Deck from "Advanced Integrations of Social Media Analytics" workshop at SXSW 2011. Workshop featured: Blake Robinson, Chris Lightner, Margaret Francis, Megan Costello and Susan Etlinger

1. March 15 2011
Advanced Integrations of Social
Media Analytics
#SOCIALMEASURE

2. Advanced Integrations of Social Media Analytics
1. Objectives Based Strategy
2. Understand where conversations occur
3. Social Media Metrics
4. Demos
5. Social Media Reporting
6. Shaky Metrics
7. A Number Is Not a Decision
8. Integrated Program Design

3. Presenters
Blake Robinson, Rackspace @blake
Susan Etlinger, Altimeter @setlinger
Megan Costello, Crimson Hexagon @megcos
Margaret Francis, MarketLive
@margaretfrancis
Chris Lightner, Edelman @clightner
#socialmeasure

4. 1. Objectives Based Strategy
4

5. Objectives differ by level
Corporate
Risk
management Business unit
Consistency
Leadership
development
& culture
across brands
Brand
Social strategist
& COE
Community
Engagement
Channel focus manager &
metrics
education
Value metrics ROI metrics
Source: Jeremiah Owyang, Altimeter Group

6. Use appropriate metrics at each level
Corporate Business metrics: revenue, CSAT,
reputation.
LOB/Geo Social media analytics: Insights, share
Stakeholders of voice, resonance, WOM.
Social Engagement metrics:
Strategist/Community fans, followers, clicks.
Manager
Source: Jeremiah Owyang, Altimeter Group
6

7. The new lifetime value calculation
• Percent that refer
+ Value of purchases • Size of their networks
-Cost of acquisition • Percent of referred
+ Value of new customers from people who purchase
referrals • Value of purchases
+ Value of insights
• Percent that provide
+ Value of support
support
+ Value of ideas
____________________ • Frequency and value of
= Customer lifetime value the support
Source: Charlene Li, Altimeter Group

8. Objective Setting Exercise
Assess current state: Envision future state:
1) Categorize your use case: 1) What are you trying to
social media marketing, achieve with social media?
PR, brand marketing, or
2) What do you want to
executive, support
measure? Why?
2) What are you currently
3) What would the ideal
doing with social media?
social media analytics
Why?
program be able to tell
3) What are you currently you?
measuring? Why?

9. 2. Understand where social media
conversations occur
9

10. Tsunami

11. Ford Focus

12. Oreo

13. Where do people talk about Coke Zero?
Used with permission of Netbase
13

14. Where should I invest my marketing $?
Used with permission of Netbase
14

15. 3. Social Media Metrics
15

16. “Social” Metrics
• # Video Views • # Facebook fan pages
• % YouTube Favorites • # Facebook fans
• % YouTube channel subscribers • Facebook Fan Rate
• % YouTube Video Plays • Facebook Likes
• # of YouTube Channel Comments • Email Open Rate
• # of YouTube video reviews • Email Click Rate
• # slideshare views • Email Forward rate
• # delicious bookmarks • Email opt-out rate
• # diggs • # of Email subscribers
• # of Blog Mentions • # of SMS subscribers
• # of Forum mentions • Clicks/ CTR
• # of Facebook mentions • Impressions
• # of Twitter mentions • Traffic
• # @mentions • Reach
• # of reviews mentions • Registration
• # of comments • Opt-in
• Positive : Negative Mentions for any channel • Page views
• # Twitter followers • Visit/session length (% site visits > 60 secs)
• Twitter Follower-Rate • Click path analysis
• # reviews • Eye tracking studies
• # stars in reviews • #/% Downloads
• Thread size • Changes in SERP results/ rankings
• Unique contributors • Earned/ Owned traffic
• Unique commenters • Inbound links

17. Paid/ Earned/ Owned
17

18. Assembling Metrics into KPIs
Measurement Attention Engagement Authority Influence Sentiment
• Unique Visits
• Total Interactions • Total “Likes” • On-Message
Chris’ Slide • Impressions • External Links to
• Fan • Subscribed “Likes” • Positive/Negative/
Facebook • Page Views Content &
Photos/Videos • Audience Profile as Neutral
• Media Discussion
• Post Quality Reflection of Target • Change Over Time
Consumption
• Retweets • Extended Network/ • On-Message
• Inbound Links
• Direct Messages Influence of Followers • Positive/Negative/
Twitter • Total Followers • External
• @Replies • Follower Profile as Neutral
Coverage
• Shared Content Reflection of Target • Change Over Time
• Likes/Dislikes • Inbound Links • On-Message
• Subscribers
• Views • Positive/Negative/
YouTube • Comments • External • Demographic Insights
• Subscribers • Audience Profile
Neutral
• FavoritesdReplies Coverage • Change Over Time
• Inbound Links • On-Message
• # of Comments
Blogger • Subscribers • Audience Profile as • Positive/Negative/
• Share of Voice Relativeto
Engagement • External Reflection of Target Neutral
Audience Size
Coverage • Change Over Time
• # of Check-ins
• Positive/Negative/
Foursquare/ • # of Unique • # of Repeat broadcast to • Audience Profile as
Neutral Commentary
Geolocation Visitor Check-ins Check-Ins Twitter or Reflection of Target
w/Check-ins
Facebook
• # Page Views
• Traffic to Site (Overall) • Profile of Visitors as • Most Popular Search
Search • Inbound links
• Unique Visitors • # Page Views/User Reflection of Target Terms
• Time Spent on Site
• Total Ongoing Engaged
• Total Trackbacks • Overall Sentiment
• Total Media Subscribers to
Overall • Total Interactions & Coverage of • Total Shift in
Consumption Content/Community
Activities Sentiment
• Community Crossover

