From audience approach to reliable platforms and tracking measurement, Tinuiti and partners are here to help marketers update their strategies in the face of increased privacy. Join our exclusive series as we unpack the top priorities for your social media advertising in a year where everything is changing.

1. 2021 Social Media
Advertising Series
The New Approach to Audience in Today’s Privacy Landscape
10am PT / 1pm ET
How TikTok’s Authenticity Impacts the Customer Journey
10:50am PT / 1:50pm ET
Creative & Storytelling Across Social Channels
11:40am PT / 2:40pm ET
Maximize Your Influencer Strategy
12:30pm PT / 3:40pm ET
Leverage Real-Time Purchase Intent to Boost Sales
1:20pm PT / 4:20pm ET

2. Machine Learning:
Leverage Real-Time
Purchase Intent to
Boost Sales & Grow
Customers

3. Today’s Logistics
Analicia Santaella
Partner Marketing Manager
Submit questions for live Q&A
Download relevant resources
Recording & slides will be
sent tomorrow
01
02
03
Join our poll questions
04

4. Some of
our clients
Our
Recognition
Tinuiti is the largest independent performance
marketing agency across the triopoly.

5. Our Speakers
KELSEY MILLER
Associate Director, Paid
Social
LYNNE HAMILTON
SVP Sales and Service
BOBBY KELLY
Director of Client Strategy

6. Black Crow AI’s ML platform
has been deployed to over
300 ecommerce sites…
… made more than 4 billion
predictions per month…
… and unlocked more than $1
billion in incremental profit for
our partners.
Our plug-and-play ML has
quickly transformed
companies across industries.
Black Crow AI provides custom, plug-and-play machine
learning predictions for ecommerce
300
Partners
+4B
Predictions
+$1B
Profit
Any
Industry

7. Today’s
Takeaways
● Machine Learning has arrived + is creating winners
and losers
● It should be on your shopping list
● With ML, your first party data is enough
● It’s affordable and easy (yes, easy)
● It works fast: Tinuiti | BlackCrow Case Study
How a clothing retailer drove 65,000 new
customers at a 2x ROI
7

8. 8
is powerful
is proven
is at an inflection point
MACHINE
LEARNING

9. 9
What is
Machine Learning?
Machine learning (ML) is the study
of computer algorithms that
improve automatically through
experience and by the use of data.
What is (Great)
Machine Learning?
Powerful
predictions
Efficient
delivery
Practical
application
Provable
results

10. POLL:
Do you use machine learning today?
a) Does my computer count?
b) A little bit...I think.
c) Yes-ish.
d) Yes, we love it.
e) I work for Amazon. I breathe machine learning.
10

11. 11
Machine learning
is now foundational.
What was once a
buzzword and then a
proven possibility is
essential now to
continued market
leadership.
machine
learning
(today)
machine
learning
(1980+)
PROVEN
WEB 3.0
BLOCKCHAIN
IT SYSTEMS
CRMS
DATA SECURITY
TOOLS
BARCODE
DISTRIBUTED CLOUD
CLOUD STORAGE
JET PACKS
HOVERBOARDS
FAX MACHINES
PC
SWITCHBOARDS
VIRTUAL REALITY
HOVERBOARDS
(AGAIN)
machine
learning
(2010+)
TODAY
YORE
BUZZWORD
FOUNDATIONAL

12. 12
should be your bedrock
is required to keep pace
is needed to win
MACHINE
LEARNING

13. 13
“Machine learning drives our algorithms for
demand forecasting, product search ranking, product
and deals recommendations, merchandising placements,
fraud detection, translations, and much more.
Though less visible, much of the impact of machine
learning will be of this type — quietly but meaningfully
improving core operations.”
― Jeff Bezos

14. 14
With masses of resources and time, you can
leverage builder tools + large data science
teams to win
Anyone can get glimpses of ML power trapped
in point solutions - but it won’t be enough to win
MARKET
LEADERS
ARE SET UP
TO WIN

