You Can't Beat Amazon, But You Can Learn from Them.

2019 Zeta Global – Proprietary & Confidential www.zetaglobal.comNovember 6, 2019
You Can't Beat
Amazon, but You
Can Learn from
ThemApplying AI and Data
Modeling to Drive Better
Business Results

2019 Zeta Global – Proprietary & Confidential www.zetaglobal.com |
Zeta Overview
+ Founded in 2007
+ 1,400+ employees
+ 600+ engineers including 80+ data
scientists and 75+ artificial intelligence
engineers/experts
+ 600+ employees in India including 400+
engineers
+ 1,000+ Clients
+ Headquarters: New York City
+ Centers of Excellence: Silicon Valley & SF,
Boston, London, Hyderabad –21 offices in 6
countries
+ Forbes’ Top 50 Most Promising Private
Companies
Our Mission is to reinvent how data and
technology make connections between
marketers and consumers more personal
and business outcomes more impactful.
“
”
2017 Named
VISIONARY
in Magic Quadrant
Digital Marketing Hubs
Number One
Omni-channel Platform
for 2018
Top 20 Companies
for 2017
Named one of the
100 Most Promising Big
Data Companies by the
CIO Review for 2017
Zeta helps the world’s leading brands
drive better business outcomes.
Enterprise Software
Marketing Solutions &
Cross-Channel Campaign
Management
for 2019

David Schey
SVP, Customer Experience
+ Lead strategy and analytics teams at Zeta
+ 20 years experience in marketing and
analytics
+ Launched and ran international S&A teams
in London and Shanghai
Your Presenters
3
Pavan Korada
SVP, Data Science & Analytics
+ Analytics & Data Science practitioner for 15
years
+ Drives marketing ROI for Fortune 100 brands
via the strategic application of modeling,
inference and optimization
+ 5.5 years at Zeta

3 Reasons We Dare Speak the Giant’s Name
Amazon is great at using their AI and
data modeling capabilities to:
1. Treat Customers Differently
2. Anticipate Customers Wants and
Needs
3. Explain the Customer Journey (in the
Context of their 4-walls)
4
Trust Amazon to provide the
most useful product
recommendations
and information
51% 44%
Purchase directly from
Amazon’s product
recommendations

What We Want You to Take
Away After Today’s Webinar
1. Identify unique customer segments based
on interest and intent data
2. Harness the power of our AI, ML and NLP
to predict and capitalize on intent
3. Back-test past campaigns to uncover
signals that can lead to future growth
5
Zeta empowers retailers to bring the capabilities
and benefits of Amazon’s AI and Modeling into
their own four walls:

Bring Powerful AI and Modeling into Your Four Walls
+ Retailers must bring AI and data modeling
into your own four walls.
+ Uncover consumer interest and intent at
the individual level by using powerful AI to
synthesize Zeta’s vast Data Cloud and your
1st-party data.
+ Here’s an example of how we helped one
client drive better business results.
6

2019 Zeta Global – Proprietary & Confidential www.zetaglobal.com | 7
Vast Scale of the Zeta Data Cloud
750M+
Permissioned Users
with Identity-Based
Data600M+ Global
Connected IDs
150M Upvotes &
Comments per
Month
2,500+ Data
Elements per User
3.4BN Unique
Users Monthly
800M+ User Signals
Processed Daily
500+ Intender
Audience
Segments
1 Trillion+ Monthly
Content
Consumption
Signals
100B+ Bidstream
Signals Monthly
3B location visits
Monthly
Data Sources
Proprietary
+ Disqus Network
+ O&O Properties and
Sources
+ Partnerships with Digital
Publishers
Strategic Partners
+ TransUnion
+ Acxiom
+ Liveramp
+ Affinity Solutions
+ PlaceIQ
High-Volume Data-In
Zeta Data Cloud Assets
+ Identity-based Profiles
with Scoring
+ Behavioral Signals
+ Environmental Signals
+ Transactional Signals
+ Transportable Data
Assets
+ Onboarding and
Distribution Pipelines
High-Value Audiences Out

Data Cloud Understands Page-Level Content
URL Title Domain Audience Segment Confidence
https://thepointsguy.com/reviews/hotel-
banke-autograph-collection/
Paris Right Banke: A Review of the
Hotel Banke, Autograph Collection
ThePointsGuy.com Resorts 0.92
Resorts
0.92

Methodology

Back Test Revealed Significant Revenue Opportunity for US
Retailer
Though analyzing historical campaigns and models leveraged for targeting, Zeta was able to demonstrate:
+ An estimated 12 month incremental $9.89M gross margin benefit from 40K shoppers making 53K new transactions —
while delivering $2.4M Gross Margin Benefit* before year end
A total 17% lift^ in predicted likelihood to buy models over current modeling
+ Actives and inactives who are likely to buy
+ Likelihood for price insensitive to buy full price
+ Likelihood for past buyers to buy again with personalized product recommendations
Accelerated customer-centric prediction capabilities through our proprietary buyer intent signal data—
previously outside of brand’s marketing reach
1010
“Connecting with our consumers, especially digitally, is a top
priority as we look to win over the next generation, and our new
model for media partners will help us to deliver on that efficiently
and at scale,” – Client CMO
10
Our analysis criteria: Shopped in last 36M (from our modeling period i.e. Sep 30 2018), with a valid opt-in email address, matched to BAU data, and also additional
exclusions applied (fraud, bulk buyers, employees).
*Gross Sales - Returns - Cost of Goods Sold (65% Gross Margin)
^Relevant lift is described as ‘As a percent of the expected $57.7M 12 Mo. gross margin, what is the incremental 12-month gross margin that can be directly attributed to new
approach. Overall lift across all models collectively is 17%.

