Slides for the talk at the International Conference on Predictive APIs and Apps (PAPIs 2014)

1. © Strands Inc. 2014
ANALYSING BANKING DATA TO PROVIDE
RELEVANT OFFERS TO CUSTOMERS
Jim Shur, Chief Architect
Ivan Tarradellas, Product Manager
Marc Torrens, CIO
Enric Plaza, Research Professor

2. © Strands Inc. 2014
• Strands, what do we do?
• Banking Industry: Innovation or Death
• Card-Linked Offers
• Financial Data Analysis

3. © Strands Inc. 2014 3
WHAT DO WE DO?
Strands is a global provider of personalisation and recommendation solutions to innovate in two
sectors: financial institutions and online retailers.
Strands Finance Strands Retail

4. © Strands Inc. 2014 4
“Banks are losing their monopoly on banking.”
– Francisco González, BBVA
THREADS IN BANKING

5. © Strands Inc. 2014 5© Strands Inc. 2014
“We are on the leading edge of a technology revolution
in financial services.”
– Anthony Jenkins, Barclays CEO
LEADER’S VIEWS

6. © Strands Inc. 2014 6
“They all want to eat our lunch.”
– Jamie Dimon, JP Morgan Chase CEO
LEADER’S VIEWS

7. © Strands Inc. 2014 7
“(…) the good news is that we still have one significant advantage, which is
the vast array of financial and non-financial data that we accumulate.”
Francisco González, BBVA CEO
THE OPPORTUNITY

8. © Strands Inc. 2014 8
Banks are faced with a great opportunity to move from being a mere
provider of financial services to become a provider of solutions.
A NEW ROLE FOR BANKS

9. © Strands Inc. 2014 9
TECHNOLOGY VISION
Transforming Data into Knowledge to produce
Actionable Insights for innovative Financial Software
Transactional Data
BIG DATA MACHINE LEARNING USER EXPERIENCE
Knowledge Actionable Insights
> >

10. © Strands Inc. 2014 10
HELP!
CARD-LINKED OFFERS

11. © Strands Inc. 2014 10
HELP!
CLO
How do I find the
most relevant
offers?
How can I attract
new customers?
Is
How well do I know
my customers?
CARD-LINKED OFFERS

12. © Strands Inc. 2014 11
Strands CLO is a marketing tool that enables retailers to target highly relevant
deals to card-holders through digital banking channels
UNLEASH THE VALUE OF CUSTOMER DATA

13. © Strands Inc. 2014 12
CARD-HOLDER’S PERSPECTIVE
Accept Offer in
Digital Banking
Buy at Merchant Pay with Bank Card Get Cash Back in
Your Account
HOW IT WORKS

14. © Strands Inc. 2014 12
CARD-HOLDER’S PERSPECTIVE
Accept Offer in
Digital Banking
Buy at Merchant Pay with Bank Card Get Cash Back in
Your Account
RETAILER’S PERSPECTIVE
Get Charged from
Bank
Upload Offer in
Digital Banking
Monitor Offer
Campaign
Sell
HOW IT WORKS

15. © Strands Inc. 2014 13
Hi, my name is Mario
and I like wearing
trendy clothes
Hi, my name is Sarah
and have a shop
selling trendy shoes
VIDEO

16. © Strands Inc. 2014 14
THE PROBLEM
Maximise the overall Performance for all offers
I want RELEVANT offers I have MARKETING strategies

17. © Strands Inc. 2014 15
THE PROBLEM
Maximise
I want I have MARKETING strategies

18. © Strands Inc. 2014 16© Strands Inc. 2014
RETAILER VIEW

19. © Strands Inc. 2014 17
CAMPAIGN AUDIENCE FILTERS
• A CAMPAIGN is defined by an OFFER and an AUDIENCE
• An AUDIENCE defines a group of consumers by a set of filters:
• Demographic filters (e.g. 20-30 years, married, in Barcelona)
• Behavioural filters
• Behavioural filters are based on Commercial Interests
• Loyalty: how loyal is the customer to the merchant (loyal, shared, competitor)
• Frequency: how frequent is the customer buying to the merchant (low, med, high)
• Purchase Segmentation: the buying segment of the customer (low, med, high)
• Location: where is the customer buying (in, out)

20. © Strands Inc. 2014 18
MARKETING STRATEGIES

21. © Strands Inc. 2014 19
MARKETING STRATEGIES

22. © Strands Inc. 2014 20
MARKETING STRATEGIES
SMART MARKETING STRATEGIES are an easy way to build audiences for different marketing
goals, so merchants do not need to be expert marketeers and use complex filtering:
Win New Customers
Reward Loyal Customers
Increase Frequency
Increase Loyalty
Increase Spending
…
SMART
MARKETING
STRATEGIES
MERCHANTS
SELECT STRATEGY
Increase Loyalty
Win New Customers
REFINE (OPTIONAL) TARGETED AUDIENCE

23. © Strands Inc. 2014 21
THE PROBLEM
Maximise
I want RELEVANT offers I have

24. © Strands Inc. 2014 22© Strands Inc. 2014
CARD-HOLDER VIEW

25. © Strands Inc. 2014 23
USER CENTERED CAMPAIGN SALIENCE
• The degree of interest of a campaign to a specific user:
• Likelihood of buying in the category of the campaign
• Proximity of the user to the merchant of the campaign
• Activity of the user with the merchant that is making the campaign
• Loyalty of the user to the merchant of the campaign
• Merchant Fitness of the user considering the median of the merchant’s selling prices
Likelihood (LK)
Proximity (PX)
Activity (ACT)
Loyalty (LY)
Merchant Fitness (MF)

26. © Strands Inc. 2014 24
MONTH TO PREDICT
LAST YEAR
2 YEARS OF DATA
Jan Feb Mar Apr May Jun Aug Sep Oct Nov DecJul
Jan Feb Mar Apr May Jun Aug Sep Oct Nov DecJul
Jan Feb Mar Apr May Jun Aug Sep Oct Nov DecJul
h✓(x)
Training Set
Hypothesis
Supervised Learning
Seasonality (12 Months) Customers (Millions) Categories (Hundreds)
LIKELIHOOD OF BUYING IN A CATEGORY

27. © Strands Inc. 2014 25
…tree1 tree2 treen
k1 k2 kn
voting
k
12 Months Month Transactions Month Amount
LIKELIHOOD OF BUYING IN A CATEGORY

28. © Strands Inc. 2014 26
THE PROBLEM
Maximise the overall Performance for all offers
I want RELEVANT offers I have MARKETING strategies

29. © Strands Inc. 2014 27
AR = campaign accomplishment ratio
USER-CENTRED CAMPAIGN SALIENCE indicates the relevance of that campaign for the customer.
combination of
behavioural features +
demographics
TR = time ratio gone for a campaign
%
CAMPAIGN SALIENCE indicates the priority of a campaign for the system.
OVERALL SALIENCE

30. © Strands Inc. 2014
Comprehensive and interconnected set of solutions
to leverage the value of customer data.
28
THANK YOU!