volume 5 of the bazaarvoice conversation index

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I believe this is the most comprehensive analysis of Twitter's impact ever published. Terrific job by our team at Bazaarvoice on this.

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Page 1: Volume 5 of the Bazaarvoice Conversation Index

The Conversation Index

Volu

me

5

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The Conversation IndexVolume 5

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Get your digital copyTheConversationIndex.comTheConversationIndex.co.uk TheConversationIndex.de

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5

Table of ContentsWhat to expect ....................................................................................................................................... 6

What we’ve found ................................................................................................................................... 9

Stock prices move with Twitter mentions ..................................................................................................... 10

Twitter evolves from portal to destination .................................................................................................... 12

Brands get more tweets, but less of the conversation is about them ................................................................ 16

Search interest doesn’t correlate to Twitter mentions, stock performance, or TV & radio coverage ....................... 20

The bottom line? Social and “the real world” are becoming inextricable .......................................................... 24

The methodology behind The Conversation Index Volume 5 / Contributors ..................................................... 27

Contact us .............................................................................................................................................. 28

About Bazaarvoice .................................................................................................................................. 31

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What to expect We’re used to hearing social discussed as if it’s some kind of vast parallel universe, free of the cause and effect of “the real world.” This view gets at least one thing right: the social universe is vast, and like our physical universe, mostly unexplored. But where does social intersect with our everyday experiences, in life and in business? How do social and the real world affect and reflect one another on a larger scale? We’re starting to see patterns emerge that tell us that social refuses to contain itself; its effects are spilling into the real world nearly everywhere we look: in politics, innovation, education, and of course, business and the economy.

In this volume of The Conversation Index, we ride along the collision course of social data, traditional media, and business performance, with an emphasis on Twitter. With over half a billion active users, and an average of 340 million tweets per day, Twitter is like a social seismograph for the entire world. We worked with enterprise social data provider Gnip to acquire 26 million tweets for this analysis. Every tweet in this research mentioned at least one of 13 brands from the BrandZ™ Global 100 Brands list, including Adidas, Clinique, Colgate, Gillette, Hugo Boss, Nike, Pampers, Pepsi, Ralph Lauren, Samsung, Intel, Tesco, and Sony.

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We compare, contrast, and combine those 26 million tweets with over 8,000 TV and radio mentions, 17 months of stock price data, more than a year and a half of Google search interest data, and 270,000 pieces of consumer-generated content from online reviews—all for the same 13 brands.

This Index reveals some fascinating patterns and relationships at the intersections of all these data streams, as well as a few places where we found—counterintuitively—no correlations at all.

Social data offers a critical new stream of insights for brands and the industry. The social ecosystem is broad; conversations happen on brand sites and on social channels, across an ever-increasing set of devices. As social content and social data expands, so does the scope of our knowledge about how it both influences and mirrors activity across the digital and physical worlds. Sharing these insights with our clients and the industry is the driving force behind The Conversation Index. We’re excited to share this edition with you.

Erin Nelson (@erinclaire) Chief Marketing Officer, Bazaarvoice

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What we’ve foundHere’s what we uncovered:

• Twitter volume for brand mentions is highly correlated with stock price

• Twitter is becoming a destination, not just a portal

• Brand mentions in Twitter lag behind overall Twitter growth

• Search interest for brands doesn’t correlate to Twitter mentions, stock performance, or TV and radio coverage

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Stock prices move with Twitter mentionsIt is becoming clear that both quantitative and qualitative analysis of social data can be useful for establishing relationships and in predicting real-world events. Stock performance for the brands in this analysis increased and decreased in line with the fluctuating volume of tweets about these brands. This is a remarkably high positive correlation of .91, meaning that high Twitter volume tends to coincide with high closing price, and vice versa. The same things that make stocks move upward tend to make social chatter spike (such as well-received product announcements and high-profile executive hires). But there’s a piece of this finding that’s counterintuitive. Shouldn’t the same factors that send a stock downward (such as a lawsuit, product flop, or poor earnings call) be just as likely to trigger a bump in conversations about the brand? Apparently not. It seems that Twitter users buzz

more about brands as they perform well on the exchanges, but quiet down a bit as their stocks fall.

