The document summarizes how social media analytics can help various organizations understand customer sentiment and behavior. It provides hypothetical scenarios where social media analytics could help a TV network understand how Twitter impacts viewership, a computer manufacturer analyze brand perception, and a consumer brand identify which messages from an ad campaign resonated best. It concludes by suggesting social media analytics can help a global company ensure employee safety when traveling.

1. The Cutting Edge of:
Customer Intelligence
Presented by David Snyder
President
Snyder, INC.
dsnyder@mindread.net

2. Social Media Helps Customers Bridge Social & Business Metrics
Internal
The Business
Business
Social Web Metrics
Data
2

3. Social Media Analytics Enables and Supports the Combination of Multiple Data Sets
Internal and External, Social and Non-Social
The Social Web Who?
Influence Metrics
Keywords, Phrases, Trends
across Social, Web,
& News
Impact
How? Which data
Sliding Sentiment
Scale, Cumulative
affects
Sentiment, Running Business
Average, and
More… metrics
Correlative Analysis
Pattern Matching
Semantic Context
What?
How much?
Volume, Influence,
Pattern Recognition
and Trend Analysis
3

4. A Simple Case of Social Media Analytics
What if You were a Major Network and…..
….you wanted to understand the Impact of Twitter
on TV Viewership of one of your TV shows?
4

5. Social Media Analytics Would Respond: “276”…
Mentions until show starts vs.
Nielsen data
900
800
700
Nielsen Data
600
500 Blue line
400 represents
300 social media
200 mentions
100
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Social Mentions vs. Nielsen Ratings Findings -
• When the daily total is greater than 276 That’s the Network’s Target
80% probability that Nielsen Rating exceeds 436k
• When the daily total is less than 276 Twitter Mentions for that
70% probability that Nielsen Rating falls below 436K
specific show
5

6. …….Because That’s When Twitter is Worth Money to the Network
Analysts found that the correlation exists
and determined the break-even points of
Nielsen Ratings and Twitter Mentions
Avg Nielsen Ratings 436,000 = Avg Nielsen Ratings over 30 Days from 12:30am-1:00am
(000’s) Avg Social Mentions
276 = Avg mentions over 30 days from 3am till 12:30am (22.5 hours)
0-150
125 238.3333333
151-300
235.25 249.5
Network X has an Opportunity to increase target show viewership
301-450 (and increase ratings to increase ad rates and make more money).
398.8 153.2
451-600
Network X can/should focus efforts on FINDING CAUSATION -
516 327.8888889
601-750 What gets people talking about that show?
734 313
751-900
796.3333333 588.6666667 It’s worth their investment
6

7. What if………
You were a Major Computer Manufacturer
and you wanted to know some things about
your Brand….
Things like….
• What are people saying about me?
• How am I perceived in the Marketplace?
7

8. Social Media Analytics would say “Your Customers Love You”….
Weekly Sentiment Breakdown ….The few that actually talk about you
Share of Voice by Brand
Cumulative Sentiment by Brand
Higher
cumulative
Sentiment
than Apple
8

9. ….Nice to Know, But How do I CHANGE That?….
Company’s current Messaging is missing the Mark by 15X……
15x 15x
Lenovo Tablet is 15x more Apple conversations
likely to be associated with associated with “Apps” and
their Laptops and enhanced user features
Notebooks than Dell or than Dell or Lenovo
Apple
Stop talking about “productivity” and Take a Bite of the Apple…….Start talking
about what you can DO with your products…..not the products themselves
Emphasize Lifestyle, Portability, Simplicity
Encourage Announce new Lenovo is a
customers to post Apps and Games “Benchmark” Brand.
pictures & stories with links to stores High Quality, High
of them with their for easy impulse Sentiment,
Lenovo Tablets on purchase frequently compared
the go
9

10. What if………
You were a Major Consumer Products Brand
and you wanted to know if your new Ad
Campaign for a product was having an impact….
Marketing Execs want to know….
• Are we increasing Brand Awareness?
• Which campaign words resonate with my customer?
10

11. …..Let’s Play…..”Spot the Ad Campaign”……
Data Point #1 –
Awareness of product spiked
during this campaign….so far,
so good.
Data Point #2 –
Positive perception of product increased
and negative perceptions decreased.
Good again.
Conclusion: We need to replicate and
build on this campaign.
11

12. ….Something Obviously Worked…..Specifically, what was it?
Word Association “Theme Analysis” shows the following detail…
12

13. …..What did I Learn?....
The Ad Campaign giving a free sample of our product
had the following benefits to Us:
• More tightly linked Craisins to the Ocean Spray Brand
• Doubled the mentions of using Craisins in Salads, with Cheese, in
White Chocolate Oatmeal Cookies, and recipes in general
• Increased comparisons to Raisins – with Craisins viewed favorably
• Increased perceptions and mentions of “Sweet” and “Fresh”
• The word “Lunch” appears for the first time – linking product to
likely time of day for consumption
Knowing this, I can replicate this campaign – and build on its success
13

14. What if….
You were a Global 250 firm, and were
sending your people all over the world on
Company Business…..
How do you help them stay safe?
14

15. ….State Department Publications won’t help….
Kidnappings are up in Kenya –
your people need to stay in
highly populated areas and
NEVER go out alone
Strikes and Civil Unrest are up in
Malaysia – your people need to
watch local newscasts
frequently for locations and
updates, take taxis and stay
close to the hotel
15

16. A few companies that have used social media analytics
16

17. So…..
What are YOUR “What Ifs”???
17

18. Contact:
For expert guidance in picking the right social media solutions and tools
David Snyder
dsnyder@mindread.net
(Member, American Advertising Federation)
18