1. Akamai Media Analytics: Driving Engagement
Girish Bettadpur, Sr Product Manager
Emily Glass, Sr Product Marketing Manager

2. 2011: The Hyperconnected World
40% adult Americans own smartphones, 5% tablets2 ?
86% of US Internet audience watched online video1
Royal Wedding: 1.73M simultaneous streams3
1ComScore August 2011 data, 2Nielsen , 3Akamai

3. : Emotional involvement or commitment
What is Engagement?
: Emotional involvement or commitment
: To occupy the attention or efforts of

4. How does the Industry Measure Video Engagement?
Total Streams
14.5B
Streams
6.2B
Sessions
142.6M
Unique Viewers
178M
Hours per Viewer
4.5
16.8
June 2011
Nielsen
ComScore

5. How Do You Measure Engagement?
Data is powerful - Context is critical

6. 6,928,198,253 (est.) World Population Drivers of Engagement
Bits per month
% of premium content to CE Devices

7. Drivers of Engagement You Can Control
CONTENT
PACKAGING
QUALITY

8. Akamai Media Analytics
Audience Analytics
Content usage, viewership, and quality reports and dashboards
Quality of Service Monitor
Real-time visibility into performance
Cross-platform support
Live, VOD, and 24x7 streams
<video>

9. Engagement Case Study

10. Engagement Case Study Using Media Analytics:
We looked at range of Media publisher data on our network
Analyzed over 30M viewers, 75M plays, 100 titles
Sliced by content, packaging and quality
Focused on video on-demand content
Supplemented with IDC data from live events study for quality

11. Does New Content drive viewer engagement?
Visits
Viewers
49%
56%
40%
Plays
19%
Play Duration

12. Advertising Placement & Abandonment
Where do ads typically appear?
Pre-Roll
Content
Mid-Roll
Post-Roll
Ad Starts:
25%
74% 1%
Pre-Rolls drove 80% of ad abandons

13. Advertising Abandonment by Content Length

14. Quality Drives Engagement
Correlation Between Session Time and Playback Bit Rates for Cases Up to the Optimal Bit Rate Threshold for Each Event
++500 kbps =
10% longer engagement
(Correlation Coefficient)
Source: Akamai Data

15. Summary View into Content, Packaging & Quality
Gain Insights into Audience behavior
Drive Decisions

16. Product Demo

17. Product Roadmap

18. Media Analytics — Roadmap Summary
Q4 11
Q1 12
Q2 12
Q3 12
Q4 12
V4.2
Focus on LIVE events
Ease of use
V4.3
Diagnostic Tools
Support for new business models
V4.4
Self-healing abilities
Viewer-level insights
Continuous innovation: connected device support

19. Thank You

20. Insight: Content Popularity varies by Geo, and genre

21. Insight: Ad Targeting Works3X
2.5X
Ad was targeted at Mid West Audience 3X the average
Ad was targeted at West Region Audience 2.5X the average
1.5X -
South Region Abandoned at 1.5X the West Region Audience
South and Mid West had the same Abandonment Rate

22. Insight: Loyal Viewers wait twice as long for video to start8X
Difference in Startup Abandonment as Startup Time goes up from 2s to 3s
97%
Abandonment Rate when Startup Time goes beyond 10s 3s
Time that “loyal” viewers are willing to wait for video to start

23. Insight: Buffering Sensitivity is not constant
% of Total Plays
LESS
AVERAGE
MORE
Rebuffering
100
Indicates average rebuffering for top 3 categories (1.6s per minute of play time)

24. Insight: Abandonment rates vary by Ad Type
16%
Ad Abandonment Rate for Top 2 Ad Types 5%
Ad Abandonment Rate for remaining Ad Types 2X
Pre Roll percent higher than average for Top 2 Ad Types

25. Insight: Buffering Sensitivity is not constant
DAYTIME
DRAMA
COMEDY
LESS
AVERAGE
MORE
Rebuffering
50%
Comedy and Drama viewers are 50% more sensitive to rebuffering than Daytime show viewers

26. But Performance Has Never Been More Important…
Correlation Between Session Time and Rebuffering Events per Hour
(Correlation Coefficient)
Rebuffering is the number 1 cause of decreased viewing times…
Source: Akamai Data, 2010

27. Insight: Ad Density Tolerance Levels should be monitored
80%
Pre-rolls are driving 80% of the ad abandons
25%
Portion of Ad Starts that were Pre Rolls

28. Roadmap Summary
Support for subscription and hybrid ad+subscription models Support for automated insights and recommendations so you can drill down from insights to data Diagnostic features that will not only help find problems but isolate them quickly with easy to use decision tree like constructs Support for data collection across all devices?? adverts