Marketing for newborns: how Analytics and IoT reflect on ... · New mothers marketing path...
Transcript of Marketing for newborns: how Analytics and IoT reflect on ... · New mothers marketing path...
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Marketing for newborns: how Analytics and IoTreflect on the way companies target new generations
Cristina Conti, Analytics Solutions Manager Global Technology Practice, SAS
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Some intro
I’ll be using mom-familiar situations
to present powerful analytical
capabilities that can generate a strong business
outcome
I have a 4 months old daughter
whose birth gave me the idea for
this presentation
I work in SAS Global Practice,
supporting Analytics and Data Science
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One day they’ll rule the world… or are they already?
Gen Z, who are they?
Most often, they are targeted through they romantically embezzeled mothers
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Without too much psychology, mothers are unsure how to treat new babies
Thus, they are very responsive to some very old style, yet very powerful marketing rule… find a need that you didn’t know you had!!
In most mother’s case, this rule is even more powerful as moms are always looking for a magic wand
Why are mothers a good target?
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New mothers marketing path
Traditional word of
mouth: you have it, I want
it
Modern word of mouth:
online blogs
Images: I do, you do, we do
Customer segmentation
Contextual marketing
Internet of things
Optimization
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Data
DeploymentDiscovery
To get VALUE out of any analytics endeavor, 3 key components have to be considered:
• DATA;
• DISCOVERY; and
• DEPLOYMENT.
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Data is the foundation
Structured Data
Online / Digital Data
Machine Data
Social Media Data
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What we do with Data: DISCOVERY
Visualization
Prediction
Machine Learning
Optimization
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How we Operationalize the results: DEPLOYMENT
Data Warehouse
CRM / Call Center
Mobile Channel
Devices
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How? word of mouth and online blogs…
*Mom Consulting Central, 2014
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Ok, so exactly how do we capture them?
From huge unstructured content
To actionable analysis that can
lead to selling our own product
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From a practical standpoint
Natural Language Processing
Context
JL
Machine Learning
H
Discovery
Human Input
Topics, Insights,Relationships, Taxonomies,
Scored Documents
Unstructured Text Data
Operations
Further
Analysis
Text Analytics
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From a practical standpoint
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From a practical standpoint
Model social relations
1
Detect the network
2
Assign the roles and classifythe community
3
Social Network Analysis
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Picture this: you have it, you do it, I want it
*Mom Consulting Central, 2014
83% of influencers have «visual»
accounts: Pinterest, Instagram…
Why pictures matter? Sometimes
we are the pics we post… and
you’ll know exactly what I’m
going through!
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Step 3: Image Recognition
Load Images and Resize
1
Convert ColorsApply noise reduction and
binarizationApply edge detection
Convert to data matrix for machine learning purposes
2 3 4 5
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Segmentation, because my child is not like yours
«needs» toys
to learn how
to crawl
«needs» toys
to manage
teething
«needs» sling
to always be
carried
«needs»
neck-ring to
enjoy water
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Modern targeting through recommendations
Cluster method
KNN method
SVD method
ensemble• User profile
• Order history
• Click history
• Item view history
Item
recommendations
Not just that!
Combine with initial mapping and profiling based on unstructured data to provide even more precise recommendations
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5 moms just finished the baby massage class
It’s lunchtime and it’s raining
They have plenty of time, no need to rush home
Real-time geomarketingGive them what they need
through geolocalized marketing
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Still an end-to-end integrated process
Descriptive
Diagnostic
Predictive
Transactions
Channel Interactions
Opinions / Sentiments
Listen / Filter / Trigger
Listen: Detect Events
Understand: Integrate Data
Understand: Apply Analytics
React: Take Action
Online, Offline
Structured, Unstructured
Match, Merge, Purge
First Party, Third Party
Outbound
Inbound / Real-Time
Orchestrated Omni-Channel
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Connected at birth
(don’t tell them though)
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Ok, maybe no demotic baby yet, but you can check out the demo-tic home at the booth