Leon Zemel, Chief Analytics Officer of [x+1]: Client case study on leveraging big data.

1. Leon Zemel
Achieving big marketing
goals through Big Data

3. What has small data driven?
Too broad &
Too low frequency

4. What has small data driven?

5. What has small data driven?
Too broad &
Too low impact

6. The Digital Marketer Challenge
Display conversions top out
1,600
1,400
1,200
1,000
Display attributed conversions
800
600
400
200
-
Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 10 Week 11

7. The Digital Marketer Challenge
Display not growing overall business
4,000 1,600
objectives
3,500 1,400
3,000 1,200
2,500 Digital Sales
1,000
Display attributed conversions
2,000 800
1,500 600
1,000 400
500 200
- -
Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 10 Week 11

8. Client Journey
Business Growth
User Interactions

9. Client Journey
Audience Audience Impact

10. Audience

11. Audience
Product Relevancy and User Need
Urban dweller College grad Family guy

12. Audience Behavior

13. Audience Behavior
In Market Readiness
Visited website
Searched keywords Clicked banner

14. Audience Impact
5 billion monthly marketing interactions
Performance campaigns

15. Audience Impact
Finding the OFR by Audience Segment
30,000 25%
25,000
20%
20,000 Performance
15%
15,000
10%
10,000
5%
5,000
- 0%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Frequency

16. Audience Impact
Finding the OFR by Audience Segment
120,000 25%
100,000
20%
80,000 Performance
15%
60,000
10%
40,000
20,000 Not in target 5%
In target
- 0%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Frequency

17. Audience + Impact
Optimizing Negotiated Media
Audience Quality
Audience Impact

18. Audience + Impact
Optimizing Negotiated Media
Audience Quality
Audience Impact

19. Audience + Impact
Optimizing in RTB
120,000 25%
100,000
20%
80,000 Performance
15%
60,000
10%
40,000
5%
20,000
Not in target
In target
- 0%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Frequency

20. Audience + Impact
Optimizing in RTB
120,000 25%
100,000
20%
80,000 Performance
15%
60,000
Not in target
10%
40,000
In target 5%
20,000
- 0%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Frequency

21. And the Results…
The old way Calibration
100,000,000 5,500
90,000,000
Period 5,000
80,000,000
4,500
Digital Sales
70,000,000
4,000
60,000,000
3,500
50,000,000
3,000
40,000,000
2,500
30,000,000
2,000
20,000,000
1,500
10,000,000
- Marketing 1,000
Investment

22. And the Results…
The old way Calibration Optimized
100,000,000 5,500
90,000,000
Period 5,000
80,000,000
4,500
Digital Sales
70,000,000
4,000
60,000,000
3,500
50,000,000
3,000
40,000,000
2,500
30,000,000
2,000
20,000,000
1,500
10,000,000
- Marketing
Investment
+20% growth 1,000
in total digital
channel sales

23. Key Takeaways
Unlock value from marketing data:
Identify key consumer states at the
user level
Balance marketing strategy and
investment to each user segment, in
real-time when possible

24. Key Takeaways
Advertisers and agencies have
unprecedented control over
optimizing frequency by audience
segment
Companies manage business impact
by user segment have driven
significant growth in their digital
channel

25. Customer Insight Through Deeper Analysis
(The Fastest Climbers Win)
Optimization
Predictive
Analytics
BI Reporting and
Ad-Hoc Analysis
• What is the
best choice?
• What will happen?
• What will the impact be?
• What happened?
• When and where?
• How much?