Driving In-Store Sales with Real-Time Personalization - Cyril Nigg, Catalina Marketing

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Driving In-Store Sales with Real-Time Personalization. #h2ony - Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai - To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata

Data & Analytics

DRIVING IN-STORE SALES
WITH REAL-TIME
Presented by
Cyril Nigg
PERSONALIZATION

Who is Catalina?
Personalized digital media
Drive CPG volume & ROI
In-store and online
We’re a data company…
2
26 Billion
Shopping Trips per Year
450K+
Checkout Lanes
280MM+
Unique Shopper IDs
2 Billion
UPC Scans per Day
Our in-store network

Retailer Problem - Circulars
100’s of promotions weekly
Millions of dollars spent
Average shopper buys <1%
Need a better way
3

My Favorite Deals
• Personalized Circulars –> Find relevant products
• One-to-one communication
• Delivered in-store prints, email, online
• Measurable results –> incremental sales
• Real-time Personalization in action!
4

More Analysis, Less Implementation
Goal: Hands off execution
5

Three Elements to Success
6
DMP
Aggregation
API
h2o
POJO
Delivery
Monitoring
1 2
3
Real-time Personalization Execution

h2o POJO
• Direct upload of model
• No Dev work needed
• No translation
• Model flexibility
8
Data Science Env
Python / R
h2o
Model
POJO
Execution Platform

Monitoring
• Low touch -> fewer “eyes”
• Not traditional monitoring
– Server response vs data input / output values
– Total Sales variable example
9
DMP
Aggregation
API
h2o Delivery
Monitoring

Better Real-time execution
• Aggregation API -> Scalable features
• h2o POJO -> Fast implementation
• Monitoring -> Identify issues
10

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