19. EXAMPLE: CREATING A MEASUREMENT PROGRAM
TRACKING PERFORMANCE AGAINST OBJECTIVES
OUTCOMES AND PERFORMANCE
ENGAGEMENT IMPACT How a communications program or campaign
How a communications program or campaign impacts changes the behavior of the target audience or
attitudes and opinions within the target audience. We impacts real world events.
measure not only who the program is reaching but what
DAILY MONITORING is said and when it occurs. This is where we measure
Changed Behavior, Brand
The measureable results of the success of our engagement. FOCUS
Perception and Awareness
core Digital tactics.
Engagement, Reach and Perception Analysis Tools,
FOCUS TOOLS
Insights Surveys, Web Analytics
Daily Content and - Consideration, Preference
FOCUS Social Monitoring Tools, Social
Community Management TOOLS and Purchase Intent
CRM, Web Analytics
- Increase in Share of Voice
Social Monitoring Tools, -Engagement Insights and - Information Request and
TOOLS Analysis EXAMPLES Lead Gen
Social CRM tools
- Community Growth - Campaign Objectives and
- Share of Voice v Competition KPI Tracker
- Actionable Insights
EXAMPLES - Recommendations - Brand Perception Analysis
- Trending Topics and
- Favorable media coverage - Message Penetration
Conversation Tone
EXAMPLES -Favorable social media
-Blog and Influencer Monthly Reports
discussion
Mentions - All up Summary of
- Sentiment and Tone
- User Generated Content engagement performance
Weekly Reports and conversation insights
Daily Reports - Summary and Analysis of - Long term strategy
- Brand and Industry Buzz Weekly Conversation development based on
- Brand Protection and -Engagement insights, success
DELIVERABLE DELIVERABLE insights
Crisis Alerts and recommendations - Performance analysis
DELIVERABLE -Community Management - Community and Audience against key business
and Engagement Growth objectives
Opportunities -KPI Tracker - Web Analytics and
- Influential Voice
Campaign Report
Identification 19
-KPI Tracker

20. EXAMPLE: REPORTING AND SOCIALIZATION
MEASURING ACTIVITIES AND RESULTS AGAINST PROGRAM OBJECTIVES AND BENCHMARKS
Daily Monitoring Weekly Engagement Monthly Performance
Impact Analysis
20

21. 3. Demos
21

22. Shareaholic - http://www.shareaholic.com/siteinfo/usatoday.com
• View the sharing stats
of any sites shared
through the Shareaholic
browser extension
• Pages are accessible at
http://www.shareaholic.com/siteinfo/sitename.com

23. Bit.ly
• Bit.ly, and other URL
truncation services,
provide a layer of
analytics that can
extend your tracking
capabilities to any
destination that allows
clickable links.
• The analytics it provides
behind each link
breakdown the number
of clicks on your link
and other truncated
links to the same site,
as well as referral and
geographical data.

24. Export.ly for Facebook
• Facebook analytics tools focus on the composition and
size of the advertising audience, not the interactions they
have with the content itself
• It can be very difficult even to see the user generated
content on a Facebook page via the web interface
• In order to see and analyze social media content on a
Facebook page, you can use Export.ly

25. Facebook Insights
• Facebook Insights
provides a top
down perspective
on who comprises
your audience and
what they do on
your Facebook
Page.
25

26. Facebook Insights for Websites
• You can include a tag on
your site which will allow
you to measure the
impact that Facebook
Likes/ Share have on you
site traffic. This is a
brand new product from
Facebook (last week)
26

27. RowFeeder for Twitter
• Less than 18 months ago Rackspace received <500 Twitter mentions/month
• Today Rackspace receives >15K Twitter mentions/ month
• To deal with this volume we’ve begun aggregating this data using Rowfeeder

