Slides from my presentation in Belem, Lisbon, Portugal (Feb 18, 2016) http://bit.ly/1o1qguD

1. Enabling Personal and Relevant Engagement
ShiSh
Worldwide Director, Analytics & IoT, Retail Sector, Microsoft Corp
Machine Learning & Retail

2. What product is Joe
most likely to buy?

3. Will Sarah come
back to shop with
us next month?

4. What advertising would
be most effective to get
Johan’s attention?

5. Listening to the voice of the customer
0
5
10
15
20
25
30
1995 1996 1997 1998 1999 2000 2001 2002
Sales Forecast in 1999
Film Cameras Digital Cameras
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5
10
15
20
1995 1996 1997 1998 1999 2000 2001 2002
What Really Happened
Film Cameras Digital Cameras

6. Retail has a multitude of
devices that generate
petabytes of potential
insights
Monitoring and mining
social media data enables
retailers to enhance
customer insights
Open data sources and
internal sources enable
retailers to better
understand customers
Democratization of data

7. Cortana Analytics
Information
Management
Big Data Stores Machine
Learning &
Analytics
Visualization
Democratization of Tools

10. Put customers first with
technology that learns,
predicts, and engages at a
personal level
» Predict what customers want before they tell you
» Engage with customers at the right time, right place
with the right offers
» Personalize the customer experience across channels
» Improve loyalty, "share of wallet" through
hyper-local assortments and inventory

11. Foodservice retailer built brand loyalty with a
cloud-based mobile app
Challenge
• Improve relationships
with customers.
• Build upon a successful
brand app to reach
more customers.
• Generate upsales and
cross-sales.
Strategy
• Added an analysis and
insights system based
on Microsoft Azure.
• Gathered data on
customers’ behaviors
and preferences
through their app use.
Results
• Expanded app use to millions of
customers in five countries.
• Enabled personal, relevant,
contextual content that adds
value for the users.
• Improved customer loyalty.

12. Demo

15. Sales for Northwest
Territory retailer
Problem: Seattle is
not selling to
forecast
1
2

16. When we drill
down to
Seattle, we
can see a
problem in
soft drinks
Click and see
further details of
Seattle sales
1
2

17. Sales driver analysis
– build a model that explains what
drives sales
Sales delta analysis
– use the model to see problems
3. How can we fix sales?
– apply the model to fix the problems
21 3

18. 25.6% variations
explained
Internal transaction
and marketing data
include variables as:
- Stock Up
- Price Elasticity
- Radio Advertising
- TV Advertising
- SKU presence
Transaction dataset
in AML experiment
1
2
3

19. Variations explained
improves to near
50%
External weather,
demographic, and
competitor data
include variables as:
- Temperature
- Precipitation
- Household size
- Annual Income
- Competitor Price
Gap
Transaction dataset
in AML experiment
External dataset
enters the model
in AML experiment
2
1
3
4

20. IoT dataset enters
the model in AML
experiment
Variations explained
improves to 89%
New IoT, research and
online activity data
include variables as:
- Survey research
- Web traffic
- Social media
traffic
- Mobile traffic
- Store traffic
- Shelf traffic
Transaction dataset
in AML experiment
External dataset
enters the model
in AML experiment
2
4
1
3
5

21. Monthly ∆ by sales
driver
Let’s first zero in on
the sales impact of
price gaps, as they
are the biggest
problem
Competitor price
gap caused 7,598
less units sold than
previous month
Click one of the
controllable variables
to see what would
happen if we take
some actions
21
3
4

22. See the impact on
physical sales if
we reduce the
price gap by
different levels
See the impact on
profit if we reduce
the price gap by
different levels.
When it is
reduced by 15%,
we would be able
to achieve 4.5K
incremental profit.
Select
competitor
price gap as it
is a controllable
variable
It would be
recommended to
decrease the
competitor price
gap
2
1
3
4

23. See the impact on
physical sales if we
increase social
media engagement
by different levels
See the impact on
profit if we increase
social media
engagement by
different levels.
When it is
increased by 20%,
we would be able
to achieve 12.6K
incremental profit.
Select Social Media
Engagement as it is
a controllable
variable
It would be
recommended to
increase social
media engagement
2
1
3
4

24. See the impact on
physical sales if we
increase
advertising by
different levels
See the impact on
profit if we increase
advertising by
different levels.
When it is
increased by 20%,
we would be able
to achieve 7.1K
incremental profit.
Select Own Brand
Advertising as it is a
controllable variable
It would be
recommended to
increase our own
brand advertising
2
1
3
4

25. 25
IoT Driving Insights,
Decisions &
Engagement
IoT in retail could have an economic
impact of $410 billion to $1.2 trillion per
year in 2025

26. 26