments
Make it easy and seamless as possible!
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12. Product Discovery
Product Barcodes
• Generally unique
identifiers for
products, standards based
• QR Codes
– Encode up to 4K
characters
– Can encode with
events, URLs, contacts, tr
iggers, etc.
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13. Product Discovery
NFC
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14. Location Services
• Services / APIs to:
– Product data
(names, prices, desc
riptions, images)
– Merchant location
data (addresses
– Real-time inventory
status
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15. Personalization
Identity
• Develop extensible applications from user history
and historical data
• Leverage purchase history to build trust
• Weave integrated payment system directly into
customer identity
• Leverage to make it easier for your customers to
buy from you
• Socialize the commerce experience
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16. Personalization
Recommendations & Predictive Analysis
Taste, Preference, Interest
Item
How do you leverage substantially amounts of Data
generated from your M-commerce solution to help your
customer?
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17. Tesco Homeplus
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