Other analyses have shown social data to reflect economic factors. Product reviews mention price more when consumer confidence is low (a -.66 correlation).1 In February 2009, when consumer confidence hit its lowest point, mentions of price hit their highest point, accounting for 11.5% of all US reviews. When we map these price references to the Dow Jones Industrial Average, an even stronger negative correlation (-.68) is revealed. Price mentions fall as the Dow average rises, and they rise as the Dow falls. And a 2010 study by academic researchers at Indiana University and University of Manchester found that measuring select dimensions of “Twitter mood” can be 86.7% accurate in “predicting the up and down changes in the closing values” of the Dow Jones Industrial Average.2 As more of these predictive relationships are discovered and subject to rigorous testing, social data will be incorporated into things like demand forecasting and product release timing.

1 The Conversation Index Volume 1. 2 http://www.relevantdata.com/pdfs/IUStudy.pdf

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2011 2012

AV

ER

AG

E B

RA

ND

ME

NT

ION

S ON

TW

ITT

ER

(in thousands)

AV

ER

AG

E C

LOSI

NG

PR

ICE

CLOSING PRICE CORRELATES TO TWITTER BRAND MENTIONS

JAN

60

50

70

80

90

100

10

20

30

40

110

120

130

140

150

160

170

180

190

200

60

50

70

80

90

100

10

20

30

40

110

120

130

140

150

160

170

180

190

200

FEB MAR APR MAY JUN JAN FEB MAR APR MAY JUNJUL AUG SEP OCT NOV DEC

121.1

45.8 44.751.0

62.468.1

62.2 60.9

68.273.4

80.874.8

88.4

99.7

107.1

124.5

133.7

144.8

154.3

125.6130.9 130.9 131.4 129.9 129.9

134.2 131.4 132.9 135.4 136.9142.6

155.5159.2

180.2173.7

156.6

stock performance and Twitter mentions.

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Twitter evolves from portal to destination

As Twitter grows, it is becoming a destination rather than a portal or midpoint. People are increasingly going to Twitter for the experience it delivers — conversation and timely information — not as an intermediate step between them and what they’re really after. And they’re staying longer. But Twitter is used much differently than other social and web channels, and its data should be used differently, too.

For example, we compared online search terms that include “Adidas” to mentions of “Adidas” on Twitter. Since search takes place when someone is looking for specific information, the terms that appear during a search vary greatly from other types of content. Top “Adidas” search terms tend to be at the level of product lines and categories, and of the top 20 searches, only three are for specific products. The top 20 search terms associated with “Adidas” also included the names of two competing brands, indicating that comparison shopping begins in the search box.

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THE CONVERSATION INDEX VOLUME 5

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Twitter users tend to reveal their personal interactions with or in relation to brands. When we dig into what people on Twitter are saying about Adidas, they mention what “new” Adidas products they’re wearing “today,” and use words such as “my” and “I.” Some of the top Twitter terms associated with Adidas reference specific campaigns, like the hashtag “#branch309adidasday.” Businesses interested in doing their own text analysis on tweets should think of it as a way to roughly gauge consumer response to news, events, campaigns, and as a method of identifying enthusiastic customer advocates. But they will have to develop repeatable methods of separating relevant, authentic tweets from the abundance of noise.

In contrast to search and Twitter language, reviews tend to focus on specific product qualities (“light,” “looks,” “fits,” “comfortable”), adjectives (“awesome,” “great,” “different,” “perfect”), and other expressions of sentiment (“love,” “disappointed,” “happy,” “recommend”). Since every single review is tied to a specific product, they are a rich social data source for product-level insights. In fact, 12% of all reviews

include product suggestions, and a fifth of all four-star reviews provide this type of feedback.3

Use search patterns to optimize your brand’s search

engine marketing and optimization strategies.

And use the words you find in tweets about your brand when you tweet about your brand. Optimize your marketing copy by using the language of your top reviewers—or better yet, quote them. When you reflect what consumers say online in your own social efforts, you’ll create content that’s more shareable. Quantify this over time by testing optimized tweets, UGC-rich copy, and SEM strategies derived from the actual terms people use when searching for your brand and products, and compare each to the non-optimized, marketing-derived alternative.