15. WHAT THEY WANT: efficient build tools
ML tools can
be crafted for
two personas
WE FOCUS ON THE ‘USER’
15
“BUILDER”
“USER”
DATA SCIENTIST
DATA ENGINEER
COMMERCIAL OWNER
DATA ANALYST / BI ANALYST:
WHAT THEY WANT: business outcomes

16. 16
provides transformational insights
let’s you predict the future
can do what no human can do
MACHINE
LEARNING

17. It can do it all on
just first party data
17

18. 18
THIS IS WHAT RAW DATA LOOKS LIKE

19. 19
PRE-ML, WE HAD WAYS TO GROUP & SORT

20. 20
ML BETTER DIFFERENTIATES AND SORTS YOUR CUSTOMERS

21. 21
And with
machine learning
we can see - and
understand so
much more.

22. 22
10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
10%
20%
30%
40%
50%
60%
0%
0%
AN AVERAGE
30-DAY SITE VISITOR
PERCENTAGE OF TRAFFIC
CONVERSION
RATE
9% CONVERSION RATE

23. 23
ACTUAL
CONVERSION
RATE
60X
value
0.90% 0.93% 1.29% 2.46% 3.08% 4.75%
8.53% 12.54%
20.24%
61.07%
1 2 3 4 5 6 7 8 9 10
23

24. 24
Machine learning can ignite any team, any industry
ACTUAL
CONVERSION
RATE
ACTUAL
CONVERSION
RATE
FUTURE VALUE SCORE
FUTURE VALUE SCORE FUTURE VALUE SCORE
FOOTWEAR STOCK TRADING
HEALTH SUPPLEMENTS B2B PRINTING
FUTURE VALUE SCORE
FUTURE VALUE SCORE FUTURE VALUE SCORE FUTURE VALUE SCORE
ONLINE TRAVEL APPLIANCES
LOCAL LISTINGS
AIRLINE
FUTURE VALUE SCORE
24

25. 25
future-proofs your company
gives marketers superpowers
can be easy
MACHINE
LEARNING

26. Real-time predictions with just first party data
26
1
2
3
4
5
6
7
8
9
10
Real-time Behavior
• Current activity and actions
Historical Behavior
• Past activities and actions
• Search Parameters (Contextual)
• Date, time, keywords, intent, etc.
Purchase History
• Past conversions and purchases
Traffic Source
• Location, device, OS, etc.
Product Details
• High Margin, Complementary
SKU, etc.
First-party Data
INGEST
Machine Learning
APPLY
Real-time Predictions
OUTPUT

27. Machine Learning can be easy, flexible, and powerful
27
Integrate in minutes with one of
our tag manager templates
Custom predictions available
before every page load
Easily plug scores into all of the
tools and platforms you love
ADVERTISING
EMAIL / SMS
MARKETING CLOUDS
Site MONETIZATION
CONTACT CENTER
CDP/DMPs
DATABASE
CRO
PREDICTIONS

28. Without these predictions, campaigns appear to meet performance targets
9% CONVERSION RATE
ALL USERS
CONVERSION
RATE
Cart abandoners
High-Value Page Visitors
30-Day Site Visitors
10%
20%
30%
40%
50%
0%
28
REMARKETING

29. Without these predictions, campaigns appear to meet performance targets
ALL USERS
CONVERSION
RATE
$10
$20
$30
$40
$50
$0
$23 CPA
10%
20%
30%
40%
50%
0%
9% CONVERSION RATE
29
REMARKETING

30. 30
4%
6%
16%
22%
48%
1 2 3 4 5 6 7 8 9 10
10%
20%
30%
40%
50%
0%
Predictive Scores
CONVERSION
RATE
REMARKETING
30