28. Chartbeat: Simple Server Side Analytics Via Tagging
• Chartbeat provides an
excellent way to
visualize the
correlations between
content publishing and
real time site traffic
• Simple for marketers
to use: put a (really
light) tag on your site
and Chartbeat’s server
side analytics will
analyze the data for
you
• For this demo, we are
using a WordPress
plugin on
Scobleizer.com

29. PostRank for Publisher Insights
• PostRank enables you to correlate site activities and
social media reactions from non-Facebook channels

30. Lithium SMM (Scout Labs) for Social Listening
• Lithium SMM (Scout Labs) will let
you set up a crawl for any eligible
Facebook and give you a 30-45 day
back crawl for wall post data
• Easy, intuitive interface
• Automated sentiment and quotes
extraction
30

31. The VI Analyze tab allows you to analyze
trending conversation across multiple media
types, time periods, across competitors, and
across different geographic regions

32. The VI Dashboard allows you to configure customize
reports that you can then pin to your custom
brand/product dashboard

33. The VI Monitor tab allows you to run ad hoc reports that
display results as a list, by volume by media type, by
sentiment, authors and sites, and also within specific
geographies or time periods

34. Crimson Hexagon for Social Analytics
iPhone on Verizon: Key Themes
Crimson Hexagon’s proprietary
algorithm separates relevant from
irrelevant content and measures
user-defined themes in online
conversation.
34

35. 5. Social Media Reporting
35

36. March 10, 2011
PRESENTED BY EDELMAN

37. INSIGHTS INSIGHTS

38. INSIGHTS

39. FACEBOOK CONTENT POPULARITY INSIGHTS
COMMENTS AND LIKES ON CONTENT POSTED BY BRAND – SEGMENTED BY TYPE
ENGAGEMENT BY ADMIN POST TYPE (AVERAGES) Likes/Post
Comments/Post
1400
1200
1000
800
600
400
200
0
Link Text Video
INSIGHTS AND RECOMMENDATIONS:
The ―I choose to drive a this car because …‖ post drove a huge spike in engagement
with the Facebook community , generating over 1,800 comments and 1,200 likes. The videos are generating a large volume of
likes,
but giving users a reason to comment could also be advantageous and generate attention from outside the community, growing the
fan base. We also recommend posting more photos to the page as those tend to generate high engagement rates. There were no
photos posted in this time period.
Source: Export.ly

40. CONTENT POPULARITY BY AUTOMOBILE LINE INSIGHTS
BREAKDOWN OF COMMENTS AND LIKES ON CONTENT POSTED BY BRAND
Average # of Likes
Model 8 Average # of Comments
Model 7
Model 6
Model 5
Model 4
Model 3
Model 2
Model 1
0 500 1000 1500 2000 2500
INSIGHTS AND RECOMMENDATIONS:
There was very high engagement with the test run video posted in February. The Model 4 which were driven by the television
commercial support which generated a high volume of ―Likes‖ but didn’t see the same spike in comments. We want to focus on
keeping the likes up, but bringing the ratio of Comments to Likes closer to that seen with the Model 3 which experienced a ratio
of 3.4 to 1, Likes to Comments.
Open ended posts such as this one from February asking fans why they choose to drive a particular car will generate high
response and also bring the ratio closer together
Source: Export.ly

41. FAN WALL POSTS VS. ADMIN WALL POSTS INSIGHTS
SIDE BY SIDE COMPARISON BY HOUR AND DAY OF WEEK
DAYS OF WEEK TIME OF DAY Fan Posts
90 Admin Posts
78 76
80 74 76 80
69
70 66
70 62
60 55 60
51 46
50
47 45 50
40 40
27 26
30 30 22
20 20 10
6
10 1
4 6
3 3 2 10 0 0 2 0 1 0
0
0 0
12am - 3am - 6am - 9am - 12pm - 3pm - 6pm - 9pm -
3am 6am 9am 12pm 3pm 6pm 9pm 12am
INSIGHTS AND RECOMMENDATIONS:
• The Facebook fans are posting on the wall every day of the • Make sure to engage earlier and continue engaging by giving the
week, including Friday through Sunday which makes up 35% of community content after work hours.
the content posted. The brand engagement is heavily weighted
on week day posts, with 85% of posts occurring Monday through • On the next slide we’ll take an even deeper dive, looking
Thursday. Extend engagement to all days of the week. at fan engagement by hour of day, specific to each day
of the week.
• The fans also engage at all hours of the day, but heavy
engagement starts around 7am PST and continues late into the • Analysis includes 410 posts to the wall by fans, and 19 posts by
evening. The brand is posting from 7am to 2pm and the brand
stopping, but the fans continue to post with 20% of posts to the
wall occurring between 5pm-10pm PST.
Source: Export.ly

