What will you get by sorting Retail chain clients into clusters (segments)? Client behaviour analisys and future purchase prediction.

1. Big Data, Big Insights
Supermarket Case
Receipt Receipt Receipt Receipt Receipt Receipt
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2. Thousands of receipt are printed every day
in each supermarket store
Receipt Receipt
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3. Supermarket got tons of data from different
cards and systems.
LOYALTY CARD COUPON CARD CREDIT CARD
1
1
0
1
0
1
0
1
0
0
1
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4. Before store used massive discount program
to bring client in, do upsell and earn money.
20% OFF
ON SALE
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5. But now many stores begin to use
BIG DATA
to gain more customer insights and increase profit

6. A Simple Use Case
Customer Segmentation
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7. Cluster Clients Proportion (%)
1 31233 63.3
2 10807 21.9
3 3027 6.2
4 1691 3.4
5 730 1.5
6 662 1.4
7 650 1.3
8 504 1
All clients are segmented into 8 clusters
according to their purchase behavior
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8. It shows the high possibility of purchase
products in each clusters.
Cluster 3
3027
06 Dietary fats, mayonnaise, eggs 100%
0607 Eggs 100%
060702 Piece (trays) 100%
20 Bakery and confectionery 96.2%
16 Milk and milk products 93.9%
14 Meat and meat products 93.4%
50 Household appliances for the home 93.2%
18 Fresh vegetables, fruits, mushrooms 91.4%
5005 Bags 88.6%
2002 Products made by supermarket 88%
1802 Fresh vegetables 86.3%
01 Grocery 85.5%
31 Personal hygiene 85.5%
02 Canned Goods 84.2%
12 Soft Drinks 81.8%
03 Packed candy 80.8% 100
100
100
96.2
93.89
93.36
93.23
91.38
88.64
87.97
86.26
85.53
85.46
84.24
81.76
80.84
6 607 60702 20 16 14 50 18 5005 2002 1802 1 31 2 12 3
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9. Now they know
who are in which segment
and
which products they more
perfer to buy!

10. Effective promotion plan can be
easily made with high purchase
rate product for targe segment.
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