31. 31
4%
6%
16%
22%
48%
$52
CPA
$25
CPA
$8
CPA
1 2 3 4 5 6 7 8 9 10
$8
CPA
$10
$20
$30
$40
$50
$0
10%
20%
30%
40%
50%
0%
CONVERSION
RATE
31
REMARKETING
Predictive Scores

32. 32
4%
6%
16%
22%
48%
1 2 3 4 5 6 7 8 9 10
14%
13%
12%
10%
20%
30%
40%
50%
0%
8%
7% 7%
CONVERSION
RATE
32
REMARKETING
Predictive Scores

33. 33
4%
6%
16%
22%
48%
1 2 3 4 5 6 7 8 9 10
10%
20%
30%
40%
50%
0%
CONVERSION
RATE
33
REMARKETING
Predictive Scores

34. 34
4%
6%
16%
22%
48%
1 2 3 4 5 6 7 8 9 10
10%
20%
30%
40%
50%
0%
CONVERSION
RATE
34
REMARKETING
Predictive Scores

35. Cool. But what
about prospecting?
35

36. 36
1 2 3 4 5 6 7 8 9 10
20%
40%
60%
80%
100%
0%
ALL USERS
CONVERSION
RATE
1 2 3 4 5 6 7 8 9 10
20%
40%
60%
80%
100%
0%
ALL USERS
CONVERSION
RATE
PRIOR CONVERTERS
as a proportion of all traffic
HIGH SCORE USERS
as a proportion of all traffic
Half of who Google and Facebook end up
looking for are Low and Medium users,
decreasing likelihood of finding more High
Propensity users
Narrowing the scope of lookalikes to
High Scores results in finding more Buyers
and more conversions at a higher ROAS
Lookaliking

37. POLL:
Which of these takeaways resonates with you most?
a) Machine learning has arrived + is creating winners and losers.
b) Machine learning should be on your shopping list.
c) With Machine learning, your first party data is enough to put you in the win column.
d) It’s affordable and easy - yes, easy.
e) Graphs rock.
37

38. HOW MACHINE LEARNING
CAN FUEL SOCIAL
CAMPAIGNS
38

39. Building ML audiences
that update in real time
● Black Crow segments are built as
website custom audience (WCA)
segments that are updated in real time
○ Every time a user take an action on
the website their future value
score is subject to change
● Structuring the audiences as dynamic
WCAs prevents ad sets from going into
the learning phase with each update
● Recommend grouping scores into a low,
medium, and high bucket
WCA_BlackCrow_Low Remarketing Scores_1-3
WCA_BlackCrow_Medium Remarketing Scores_4-7
WCA_BlackCrow_High Remarketing Scores_8-10
Lookalike (1-2%)_BlackCrow_High Future Value Scores_8-10
Lookalike (3-4%)_BlackCrow_High Future Value Scores_8-10

40. Implementing smarter bidding
Campaign
Low
Future
Value
Scores
Medium
Future
Value
Scores
Ad 1 Ad 2 Ad 3 Ad 1 Ad 2 Ad 3
High
Future
Value
Scores
Ad 1 Ad 2 Ad 3
25%
average CVR
6.5%
average CVR
1.5%
average CVR
● By de-averaging purchase conversion
rates, advertisers can heavy up spend
against users most likely to purchase
or subscribe
● Separating website visitors by future
value scores replaces tiering by
recency of visit
● Scores allow media managers to be
more strategic with bidding
○ Campaign Budget Optimization will
naturally allocated higher spend to high
scores
○ Can accelerate this by setting higher daily
ad set spend minimums or more aggressive
target CPA goals for high scores