42. FAN POSTS BY HOUR AND DAY OF WEEK INSIGHTS
DAY OF WEEK BREAKDOWN BY HOUR
INSIGHTS AND RECOMMENDATIONS:
SUNDAY: Heavy engagement in the evenings, with 62% of Tues - Thurs: Engagement occurs during peak work
posts coming after 3pm PST hours, again starting at 7am PST but slowing at 4pm PST
Monday: Fans post bright and early when they get into the Friday: Posts spike mid-day, but continue to occur in the
office. Engagement spikes at 7am PST, and slows evening at a higher rate than Monday through Thursday
consistently throughout the day
Saturday: Continual posts throughout the day, with peaks
in the morning and late evenings
Source: Export.ly

43. COMMENTS ON WALL POSTS INSIGHTS
HOURLY AND DAY OF WEEK ANALYSIS
DAYS OF WEEK TIME OF DAY Links Text
Photos Video
1200
1061
1800 1708
1000
1600
1400 800 710
1200
1000 600
800
400 312
600
366 214 223
175
400 286
226 239 200 158 140 157
130 128 126
208 206
128 132
200 96
35 36 6 11 0 34 2
42
13 21 3 37 10
56 51 57 35 22 7 13
1 22 2 3 23 17 21 11 7 14 5 9 3 7 7 7 7 4
0 0
12am - 3am - 6am - 9am - 12pm - 3pm - 6pm - 9pm -
3am 6am 9am 12pm 3pm 6pm 9pm 12am
INSIGHTS AND RECOMMENDATIONS:
This analysis includes comments in response to the posts
on the fan wall from both the Page Admin and the fans. Although The large spike seen in the 12-3pm hour, and on Wednesday was
98.8% of comments were in response to posts by the Admin. caused by the response to the post asking fans why they drive a
specific car.
The day of week and time of day analysis was largely driven by
when the brand is posting on the page. For example, updates that We recommend posting similar types of content at different times of
contained a video were always posted on a Monday or the day and different days of the week so that we can better
Tuesday, thus 90% of comments in response to video posts came understand when these posts get the highest engagement. This will
on Mondays or Tuesdays. help inform the engagement strategy going forward
Source: Export.ly

44. INSIGHTS

45. @AUTOMAKER
6 MONTH FOLLOWER GROWTH INSIGHTS
@AutoMaker Twitter Followers
13,477
11,720
10,295
9,317
8,545 15%
7,843
7,035 growth
14%
10.5% growth
9.0% 9.0% growth
11.5%
growth growth
growth
September October November December January February March
INSIGHTS AND RECOMMENDATIONS:
The @AutoMaker Twitter profile has grown the follower base by 92% in the past 6 months. Looking back to September, there
has been a average month over month growth rate of nearly 12%. A spike in growth has recently occurred during the months of
January and February, where fan growth rose at 14 & 15 percent respectively. Follower growth in January and February
was up 82 percent (combined 3,182 new followers) when compared to growth in November and December, which had only
1,750 new followers.
Source:
TwitterCounter

46. @AUTOMAKER TWITTER CHANNEL
OUTBOUND TWEET VOLUME INSIGHTS
Tweets
@AutoMaker Tweet Volume
Replies
200
Retweets
180
160
140
120 126
119
100 96
103
80
60
58 60 7
12
40 26
20 29 47 39
18 18 28
0 6 3 2
September October November December January February
INSIGHTS AND RECOMMENDATIONS:
Consistent with follower growth, the @AutoMaker profile has seen an increase in outbound Twitter activity in the past 3 months
(includes all regular tweets, @replies and retweets). During the months of December – February, outbound Twitter volume
increased 68 percent, and more importantly, engagement with other Twitter profiles increased 109% which contributed to
the large fan growth during that time period. @Replies volume dipped a little, so we recommend continuing to @Reply with
other profiles which will help increase the influence score of the Twitter handle as calculated by tools such as Twitalyzer, Klout
and TweetLevel, along with building the follower base. In addition, continue to retweet positive conversations about Brand - for
example when people post that they ―Love the brand, or ―considering a purchase‖ or even just entertaining tweets such as this
one This has been effective in building the follower base
Source: TweetStats

47. FEBRUARY TWITTER REPORT
TWEETS, RETWEETS, @REPLIES BY DAY INSIGHTS
February Tweet Timeline
Retweets Replies Tweets
14
12
10 7
7
8 6
6
5 7
6 0 6
5
0 4 4 4
5
4 2 4 4
5
0 4 2 6 4 0 0 0
5 3 3 3
2 0 0 0
3 3 3 3 3 3 3 3
2 0 0 2 0 2 0 2
1 1 1 1 1 1
0 0 0 0 0 0 0 0 0 0 0 0 0
INSIGHTS AND RECOMMENDATIONS:
During the month of February, the @AutoMaker Twitter handle had a total of 96 tweets with an average 3.4 tweets per day.
Source: TweetStats

