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Deep dive into data insights
Jacques Farcy – COO dunnhumby Canada
GIC Toronto – 30th September 2014

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dunnhumby is a global customer science company
600 million
customers
$300billion
retail spend

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we were leveraging Data before it went Big
Our vital data statistics

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what is Big Data about ?
Big Data is like teenage sex :
Everyone talks about it,
nobody really knows how to do it,
everyone thinks everyone else is doing it,
so everyone claims they are doing it…
(Dan Ariely)

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we are 25 years old, we are not teenagers anymore
Customer view
of retail data
+ other data
(structured or
unstructured)
enables
Improved
Customer
Understanding
Better Business
Decisions
Loyalty /
Brand Value
driving to grow…
Generates more and better data

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early adopters are incredibly valuable
Combining different sources of data
(behavioral, declarative, product, calendars, promotional
data) and different statistical predictive models we can
precisely identify the Early Adopter attitude
Case Study
Because they are massively engaged in the promotional
activity, displaying innovation on the flyer is key
(although it does not deliver a lot of sales)
Up to 3 times more likely to be Loyals
Account for around 20% of the Loyal customer base
Are spending 50% more than the average loyals because
they buy more units per trip and visit us more frequently

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personalization and relevancy pay out
context
insight
• Our Brand partner is a market leader in the Oral Care Category with 35% category share.
• In a falling category : less baskets and customers (almost 4% each) buying less
frequently and at lower price (LFL).
• All Oral Care segments are extremely promotionally driven, (50%+ sales in TPR)
• Customers are cherry pickers from one promo to the other, from one brand to the other
• We have identified 36 363 customers who were scored as receptive to the Brand, though being
promotionally driven
• We sent them a specific mailer with loyalty points offers and advise to help them take benefit of the
Brand in all segments of the category
action
-4.2%
results
• Brand spent per targeted
customer +306%.
• Category sales +2%
Case Study

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the future of Big Data, better insights?
Agent Base Modelling
example

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…health concerns froze?”
…health concerns increased?”
…our current diet proposition Brand
were considered unhealthy?”
… the current healthy segment was
progressively considered as unhealthy
“What if…
to explore…
Built on 1st
party data…
…and a deep
understanding
of shopper
behavior
ABM on the
category
we used AGENT BASED MODELLING to help a Brand Partner understand the
impact of health concerns on their Brands for long term future & for the
categories and segment they currently operate in
Case Study
trend impact prediction, thanks to ABM
Q
-30%
+6%
The simulation identified Brand B
as being particularly vulnerable
to a change in perception compared to Brand A A
B

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when it comes to customer intimacy, we all want
to avoid confusions

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when it comes to customer intimacy, we all want
to avoid confusions

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big advice 1 : pick the right lens to organize your
data in a meaningful way

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Crude Oil Bitumen,
Asphalt
Oils
Diesel
Kerosene
Petrol
Clean Data
Organized and
connected data
Filtered data and
summaries
Derived data,
semantic attributes
and segmentation
Business DNA,
metrics, trend
big advice 1 : pick the right lens to organize your
data in a meaningful way

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big advice 1 : pick the right lens to
organize your data in a meaningful way
Cereals
Kellogg’s
Mini-
Wheats
Breakfast
Grocery
The usual way The customer lens
Kids
Case Study

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big advice 2 : fight against the weakest link
insights are only good if you’re up for change
Tools Tricks
Teams
make the right
call on
technology to
support
Internal open source
mindset is requested
Lead your team to fight against inertia

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Big Advice 2 : fight against the weakest link
Biscuits 200g
£200k/week
Products
Customer Loyalty to
the product
Substitutability
Sales
Biscuits with nuts 300g
£150k/week
Biscuits in a Tube
£40k/week
Buy 40% of the time Buy 35% of the time Buy 90% of the time
High High Low
We should lead our teams to be comfortable to put
Biscuits in a Tube as a priority.
Case Study
Will we ?

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big advice 3 : Keep on eye on the man, not the
dog*
Do not chase the silver bullet.
Big moves come as a sum of small, better decisions.
* As would say Prof. deGrasse Tyson

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as a conclusion
1. Organize our data and structure it, as if we were a customer, not a
professional
2. Pay attention to the weakest link (team, tool, trick) not the best in
class
3. Keep an eye on the man (the trend) not the dog (the short term
vision)
Despite some fantasy, Big Data is really at play and produces major benefits
The future of Big Data is for sure more, better insights
But this will only take place if we

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Can we help?
Jacques.farcy@dunnhumby.comThank
You!
?