41. Preparing for upcoming privacy
changes
● Currently, about 70% of IOS users share their IDFA with
app publishers, after the rollout of Apple’s opt-in tracking,
it is estimated that this number will drop to 10% to 15%
across social channels
● Leveraging Black Crow segments allow brands to
preserve purchase intent signals throughout privacy
changes and IDFA deprecation
● Facebook has instructed advertisers to limit pixel
tracking to 8 conversion events. Black Crow’s scores are
sent into Facebook as custom events not used for
conversion tracking
○ Black Crow’s custom pixel events will not take up
any of your eight event slots
“Upcoming privacy
changes are going to
significantly impact Social
reporting and perceived
effectiveness of the
channel.
The key to success will
be honing first party
data signals and
exploring more
sophisticated ways to
measure the channel's
performance.”
-Avi Ben-Zvi, Group Director
Tinuiti Paid Social

42. Screenshot
Increasing the sophistication of
your messaging strategy
After segmenting your audience approach, think
about what creatives to pair with low, medium, and
high future value scores
● Do you want to serve customized deals to your highest
value customers to incentivize higher average order
value?
● Do you want to callout different product categories or a
separate reason to buy to an individual with a medium vs
high future value score?
● Are there stronger monetary discounts that you want to
offer individuals assigned a low score

43. HOW A CLOTHING
RETAILER DROVE 65,000
NEW CUSTOMERS
AT A 2X ROI
Tinuiti | Black Crow Success Story
43

44. THE
OPPORTUNITY
Like most brands in 2020, a women’s clothing retailer
had their in-store revenue significantly decline due to
COVID-19 with temporary store closures and consumers
shifting to digital purchasing methods. Within the critical
Q4 holiday period, the brand needed their digital
advertising dollars to work harder, driving increases in
both year-over-year revenue and new customers.
The brand partnered with Tinuiti & Black Crow ai to
integrate machine learning technology into their
targeting approach.

45. Training the Machine
Learning Model
● Using machine learning, Black Crow
analyzes over 400 website signals to
predict the likelihood of each user’s
purchase
● Website visitors were divided into ten
equal-sized cohorts based on the
anticipated rate of purchase
● After monitoring the retailer’s website
for 3 weeks, Black Crow identified a
40x differentiation in purchase
conversion rate between future value
scores one and ten

46. Activating the Scores
Screenshot
Screenshot
1. OPTIMIZING BIDS
Increased bids and spend against the 8-10
high scores who purchase at 10x higher rate
than low 1-3 scores.
Decreased bids against low scores.
2. TAILORING THE MESSAGING
STRATEGY TO PRESERVE MARGIN
We preserved margin by reserving high-value
promotions to only lower purchase intent
website visitors (scores 1-3) to incentivize
purchases.
Meanwhile high purchase intent users
(scores 8-10) received full-price new arrivals
creative.

47. Driving Prospecting Efficiencies
Leveraging a real-time purchase intent model led to significant
improvements in the retailer’s revenue efficiencies & new
customer growth across Facebook/Instagram:
Higher spend*
30%
lower CAC*
48%
higher ROI*
2x
*compared to prospecting campaign average
The AI powered purchase intent segments drove 65,000 new
customers for the retailer in Q4 2020.

48. Building upon the success
Expanded lookback of retargeting windows to 180 days
● To scale the success further, we expanded the website
retargeting beyond a 30 day lookback
Using scores to predict lapsed customers
● Combine Black Crow and the client’s first party data to
anticipate and prevent lapsed buyers
● Serve custom messaging and promotions to incentivize
continued purchases
Expanded
spend
6%
lower CAC*
14%
*compared to prospecting campaign average
higher ROI*
1.5x

49. Building upon the success
Leveraging predictive audiences
outside of paid marketing:
● Uploading scores in Adobe Analytics for
better insights into users
● Uploading scores into Dynamic Yield -
preparing to test on-site personalization
● Next plugging scores into Oracle
Responsys + Attentive to personalize
email + SMS targeting

50. Schedule Your
Consultation
with a Social
Media Expert

51. Build your custom
Model Today!
Get Started on your
custom model today
See how our machine learning can
segment your site users and better
leverage your 1st party data with an easy
30 day free trial

52. Q&A

53. Thank you!