48. FEBRUARY TWITTER REPORT
OUTBOUND ENGAGEMENT VS. ALL CONVERSATION ANALYSIS INSIGHTS
Outbound Hourly Tweets Total Distribution of
30 @AutoMaker Conversation
25 24
23
20 30%
25%
17 25% 21%
19%
20%
15
15% 10%
7% 9%
10% 6%
10 4%
5%
6 6 0%
5
4
9AM to Noon
3PM to 6PM
6PM to 9PM
Noon to 3PM
3AM to 6AM
6AM to 9AM
12AM to 3AM
9PM to 12AM
5 3
2 2 2
1 1
0 0 0 0 0 0 0 0 0 0 0
0
INSIGHTS AND RECOMMENDATIONS:
The most concentrated efforts for outbound Twitter volume occurred between the hours of 3:00 P.M. and 6:00 P.M. PST, with
67% of the outbound tweets occurring at this time. And when looking at the overall conversation volume on Twitter mentioning
@automaker (chart on right), you see that 65 percent of the conversation is happening between 9 A.M – 6 P.M. It is
recommended that the @automaker Twitter profile engage with users earlier in the day, as conversation seems to be peak by 3
P.M., which is the time the @automaker profile just be begins to engage.
Source: RowFeeder and TweetStats

49. FEBRUARY TWITTER REPORT
– POSTS AND IMPRESSIONS (SAMPLE) INSIGHTS
Twitter Posts & Potential Impressions
Total Posts Potential Impressions
50 47 90,000
45 80,000
77,729
40 70,000
35 33 32 63,413 60,000
30 53,726 26 50,000
25 47,577
40,000
20
14 30,000
15 25,712 10
10 20,000
5 2,368 10,000
- -
3/2/11
3/3/11
3/4/11
3/5/11
3/6/11
3/7/11
INSIGHTS :
Between March 2, 2011 & March 7, 2011, there was a total of 162 total tweets with a reach of 270,525 impressions.
Note the large spike in impressions on 3/7/11. This was caused by the tweet by a specific influential blog tweeting about the line
of autos
Source: RowFeeder

50. MOST ACTIVE & FOLLOWED ACCOUNTS
MENTIONING @AUTOMAKER INSIGHTS
Most Active Users Most Followed Users
5 List 69,514
List
4 14,863
removed removed
4 13,752
for for
3 12,504
privacy privacy
3 10,974
3 7,544
2 6,537
2 6,448
2 5,547
2 4,760
2 4,467
2 3,173
2 3,031
2 2,836
2 1,634
2 1,347
2 1,323
1 1,222
1 1,155
1 1,115
1 1,084
1 1,055
1 986
1 576
1 565
Updates/Person 0 2 4 6 Number of Followers
- 20,000 40,000 60,000 80,000
Source: RowFeeder

51. TOP CONVERSATION DRIVERS ON TWITTER
(SAMPLE TIME PERIOD 3/2/11 – 3/7/11 ) INSIGHTS
INSIGHTS AND
RECOMMENDATIONS:
Total Posts & Conversation Drivers
Day of Week
Between March 2 –
March 7, 2011, a total admired companies car jetta #vw campaign 2011
of 162 mentions. The
chart at right provides a
breakdown of common
terms and phrases used
in these tweets 10
8
6
4
2
- Time of Day
3/2/11
3/3/11
3/4/11
3/5/11
3/6/11
3/7/11
Admired
Top Keywords Car Model X #auto Campaign 2011
Companies
Mentions 10 20 15 12 11 12
% of Total
6% 12% 9% 7% 7% 7%
Volume
Source: RowFeeder

52. FEBRUARY EDITORIAL ANALYSIS
TOP MENTIONED KEYWORDS THAT INCLUDED THE @AUTOMAKER PROFILE INSIGHTS
Keyword @Automaker Usage Mentions Impression Reach Top Influencers
@stevewhiteBrand
Keyword 1 39 169 123,684
(1,985 followers)
@kelseySchnell
Keyword 2 10 27 2,883
(175 followers)
@kellybluebook
Keyword 3 5 55 35,026
(6,434 followers)
@alovey
Keyword 4 1 10 41,802
(168 followers)
@m80parents
Keyword 5 4 18 9,888
(3,670 followers)
@grantimahara
Keyword 6 1 429 875,592
(238,846 followers)
@idiotsguides
Keyword 7 1 88 20,746
(1,433 followers)
INSIGHTS :
During the month of February, the above hashtags & keywords were the most used in all outbound tweets:
• #AutoMaker– had the highest usage at 39 times, yet only received 169 mentions with just 123,684 impressions
• #AutoModel– was just used once, but had the highest impression reach at 876,000
• This was due to the nature of the content and popularity of the Television Commercial that supported and a number of
influential people responding or retweeting the content
• The misspelled hashtag, – only had 88 mentions and an impression reach of just 21,0000
Source: TweetStats and
Sysomos