Tweets that mention brands are using fewer links over time. In the last half of 2010, 68% of tweets that mentioned brands also had links in them. In all of 2011, the number dropped to 55%. In the first half of 2012, the number drops further to 51%, signaling a clear downturn in link usage. This means

3 The Conversation Index Volume 3.

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14

TIME ON TWITTER AND PAGES PER VISIT ARE GROWING

AUGSEP

SEP

2010 2011

Source: COMPETE.COM

2012

OCTNOV

DECJA

NFEB

MAR

APRM

AYJU

NJU

LAUG

AUGOCT

NOVDEC

JAN

FEBM

ARAPR

MAY

JUN

JUL

400

420

440

460

480

500

520

540

560

TIM

E O

N S

ITE

(in

sec

onds

)

PAG

ES P

ER

VISIT

580

600

620

640

660

680

700

720

740

760

780

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

Time on site (in seconds)Pages per visit4

48

42

5

42

8

42

1

42

3

45

8

434

45

6 46

7

45

7

48

6

52

8

58

3

56

3 56

6

59

3

578

579

54

4 55

1

58

3 60

2

68

4 714

10.1 9.9

7.7 7.68.1 8.4

7.4 7.46.6 6.5

6.9

8.1 8.08.4

9.710.3 10.4

9.9

10.8

12.0

12.9

15.1 15.2

7.3

66

6

14.1

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that content about brands on Twitter is becoming increasingly conversational, and less transactional. Users are talking about brands instead of just pointing to what they bought or want to buy with a link to external sites.

External data confirms this. Twitter users are spending more time on Twitter, and visiting many more pages within Twitter.com while they’re there. According to data from Compete.com, from 2010 to 2011, there was a 19.8% increase in average time on site; in 2011 to 2012, so far, there is a 19.7% increase in time on site. And average pages per visit decreased 9% from 2010 to 2011, but increased by an incredible 58.7% from 2011 to 2012.

Pages per visit increased by an incredible 58.7% from 2011 to 2012

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Brands get more tweets, but less of the conversation is about themThe volume of tweets per day has grown 143% from 2011 to 2012; however, mentions of brands on Twitter have only grown 113% in the same period. To maintain and improve Twitter share of conversation, brands should analyze their data to find which tweets are generating positive conversation about them, emulate these tweets, and continuously optimize and add fresh content.

Original tweets about brands are declining over time,

as retweeted brand mentions are rising. In other words, more and more content is simply repeated verbatim or with little alteration from the original source. In 2010, 85% of brand mentions on Twitter were original, and 15% were retweets. In 2011, 18% of brand mentions were

retweets. So far in 2012, 22% of all brand mentions on Twitter have been retweets, and only 78% of brand mentions are original.

There’s good news and bad news for brands in this data. The increase of brand mentions overall means there is more data to learn your customers’ thoughts about you, but as the retweet analysis shows, that data is increasingly redundant. Retweets are becoming a bigger part of the Twitter brand story, but a retweet is a weaker social signal than an original tweet from, say, an advocate or detractor. Retweets also contain less original data, and may not represent the users behind them as much as a wholly original tweet from the same user. Our research also found that some of the most retweeted content is the work of automated bots (nonhuman scripts) and spammers that have set up networks of auto-retweeting accounts to spread their inauthentic messages across the social web as quickly as possible before Twitter shuts them down. Altogether, this means that businesses need to apply more scrutiny to Twitter data. Perform spot checks, weight and filter your metrics to place less emphasis on retweets about your brand if you find they are far more noise than signal.

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2010 2011 2012

BRAND MENTIONS VOLUME GROWING; ORIGINAL TWEETS DECLINING

500

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1000

1500

AG

GR

EG

AT

E O

F B

RA

ND

ME

NT

ION

S (i

n th

ousa

nds)

OR

IGIN

AL

TW

EE

TS (i.e., not retw

eets)

2000

2500

JUL

AUGSEP

OCTNOV

DECJU

LAUG

SEPOCT

NOVDEC

JAN

FEBM

ARAPR

MAY

JUN

JAN

FEBM

ARAPR

MAY

JUN

537

,332

539

,86

4

536

,89

4

615

,218

638

,98

3

58

7,4

69

68

1,4

55

69

5,0

41

784

,875

879

,132

1,0

31,8

75

919

,238

89

7,4

34

96

7,9

93

1,0

39,5

32

1,13

0,9

81

1,0

67,

332

1,2

47,

513

1,37

2,3

90

1,5

07,

232

1,72

4,3

14

1,8

29

,34

4

2,2

29

,62

0

1,9

77,7

83

78% original tweets in 2012 (as of June), down from 82% in 2011 and 85% in the second half of 2010.

