mining customer loyalty card programs

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Porto – Portugal View of Porto riverside

The School of Engineering

João Falcão e Cunha [email protected]

+351-91-254 1104

Ana Camanho [email protected]

Vera Miguéis [email protected]

A service system is a configuration of technology and organizational networks designed to deliver services that satisfy

the needs, wants, or aspirations of customers.

Firms, as service systems, need, want and aspire to survive, prosper, grow (sometimes also making profits ),

relying on customers for that.

How can we use SSME Research in order to help the firm and its

customers?

We are still in the way of finding the answers…and also the right questions!

This work proposes a new method for promotions design, informed by product associations observed in homogeneous

groups of customers.

The method is based on clustering techniques to segment customers, and decision trees to characterize the segments

profile.

This analysis is followed by the identification of the products usually purchased together by customers from each segment.

This enables regular customization of promotions to specific groups of customers, having in mind improved satisfaction of their

needs, wants, and aspirations.

Conclusion Case Study Methodology Literature Mo5va5on Contents

•  Research motivation •  Literature review

–  Segmentation –  Market basket analysis

•  Methodology •  Case study

–  Contextual setting –  Data –  Segmentation results –  Market basket analysis results –  Customer centered strategies

•  Conclusions and future research

13 Contents


•  Evolution of marketing efforts in retailing companies

14 Contents Mo5va5on

Few concerns about consumers

Need to keep customers

Lifestyle changes

Customer centered strategies

Competitors proliferation

Need to satisfy customer needs

Product centered strategies Tim

e

Conclusion Case Study Methodology Literature Mo5va5on Contents 15 Contents Mo5va5on Literature

Conclusion Case Study Methodology Literature Mo5va5on Contents 16

[Ngai et al (2009)]

Contents Mo5va5on Literature

Clustering

Forecasting

Regression

Classification

Association

Visualization

Sequence Discovery

Conclusion Case Study Methodology Literature Mo5va5on Contents 17 Contents Mo5va5on

•  Market segmentation [Smith (1956)] –  Segmentation criteria:

•  Geographic (initially) •  Demographic •  Volume of sales •  Perceived value for customers •  Lifestyle •  Psycographic •  Customer behaviour – inferred from transaction records available in large

databases, or surveys [e.g. Kiang et al. (2006), Min and Han(2005), Helsen and Green (1991), Liu and Shih(2005)]

–  In particular: Recency (date of the last purchase), Frequency and Monetary (“RFM” model, [Bult and Wansbeek (1995)])

–  Techniques for segmenting customers: Data mining clustering

Literature


•  Market Basket Analysis –  Applied to large databases (transactional) –  Application domains:

•  Banking [e.g. Peacock (1998)]

•  Telecommunication [e.g. Klenettinen (1999)]

•  Web analysis [e.g. Tan and Kumar (2002)]

•  Retailing [e.g. Chen et al. (2004)]

–  Objectives: •  Cross-sales [e.g. Poel et al. (2004)]

•  Product assortment [e.g. Brijs et al. (2004)]

Literature

Conclusion Case Study Methodology Literature Mo5va5on Contents 19 Contents Mo5va5on Methodology

Customers segmentation

Characterization of customers’ profile

Market basket analysis (*)

Design of customized promotions

K-means algorithm

Decision tree

Apriori algorithm

Literature

Improvement of service levels

(Agrawal and Srikant, 1994)

(*) market basket analysis within segments is very rare in the literature

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14th February: Valentine’s Day ...

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•  Chain of hypermarkets, supermarkets and small supermarkets; •  Two loyalty cards: approximately 80% of the purchases are done using

such cards. •  Two ways of segmentation:

–  “Frequency and Monetary value” segmentation; –  Lifestyle segmentation;

•  Customer segments are not used to differentiate customers in strategic policies to promote loyalty:

–  Discounts for specific products advertised in the store shelves and leaflets, that are applicable to all customer with a loyalty card;

–  Discounts on purchases done on selected days (percentual discount or absolute discount on total value of purchases). These are applicable to customers that present at the cash-point the discount coupon sent by mail;

–  Discounts for specific products on selected days.