54. SHARE OF VOICE INSIGHTS
TOTAL MENTIONS OF AUTO MAKER WITHIN SOCIAL MEDIA (30 DAY SAMPLE)
INSIGHTS AND
RECOMMENDATIONS:
Day of Week
Between February 4 – March
6, there were 826,468 total
mentions of Auto Maker.
Over 75% of mentions
occurred on Twitter or on
Blogs
Time of Day
*Sample data pull of all Twitter conversation mentioning @Automaker from 3/2 -
3/7
Source: Radian6

55. SHARE OF VOICE INSIGHTS
TOTAL MENTIONS OF AUTOMAKER WITHIN SOCIAL MEDIA (30 DAY SAMPLE)
Day of Week
Conversation peaks on
Twitter with 37,389 total
mentions
Mentions on Twitter top
out at 11,554 with the
unveiling of a new model
Time of Day
*Sample data pull of all Twitter conversation mentioning @Automaker from 3/2 -
3/7
Source: Radian6

57. SHARE OF VOICE INSIGHTS – MODEL CONVERSATION
TOTAL MENTIONS OF AUTOMAKER & ECO FRIENDLY WITHIN SOCIAL MEDIA
INSIGHTS :
Day of Week
Between February 4 – March
6, there were 58,387 total
mentions of specific
models, about 7 percent of
the overall Automaker
conversation
A much larger percent of
mentions are occurring on
Blogs as it relates to
Diesel, with 64% of posts
happening on blogs
Time of Day
*Sample data pull of all Twitter conversation mentioning @Automaker from 3/2 -
3/7
Source: Radian6

58. MODELS SHARE OF VOICE INSIGHTS
30 DAY POPULARITY CHART (FEBRUARY 4 – MARCH 6, 2011)
Day of Week
124,581 blogs posts, with major
content topics being:
•Commercial buzz
•2011 Chicago Auto Show
Time of Day
*Sample data pull of all Twitter conversation mentioning @Automaker from 3/2 -
3/7
Source: Radian6

60. COMPETITORS
30 DAY SHARE OF VOICE (FEBRUARY 4 – MARCH 6, 2011)
Day of Week
Brand Y
20%
AutoMaker
47%
Brand X
Brand W
14%
Time of Day
DIESEL SOV - AUTOMAKER *Sample data pull of all Twitter conversation mentioning @Automaker from 3/2 -
& COMPETITORS
3/7
Top Keywords Automaker Brand X Brand Y Brand Z
Mentions 58,387 17,380 23,581 24,679
% of Total Volume 47% 14% 19% 20%
Source: Radian6

61. AUTOMAKER - SEARCH
UNIQUE VISITORS (JANUARY 2009 – JANUARY 2011)
Day of Week
Time of Day
INSIGHTS :
*Sample data pull of all Twitter conversation mentioning @Automaker from 3/2 -
3/7
The Automaker site traffic over the past two years has had an interesting history, between January 2009 – August 2009, unique
visitors average nearly 811, 975 unique visits a month. But over the next year, the site traffic dropped dramatically , averaging
only 662,780 unique visits a month. The site bottomed out completely in September 2010 when it recorded only 535,000
unique visits, lowest in two years. After this point, the site seemed to gain better traction and improved greatly, with its highest
peak in two years with 912,000 unique visits recorded in January of 2011.
Source: Compete.com

62. TOP REFERRAL SITES
JANUARY 2011 TRAFFIC SUMMARY
Percentage of Overall
Source Referring Volume
Traffic
Direct Traffic 103,608 8.69%
Google 314,306 26.35%
Yahoo 166,070 13.92%
Facebook 49,272 4.13%
MSN 28,770 2.41%
Bing 24,943 2.09%
Ask.com 24,688 2.07%
Autotrader 15,370 1.29%
AOL 10,274 0.86%
YouTube 9,052 0.76%
TimeeBayDay
of 6,396 0.54%
INSIGHTS : Webcrawler 6,376 0.53%
*Sample data pull of all Twitter conversation mentioning @Automaker from 3/2 -
3/7
Edmunds 5,852 0.49%
The traffic summary for January 2011
had nearly 1.2 million site visits, with Honda.com 5,767 0.48%
nearly 8 percent of the traffic coming
from direct sources to Brand.com, and Cars.com 4,636 0.39%
the remaining 92 percent coming from Toyota.com 4,459 0.37%
referral traffic sources
Audiusa.com 4,445 0.37%
CNN.com 4,342 0.36%
Source: Compete.com