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PERCENTAGE OF BRAND MENTIONS CONTAINING LINKS IS DECLINING

AUGSEP

SEP

2010 2011 2012

OCTNOV

DECJA

NFEB

MAR

APRM

AYJU

NJU

LAUG

OCTNOV

DECJA

NFEB

MAR

APRM

AYJU

NJU

L

10

20

30

40

50

60

70

80

90

100

PE

RC

EN

TAG

E O

F T

WE

ET

S W

ITH

LIN

KS

537

,332

539

,86

4

536

,89

4

615

,218

638

,98

3

58

7,4

69

68

1,4

55

69

5,0

41

784

,875 ,

879

132

1,0

31,8

75

919

,238

89

7,4

34

96

7,9

93

1,0

39,5

32

1,13

0,9

81

1,0

67,

332

1,2

47,

513

1,37

2,3

90

1,5

07,

232

1,72

4,3

14

1,8

29

,34

4

2,2

29

,62

0

JUL

1,9

77,7

83 A

GG

RE

GA

TE

OF

BR

AN

D M

EN

TIO

NS (in thousands)

500

1000

1500

2000

2500

51% of tweets contain links in 2012 (as of July), down from 55% in 2011 and 68% in the second half of 2010.

994

,291

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The increase in retweets also illustrates that news travels faster than ever before—and that a single piece of content can have major consequences for the companies involved. In fact, many of the most retweeted messages about brands in our analysis were highly negative in sentiment, and concerned things like scandals, lawsuits, and negative press coverage. Now is the time to prepare social crisis communications plans if you haven’t already.

It’s also important for brands to get to know the real people that are creating the ripple effect for their brand across the

network (and, as this Index shows, beyond) by creating consistently retweetable content—they are the greatest distributors of social currency. Reach them, highlight, and promote them if they are advocates, and address their concerns if they are detractors. Determine whether they are influential in other channels: Are they a top reviewer as well? Give them exclusive access: insider news, early product testing, event invitations, and the like. Make them feel like a part of your brand instead of a spectator, and in all cases, locate them as soon as possible.

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Search interest doesn’t correlate to Twitter mentions, stock performance, or TV and radio coverage

While it may seem that people tweet what’s top of mind, they’re not tweeting about what they’re searching for. While we saw this across the board, we’ll use Clinique as an example. Twitter mentions for “Clinique” spike in April 2011, August 2011, and March through June 2012. During these Twitter peaks, however, we saw either no correlation with search interest or a decline in search interest (search interest is Google’s normalized indicator of “the likelihood of a random user to search for a particular search term” on a 0-100 scale). When we compared the stock performance of the brands in this analysis to search interest for the same period in time, we found no correlation.

Unpaid coverage doesn’t drive much search activity

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112

012

FOLLOWER GROWTH FOR USERS THAT MENTION BRANDS

NETWORKS GROWING FOR USERS THAT MENTION BRANDS

JUL

AUG

SEP

OCT

NOV

DEC

JAN

FEB

MAR

APR

MAY

JUN

JAN

FEB

MAR

APR

MAY

JUN

100200

300400

500600

700800

9001000

11001200

13001400

15001600

17001800

19002000

Average Twitter followers per user

1566

1309

1287

1161

1299

1183

1041

1087

1155

1177

1194

1067

1067

1208

1130

993

1097

995

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4 http://econsultancy.com/us/blog/7731-how-can-marketers-use-offline-ads-to-drive-people-online

We analyzed 8,000 brand mentions in closed captioning data from television broadcasts (most TV ads are not closed-captioned, so ad mentions are not reflected in this data), and radio transcripts (this data does include ads) to determine whether brands being mentioned in traditional media saw a corresponding bump in search interest. Surprisingly, they do not. This suggests that unpaid coverage (news pieces, etc.) doesn’t drive much search activity, but findings from a study by Efficient Frontier show television ad campaigns correlating to a 60%-80% bump in brand-name search during the life of the campaign.4 So, while unpaid coverage in traditional media may be a great awareness mechanism, it’s not driving the consumer search behavior many businesses are craving. For that, television ads still seem to do the trick.

