Harnessing the Power of Customer Data: A Retailer’s Primer

1. Harnessing the Power of
Customer Data: A Retailer’s
Primer
Personalize experiences at every customer interaction

2. Today’s Speakers
Gavin Estey
Group Director,
Technology
Taylan Oztekin
Digital Strategist
Jaedyn Guthrie
Associate Product
Marketing Manager
Alex Dal Canto
Senior Director
Product Marketing

3. AGENDA
● Appnovation’s Story
● Panel Discussion
● Q&A

4. Appnovation has been a Acquia partner since 2009.
Appnovation is a global, full-service digital partner. We build
purposeful digital solutions that deliver real impact today and
serve as strong foundations for future growth.
Appnovation helps ambitious brands transform into modern
retailers by creating new value, spurring growth, and driving
progress through technology.
At Appnovation, we believe that data should be more than a
form of business intelligence, it should be a differentiator.

5. Where do you,
the marketer,
want to store
your marketing
data?

6. Sales Purchasing POS Analytics Data Lake

7. Data silos are the biggest
stumbling block to an
effective use of your data

8. 47%
Data silos are the biggest
stumbling block to an
effective use of your data
of marketers say their
customer data is siloed
and difficult to access

9. Customer Database
Customer Data Platform

10. Customer Data Platform:
a unified 360° view of the
customer for marketers

11. Putting your data to work
driving your revenue
(by better understanding the customer)

12. Collect first-party
data directly
Avoid data silos
Unify cross-channel
execution
Get to know your
customers

13. CRM DMP
Known customers Unknown Customers

14. Gain
valuable
insights
from data
CDP:
Unifies known and
anonymous
customers, provides
personalization and
predictions
DMP:
Build profiles of
anonymous
customers from
third-party data
CRM:
Tracks customers
intentional
interactions

15. Email SMS Push Social Web Ads
Personal &
Demographics
Behavioral:
Onsite/Offsite
Engagement Transactions
Device/
Location
CHANNELS
DATA

16. Email SMS Push Social Web Ads
CHANNELS
DATA
CDP
User ID & cross-device
tracking/merge
Transformation
& Analysis Segmentation Predictions
Personal &
Demographics
Behavioral:
Onsite/Offsite
Engagement Transactions
Device/
Location
1 2 3 4
Integration
Activation

17. The Journey
END
START

18. END
START
The Journey

19. Live
START
The Journey
Value Delivered

20. How does a CDP
fit in a composable
ecosystem?

21. Growth
Acquisition
Optimization
Retention
CDP for Retail

22. Machine Learning For All Personas
Key
Capabilities
Technology
Acquia Customer Data Platform - Machine Learning Framework
A big data Machine Learning framework performing 3+ billions predictions a day powering
Machine Learning capabilities across CDP and Marketing Cloud
Explainability for All
(ML Center)
Dashboard for transparent &
understandable ML
Intelligence for All
(ML Standard Models)
Families of supervised &
unsupervised ML models
Custom Intelligence
(ML Studio)
Self service ML IDE to build custom
ML models
Personas ML Engineer
Key
Principles
Data Scientist
Data Analyst
Marketing Analyst
Marketing Ops
Democratization
ML across all applications
catering to all personas
Transparency and Fairness
No black box, transparency
& trust predictions
Self-Service
Configure or code your own models
to meet your unique needs

23. Acquia ML supports the configuration and deployment of many variants of supervised, unsupervised
learning and reinforcement learning models.
Prediction Models Personas Models Next Best XP Models
Likelihood
to engage
Likelihood
to buy …
Product
Cluster
Behavioral
Cluster
Seasonal
Cluster
Next Best
Product
Next Best
Channel
Next Best
Send Time
Examples
Predictive
LTV.
Framework
Powered by Acquia Machine Learning Framework
Machine Learning Models
Family
… …

24. Likelihood to Pay Full Price Model Drives Smarter Discount Strategy
Objective
Improve customer spend and campaign ROI by
identifying the right discount level.
Company targeted discounts
• Mild discount for low LTPFP (5-15% off)
• Medium discount for medium LTPFP (15-25% off)
• High discount for high LTPFP (50% off)
Results
• Margin has improved by +26%
Batch and blast blanket discounting had
trained customers to expect a discount
Machine Learning - Use Cases

25. Product Clusters Model Improves Engagement with Category
Personalization
Machine Learning - Use Cases
Acquia product and category clusters determine
which customers belong to wireless headphone
personas.
Step 1: Build personalization based on AI-driven
segments
Retailer wants to personalize in app content to appeal to specific clusters (e.g. customers interested
in wireless headphones).
Step 2: Measure increase in engagement metrics
using A/B testing
Results:
● 21-45% increase in CTR
● 54-125% improvement in
conversion

26. After considering numerous solutions (including developing a
homegrown solution), J.Crew chose Acquia CDP.
Standardizing on Acquia CDP has enabled J.Crew to:
Improve data freshness: Daily, Acquia CDP updates all
transactions, customers and engagement data (email, web),
and all associated summary calculations and machine
learning model scores, allowing J.Crew to quickly and
effectively respond to their customers’ behaviors.
Enhance data quality: MSP’s poor deduplication led to
erroneous lifecycle classification of customers and incorrect
marketing actions.
THE SOLUTION
Acquia Customer Data Platform (CDP)
CDP

27. Q&A