63. TOP REFERRALS
PAID VS. NATURAL SEARCH TRAFFIC (JANUARY 2009 – JANUARY 2011)
Day of Week
Time of Day
*Sample data pull of all Twitter conversation mentioning @Automaker from 3/2 -
3/7
INSIGHTS :
In January 2011, there were a total of 338,672 Search Referrals (Google, Yahoo!, Bing) and 35,970 Paid Search Referrals
Source: Compete.com

64. TOP REFERRAL KEYWORDS
NATURAL VS. PAID SEARCH KEYWORDS (JANUARY 2009 – JANUARY 2011)
Top Organic Keywords Search Referral Share Top Paid Keywords Search Referral Share
keyword 1 2.04% keyword 1 16.57%
keyword 2 1.8% keyword 2 10.23%
keyword 3 1.75% keyword 3 4.08%
keyword 4 1.75% keyword 4 2.04%
keyword 5 .88% keyword 5 1.80%
keyword 6 .83% keyword 6 1.75%
keyword 7 .71% keyword 7 1.58%
keyword 8 .46% keyword 8 1.23%
keyword 9 .43% keyword 9 0.92%
keyword 10 .43% keyword 10 0.88%
keyword 11 .37% keyword 11 0.83%
keyword 12 .29% Time of Day keyword 12 0.71%
keyword 13 .29% keyword 13 0.70%
keyword 14 .25% 0.65%
*Sample data14 of all Twitter conversation mentioning @Automaker from 3/2 -
keyword pull
3/7
keyword 15 .22 keyword 15 0.60%
keyword 16 .19% keyword 16 0.50%
keyword 17 .18% keyword 17 0.46%
keyword 18 .17% keyword 18 0.43%
keyword 19 .17% keyword 19 0.43%
Keyword 20 .16% keyword 20 0.40%
Source: Compete.com

65. THANK YOU
Copyright ©2011 Daniel J. Edelman, Inc. All rights reserved.
All information contained herein is confidential and proprietary to Daniel J. Edelman, Inc. (―Edelman‖).

66. 6. Shaky Metrics
66

67. What is Sentiment?
• From PR: A judgment about whether an author or document
expresses a positive opinion about a person, place or thing.
Sometimes called tone or opinion.
• Usually expressed as positive, negative, or neutral
• Sometimes expressed with polarity (strongly positive, strongly
negative)

68. Challenges in Sentiment
Implication vs. Information
• ―Today Morgan Stanley upgraded GM from a sell to a hold.‖
• ―An earthquake of magnitude 8.9 has struck Japan off the island of Honshu.‖
Interpretation & Irony
• ―The average creationist exhibits all the intellectual rigor as a modern day
Neanderthal.‖
• ―Microsoft is about as cool as Austin in August.‖
Interpretation/Context
• MUST WATCH: http://bit.ly/9nOU7 ROTFL #charliesheen #winning
• ―I totally love Chris. I would kill myself kill myself if he left me for another
man.‖
• ―Just read the book.‖
• ―I love Hulu. I just wish they didn’t have so many ads.‖

69. More Challenges in Sentiment
Entity Clarification
• ―I love Coke Zero, even though I hate Coca-Cola.‖
Relevance
• ―sitting on the couch with Bruce watching burlesque on netflix‖
• ―This is amazing coke.‖
• ―ZICOZICOZICO!!!!!!!!!!‖
• ―I <3 Beeeeeiiiiiibbbbeeeerrrr!!!!!!!!!!!!!!!!!!!!!‖
• ―OMG you gotta watch this http://awe.sm/O7gb6T
Slang
• ―Totally digging Netflix streaming‖
• ―I <3 Beeeeeiiiiiibbbbeeeerrrr!!!!!!!!!!!!!!!!!!!!!‖

70. Sentiment: Understand Error Tolerance vs. Level of Effort
Rate of Human Agreement on Sentiment: 80-95%
• <80%: Mechanical Turk
• 85%: College educated, same set of guidelines
• 90%: PR companies using same set of guidelines
• 95%: KD Payne & her crew
Factors in Machine Learned Agreement with Humans
• Cleanliness of content (POS, grammar, punctuation)
• Completeness of vocabulary (Taboo)
• Ability to look beyond the text words (punctuation, URLs)
• Sophistication of the formula used (documents vs. statements)
• Interpretation vs. information (Index Falling)

71. Sentiment Can Vary By Channel
71

72. Sentiment Analysis: Not Just Positive/ Negative/ Neutral

73. Partial Twitter is Good for Trend
73

74. But You Need To Know What You Don’t Have
Twitter clients that use the search/track APIs don’t necessarily give you the full
stream
• Depends on popularity of term and frequency of polling
• Rate limits from Twitter per vendor/ Distribution of polling across applications
• Sometimes, Twitter clients don’t even have full @ data (though DMs mostly
seem to arrive)
• Search criteria are limited in length (140 characters) and functionality
(embedded logic) or other issues (Ke$ha; language classification)