Analyze Historical Campaigns To Increase Revenue
Opportunities And Increase The Profitability Of Each Existing
Customer
Approach
Enhance current predictive modeling capabilities with Zeta proprietary signals to identify new
purchase drivers specific to: 1) time in which the customer is likely to buy, 2) the preferred product
3) and price paid. Apply to an independent “observation period” to understand impact:
Client 1st Party
Data
PII, Digital &
Cross-Device
Resolution
Insights from
Signals on Client
Data
Insights Zeta Data In
Motion Signals of
Intent
+ + + =
Improved Margin &
Buy Rate Amongst
Existing Customers
Model Set
Dev. Period
Observation
Period
+3 Months-3 Months

1212
12
12 Month Buyers (Active
and Inactive)
Price Inelastic Buyers
Right Price To Buy
Again
Right Time To Buy
Again
Increased AOVIncreased Buy Rate Increased CLTV
1 2 3
Repeat Buyers
Right Product
To Buy More
Growth
Better
Audiences
Better
Experiences
Best
Outcome
Better
Efficiency
Campaign Prioritization
Campaign Dynamic
content opportunities
Campaign automation
opportunities
Creating A Transformational Roadmap Forward

Back Test Past Campaigns to
Uncover Signals that Can Lead
to Future Growth

Data Cloud Outcomes
1414
14
Back Test Based on Customer Activity Segment Demonstrates
Significant Lift
﹢ Data cloud enrichment over
random population has $403K
12 month incremental revenue
with $100K delivered by year
end* with:
﹢ 24.1% lift in 12-month
active purchases
﹢ 50% lift in 12-month
inactive purchases
﹢ 17% lift in engagement
compared to 4Q19
sample
﹢ Incremental value suggests
Data Cloud enrichment can
effectively be used in
situations where limited
database / transactional
history variables are available.*Not reflecting Seasonally Adjusted Gross Margin

12 Month Order Probability Model Active Account Outcomes
1515
15
Tighter Fit In Prediction Through Modeling Back Test
﹢ Assuming a 650K sample of 12 month active accounts, the peak cumulative sales
difference vs. BAU model is $7.4M. This represents $4.4M in 12 month gross margin
(seasonally-adjusted), equating to a $1.1M 3M contribution by year end (Q4 Oct-Dec).

Identify Unique Customer
Segments Based on Interest
and Intent Data

Price Sensitivity Outcomes
1717
17
Greater Total Items Per Buyer & Higher Total Spend
﹢ Identified High Value Shoppers will buy greater % of items purchased at full price with greater total items per buyer and higher
total spend
﹢ Reduction in discounts over the upcoming holiday season is 8% or $1.1M in protected margin with $14M incremental sales than
the existing BAU model
﹢ Recommend maintaining BAU Discount Seeker and Opportunities current offer approach

Harness the Power of AI, ML
and NLP to Predict and
Capitalize on Intent

Next Best Product Outcomes
Back Test Proved Incremental Cross Shop Behaviors
1919
19
﹢ Product recommendations identified $1.4M incremental sales in 12 months with $354K before year end
﹢ Strong accuracy in Children products (40+%)

Value Based Interest Based
The Beginning:
The Pivot:
The Ascent:
Complete View of
Customer Intent
1:1
Personalization At
Scale
Real Time
Relevance
Predictive
Decision Making
Real Time
Point of
Departure
Predictive
Modeling with
Third-Party Data
Analytics Center
of Excellence
Learning Lab For
Personalization
Testing
Personalization
Center of
Excellence
Activity & Rule
Based
Triggers
Digital
Commerce
Center of
Excellence
To Be Personal, Perceptive and Productive
Point of
Arrival

2019 Zeta Global – Proprietary & Confidential www.zetaglobal.com | 21
David Schey Pavan Korada
dschey@zetaglobal.co
m
pkorada@zetaglobal.co
m

UpcomingEvents
01SeeZetadiscusshow
to captureconsumer intent
through AI, MLand NLP.
AI & Bi g Da t a
i n Sa n t a Cl a r a
1 1 / 1 3 02 Join Zetaat Brand Innovatorsfor
awomen’spanel focused on
marketingfor next-gen
consumers.
Br a n d I n n o v a t o r s
Ma r k e t i n g I n n o v a t i o n
I n Ch i ca go 1 1 / 1 9 03Our presentation will dive
deeper into boost business
outcomesthrough back testing
and signal harnessing.
Gr o w t h Ma r k e t i n g
Co n f e r e n ce i n Sa n
Fr a n ci sco 1 2 / 1 0 - 1 1
Upcoming Events
01See Zeta discuss how
to capture consumer intent
through AI, ML and NLP.
A I & B i g D a t a
i n S a n t a C l a r a
1 1 / 1 3 02 Join Zeta at Brand Innovators
for a women’s panel focused
on marketing for next-gen
consumers.
B r a n d I n n o v a t o r s
M a r k e t i n g I n n o v a t i o n
I n C h i c a g o 1 1 / 1 9 03Our presentation will dive
deeper into boost business
outcomes through back testing
and signal harnessing.
G r o w t h M a r k e t i n g
C o n f e r e n c e i n S a n
F r a n c i s c o 1 2 / 1 0 - 1 1

2019 Zeta Global – Proprietary & Confidential www.zetaglobal.com

You Can't Beat Amazon, But You Can Learn from Them.

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