Brand advocates and detractors have wider audiences in 2012

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The bottom line? Social and “the real world” are becoming inextricable

The borders between “social” and “the real world” are difficult to pinpoint, but they’re being redrawn in some places, and eliminated in others. Consider this: Just a few years ago, the terms “in-store” and “online” gave us a clear, differentiated way to talk about channels. But as channels converged, and consumers began to use the mobile web while in the physical aisles, the terms no longer accurately described the way that people actually shop. The same is true of social—and everything it touches.

Convergence is a new concept for many companies, but it’s actually nothing new in practice. In fact, it’s the “place” we’ve called home since 2005. Reviews, Q&A, and stories are all forms of earned social content that live on owned digital real estate. And while we were helping clients across the globe integrate owned and earned, Twitter launched, Facebook opened to the public, and search became more and more social. Channels blossomed, and are now converging. Data exploded in volume and then fragmented, and is now coming together again. Convergence will soon cease to be the exception, and will become the rule, just as product reviews on company websites were once the exception.

Social’s connection to the world around us is has been established in some areas, cannot be found in others, and has yet to be discovered or quantified in most. But it’s far better for businesses to look for it everywhere and find it only in some areas, than for them to stumble over it where they least expected it.

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The methodology behind The Conversation Index Volume 5Volume 5 is based on an analysis of social content and other data surrounding 13 brands appearing on the BrandZ™ Top 100 Global Brands list, which ranks the “most valuable global brands” of 2012. The brands analyzed are Adidas, Clinique, Colgate, Gillette, Hugo Boss, Nike, Pampers, Pepsi, Ralph Lauren, Samsung, Intel, Tesco, and Sony.

The data includes 26,000,000 tweets, over 8,000 TV and radio mentions, 17 months of stock price data from relevant exchanges, more than a year and a half of Google search data, and 270,000 pieces of authentic user-generated content from online reviews across the vast Bazaarvoice network.

ContributorsColumn Five Media created the visualizations for The Conversation Index Vol. 5.

columnfivemedia.com

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Contact usContact us to see how we help brands gain invaluable consumer and product insights by putting consumer conversations at the heart of their organizations.

United States: (866) 522-9227 bazaarvoice.com

United Kingdom: +44 (0) 208.080.1100 bazaarvoice.co.uk

France: +33 1 56 60 54 45 bazaarvoice.fr

Germany: +49.89.24218508 bazaarvoice.de

Netherlands: +31.20.301.2169

Australia / Asia-Pacific: +61.2.9362.2200

Sweden:

San Francisco:

+46.8.463.1083

(866) 345-1461

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About Bazaarvoice Bazaarvoice brings the voice of customers to the center of business strategy, transforming business performance for nearly 2,000 clients globally, including over half of the Internet Retailer 500 list of the world’s largest retailers, over 20 percent of the Fortune 500, and over one-third of the Fortune 100 brands. Bazaarvoice social software helps clients like Best Buy, Costco, Dell, Macy’s, P&G, Panasonic, QVC, Travelocity, and USAA create social communities on their brand websites and Facebook pages where customers can engage in conversations. These conversations can be syndicated across Bazaarvoice’s global network of client websites and mobile devices, making the user-generated content that digital consumers trust accessible at multiple points of purchase. Through Bazaarvoice, manufacturers can also connect directly with consumers on retail sites to answer questions and respond to reviews about their products. The social data derived from online word of mouth translates into actionable insights that improve marketing, sales, customer service, and product development. Headquartered in Austin, Texas, Bazaarvoice has offices in Amsterdam, London, Munich, New York, Paris, San Francisco, Stockholm, and Sydney.

For more information, visit www.bazaarvoice.com, read the blog at bazaarvoice.com/blog, and follow on Twitter at twitter.com/bazaarvoice.

#BVINDEX5TheConversationIndex.comTheConversationIndex.co.uk TheConversationIndex.de

#BVINDEX5

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