75. Twitter Partnership with Gnip
Twitter has made full firehose data available by keyword search through
GNIP. Approximate costs:
• Volume or coverage based
• URL expansion
• $2K/ month for a box
• $0.1/ 1000 tweet ($1K/ 10K Tweets)
• API from which to pull data
• Contact @robjohnson for more information

76. 7. A Number is Not a Decision
76

77. Social Intelligence…
…the management
and analysis of
customer data from
social sources, used
to activate and
recalibrate marketing
and business
programs.
Source: Forrester Report
―Defining Social Intelligence‖
77

78. Metrics Cannot Make Decisions
What strategic actions can result from knowing…
• Added 200 Facebook fans this month
• Positive sentiment decreased by 5% this quarter
• Twice as many Twitter mentions this week
78

79. 79

80. Go Beyond Metrics to Social Intelligence
How are consumers reacting to the Verizon iPhone?
300,000 mentions of iPhone & Verizon
50% Off-Topic
27% - Phone Feedback
19% - Pro Verizon
14% - Pro AT&T
50% On-Topic
% relevant conversation 1/11/11 – 1/17/11
80

81. Case Study: Major Insurer – Social Media Analysis of
Advertising Effectiveness
Overview: Insurer has spent millions
running national ad campaigns and
needed to understand effectiveness Key Findings / Insights
of messages and drivers of
consumer purchase intent.
Both Insurer’s and Competitor’s
campaigns generate healthy “buzz”, but
Using Crimson Hexagon, Insurer opinions indicate that positive sentiment
analyzed the nature of online doesn’t reflect intent to purchase
conversations about its own and a insurance based on campaign
key competitor’s ad campaigns: • The Insurer’s ad campaign is better
 What topics dominate the online received but does not generate
conversation related to Insurer? conversation related to buying or
 Is the ad campaign driving intent to switching insurers
purchase? • The Competitor’s ad campaign, while
 How does competitor stack up in more divisive, spurs a conversation
similar analysis? trend related to intent to purchase
 What’s missing from current
campaign messaging?
81

82. Insurer Ad Effectiveness Analysis
Data reveals “Insurer’s‖ ad campaign is
liked but didn’t generate conversation about
buying or switching insurers
―Competitor‖ ad campaign, is more
divisive, but spurs a conversation trend
related to purchasing
82

83. Case Study: Medical Device for Diabetes & Insulin
Overview: Customer planned to Key Findings & Recommendations
introduce a new Insulin delivery device.
Majority of conversation intertwines emotions with
How can the online conversation inform experiential factors
and improve the product marketing and • Impacts of diabetes and insulin usage are both
launch messaging? medical and lifestyle related
Insulin itself is often the issue
Using Crimson Hexagon, the • Over one-quarter of the discussion shows
customer analyzed the nature of online concerns about having diabetes which requires
using insulin or about the efficacy of insulin itself
conversation about diabetes and Addressing convenience factors presents a big
insulin, specifically: opportunity
• 24% of all conversation (and over 40% of
 How do patients discuss the frustrations voiced) focus on either the lifestyle
complexities of treatment and complexities or problems with delivery devices
control? (primarily needles)
Opportunity for brands to get more engaged and
 What core messages will resonate become trusted-partner
most with these consumers? • Consumers are looking for advice,
recommendations, shared-support within the
 What is the significance for new online community
product launches?
83

84. Medical Device Consumers’ Concerns Presented
Opportunity to Provide Lifestyle, Community & Support
Lifestyle and personal
experiential factors jump
out as leading categories
of opinion. Comment on
the actual devices is low.
84

85. 8. Integrated Program Design
85

86. Why Care about Metrics?
To understand if the activities
you undertake help you to
achieve a goal or purpose.

87. A Tale of Two Facebooks
87

88. Finding 1: Improved Visit Loyalty
Paid Search
Natural Search
Referring Sites
Twitter
E-mail
Facebook
0 0.5 1 1.5 2 2.5 3 3.5 4
Visit Loyalty — how may repeat visits are generated in the following 30 days?
Source: Rob Brosnan, Seton Hall University

89. Finding 2: Improved Conversion Efficiency
Facebook
Marketing Programs
Natural Search
Referring Sites
Direct Load
0 0.5 1 1.5 2 2.5 3
Conversion Efficiency — how visits are converting visits?
Source: Rob Brosnan, Seton Hall University

90. Finding 3: Facebook Delivers Local Visitors
Source: Rob Brosnan, Seton Hall University

91. Thank you.
We’ll see you at the closing parties!
@blake
@clightner
@setlinger
@margaretfrancis
@megcos