Leverage Real-Time Purchase Intent to Boost Sales & Customer Growth

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!

Leverage Real-Time Purchase Intent to Boost Sales & Customer Growth

Leverage Real-Time Purchase Intent to Boost Sales & Customer Growth

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Leverage Real-Time Purchase Intent to Boost Sales & Customer Growth