Case Study Methodology Literature


•  Data available: –  Transactions for the last trimester of 2009 –  Demographic information for each customer: residence postcode, city,

date of birth, gender, number of persons in the household

•  Data analysed: –  Customers whose average amount of money spent per purchase was

up to 500€ –  Customers whose average number of purchases per month is up to the

mean plus three standard deviations (11.7 visits per month) »  2.142.439 customers »  16.341.068 shopping baskets



0.522 0.524 0.526 0.528

0.53 0.532 0.534 0.536 0.538 0.54

-1 1 3 5 7 9 11

DB

inde

x

Number of clusters (k)

Davies Bouldin

0

0.2

0.4

0.6

0.8

1

1.2

0 2 4 6 8 10 12

Sum

OfS

quar

es/k

Number of clusters (k)

Elbow Curve

23 Contents Mo5va5on

•  Segmentation variables: –  Average number of purchases made per month –  Average amount of money spent per purchase

•  5 clusters defined according to DB index and elbow curve



#Customers (%)

37%

27%

20%

8%

8%



•  Clusters’ profile:

Avg.# purchases per month

Avg. Amount money spent per purchase

Avg.# purchases per month

≤3.2 >3.2 >6.2

≤1.5 >1.5

≤135.9 >135.9


Conclusion Case Study Methodology Literature Mo5va5on Contents 26 Contents Mo5va5on Case Study Methodology Literature

Conclusion Case Study Methodology Literature Mo5va5on Contents 27

•  Transactions were aggregated by customer •  The products were aggregated by subcategory

–  Examples of rules obtained:

Antecedent Consequent

Hair Conditioner Shampoo

Tomatoes Vegetables for salad

Sliced ham Flemish cheese

Cabbage Vegetables for soup Pears Apples

Cluster 4

Case Study Methodology Literature Contents Mo5va5on


•  Customer development: –  The company may issue a discount voucher at the PoS that

advertises a consequent product of the association rule, which was not recently bought by the customer who bought the corresponding antecedent product.

•  Examples: –  In Cluster 4:

»  Discount shampoo to customers that have bought conditioner but did not buy shampoo.

»  Discount vegetables for salad to customers that have bought tomatoes but did not buy vegetables for salad.

28 Contents Mo5va5on Case Study Methodology Literature

This work proposes a new method for promotions design, informed by product associations observed in homogeneous

groups of customers.

The method is based on clustering techniques to segment customers, and decision trees to characterize the segments

profile.

This analysis is followed by the identification of the products usually purchased together by customers from each segment.

This enables regular customization of promotions to specific groups of customers, aiming at improved satisfaction of their

needs, wants, and aspirations.

Conclusion Case Study Methodology Literature Mo5va5on Contents 30 Conclusion

•  Data mining allows to find natural clusters of clients on large retailing databases, by means of customer behaviour segmentation.

•  Decision trees enable discovering the rules characterizing customer segments.

•  Market basket analysis within segments seems to show good potential to support the design of customized promotions and consequently the provision of better service to customers.

•  In the future, we intend to interview panel customers belonging to each cluster, in order to see if they consider that the service levels are improving or can be improved.

•  We also intend to monitor the evolution of the results of the satisfaction surveys.

Contents Mo5va5on Case Study Methodology Literature

Conclusion Case Study Methodology Literature Mo5va5on Contents 31 Conclusion

•  What are the adequate promotions to improve service levels?

•  Are derived association rules more relevant than creativity to design promotions?

•  What “level” of segmentation should be used? No segmentation? The one proposed here? Individual segmentation?

•  How important is it to listen to customers, in each segment, and individually?

•  …?

Contents Mo5va5on Case Study Methodology Literature

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mining customer loyalty card programs

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