Putting Consumers first using Data Science
uncover valuable insights into what customers want, where
they want it, and how much they’re willing to pay for it
Thank Youabout
What we do – the ‘elevator pitch’
dunnhumby is the world’s leading customer science company.
We analyse data and apply insights from more than 400 million customers across the globe to create better customer experiences and build loyalty.
Our insights and strategic process help clients create competitive advantage and enjoy sustained growth.
WHYWe’re passionate about loyalty and partnering for future growth
HOWWe place customers at the center of every decision
and personalize their experience
WHATOur capabilities build loyalty and emotional connections with
customers that create a lasting competitive advantage
Our mission
© dunnhumby 2014 | Confidential6
“We have loyal customers”
Assort based on sales and margin
Growing gross margin by vendor/class
Marketing to mass or broad group
Episodic customer insights
Acquisition based promotions
PRODUCT-CENTRIC ORGANIZATIONS
The best retailers put the customer at the center of every decision
“We are loyal to our customers”
Right products for the right customers
Grow share of customer wallet, profitably
Personalized targeted marketing
Continuous test and learn
CUSTOMER-CENTRICORGANIZATIONS
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Data allows you to see customers as individuals
VALUE
CONVENIENE
VALUEEXPERIENCE
VARIETY
CONVENIENCE
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And personalize the experience across your business
MASSDIFFERENTIATED
(Segmented) PERSONALISED
PR
ICE
&
PR
OM
OT
ION
AS
SO
RT
ME
NT
CO
MM
S
SELECT THE BEST PROMOTIONS
TARGETED PRICE INVESTMENTS
MY PERSONAL PROMOTIONS
SELECT THE CORE RANGE
DIFFERENTIATED STORES
MY SHOPPING LIST
EVALUATE IMPACT ON LOYALTY
CUSTOM CONTENT MY PERSONAL COUPONS
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We use data to maximize the relevance of 1:1 communication
1:1COMMUNICATION
FREQUENCY & CADENCETiming of touch points
CONTENTCustomized content
CHANNELReaching the customerwith relevant touch points
TARGETINGFinding the right customer
OFFERRelevant offers
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SEGMENTATIONTARGETING
15 % BUYINGBEHAVIORALSEGMENTATION
22% ENHANCEDHOUSEHOLD
TARGETING
31% CUSTOMERRESPONSE
48%1:1
RELEVANCY
55%
We know that make things more relevant to customers drives sales
% of households engaging in communication over time
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I feel like this is just for me.
This is something I am interested in.
I feel they really know me.
“WOW
WOW applies to every 1:1 connection with the customer
including offers, content, messaging and more.
The theory of
And helps to win the hearts and minds of your customers
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• Focus on customer loyalty• Relevant, timely, personalized
customer communication by channel• Measurable and sustainable ROI-
value for your money• Ability to handle complexity• Complete package at scale
(Strategy, technology, analytics, and execution)
• Custom Designed Solutions• Unsurpassed expertise in analytics
& insights• Broad scale experience
in retail• The option of pursuing a broader
customer insights• Unique capabilities including
advanced social media advocacy
We can help to shift the focus to the customer
WHAT DUNNHUMBYCAN PROVIDE WHAT MAKES US DIFFERENT
CASE STUDIES
Macy’s
Macy’s Custom Books leveraged data to deliver each customer with more relevant content
A single Custom Book campaign could produce over 500,000 unique versions of the book, reflecting the shopping behavior of
each customer
• Custom Books were personalized by featuring the most relevant combination of product categories for each household
• Content/category selection driven by customer shopping data
• Offers, promotions, and creative execution were the same between Custom and Traditional books
15
16
“effective reach” is a critical concept…you don’t need to talk to everyone about everything to drive category sales
36-M
ENS SPORTSW
EAR X C
OLL
79-T
RADITIO
NAL SPORTSW
EAR
Category Lift per HHCustom Book vs. Base Book
16-W
OMENS S
HOES
85-H
OUSEWARES
3-PETIT
E SPORTSW
EAR
7-HOSIE
RY
81-T
EXTILES
33-C
OLOR AND T
REATMENT
38-F
RAGRANCES
26-K
IDS
6-FA
SHION J
EWELRY
5-M
ENS COLLECTIO
NS
25-M
ENS FURNIS
HINGS
8-HANDBAGS
35-F
INE J
EWELRY
12-C
ASUAL SPORTSW
EAR
28-W
OMEN'S
SPORTSW
EAR
84-L
UGGAGE
13-D
RESS ACCESSORIE
S
31-M
ENS TAIL
ORED CLOTHIN
G
86-F
URNITURE
22-IN
NERWEAR
87-M
ATTRESSES
82-T
ABLETOP
10-J
UNIOR S
PORTSWEAR
68-D
EC HSW
RS/TABLE L
INENS/D
ECOR
19-S
ILVER
27-B
OYS 2-2
0
80-N
EO COLLECTIO
NS
20-C
OATS
Sales for most categories in the Macy’s Custom Book matched or beat the “Traditional Business as
Usual” Book in spite of the category only appearing in books
for 30% of households (on average)
Our experience shows the longer term benefits of relevant content
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37
Week After First Customized Mailer
Cu
mu
lati
ve C
ust
om
ers
Sal
es L
ift
Fro
m R
ecei
vin
g P
erso
nal
-iz
ed M
aile
r
1 2
3
4
6 10X lift from 6 personalized campaigns vs 1
5
• Relevancy is about continually engaging customers with the right content over time
Impact of relevant content on Lift (37 weeks)
17
Kroger
Kroger’s MyMagazine brings personalized custom publishing to the grocery space
• Targeted editorial content• Increased emotional connection• Customer shopping data drives content
targeting
• Balanced coupon offering• 8 ranked retention offers• 8 ranked acquisition offers
And delivers seamless experience online
Open rates significantly higher than industry average
Personalized version outperformed previous campaign 2:1
Customers reaction was overwhelmingly positive “Finally! Thank you for making the magazine and the coupons digital.”
“Neat. I like this being tailored to my shopping habits.”
How Does Exadata Enable This
?
Several examples of why dunnhumby has been successful using Exadata
• Exadata performed 8x better than the next-closest competitor for our workload!
• Speed in data manipulation facilitates more data science and therefore more relevancy
• Concurrency was key
• SQL – A simple, yet powerful way to manipulate the data for analytical readiness
• Sharing and packaging SQL is easy
• 70% of our analysis done right in the database using SQL
• Oracle R enables deeper modeling without moving the data
How Exadata makes this possible
dunnhumby Engineered Architecture
Some fun technical bits
?
In addition to ETL staging and processing, we perform all full and incremental backups to the ZFS Appliance
• Roughly 14Tb per hour
• Full backups are then offloaded to tape
• Using the ZFS Appliance saves Exadata resources
Backups using the ZFS Appliance
?
Where are we headed with the Big Data Appliance
• Near-line storage for historical data
• Low cost distributed processing for analytical modeling
• Platform for machine learning
• Just the beginning
Use Cases for the BDA
?
dunnhumby is excited about the future
• Utilizing the ZFS Appliance for TEMP tablespaces
• Approximate DISTINCT COUNT functionality – a dunnhumby addition
• In-Memory Columnar Database
• R&D on creating RAM disk for TEMP tablespaces
What about tomorrow?
Thank You