1

2011 Market Research in a Mobile World July 2011 Michael Wolfe

THE HOLY GRAIL?

• Don’t believe it for a minute, it doesn’t exist! • But some metrics are better than others. • There are many social media metrics available today.

– Many simply count words with rudimentary sentiment differentiators – Others based on Influence, klout scores, number of followers, etc – Still others based on language and Linguistics science

• We have developed a special metric called the Semantic Engagement Indexsm(or SEIsm). – It is based on the principle that conversations on social media are

more than just words or what is said, but how it is said and the context of the conversation. Semantics matter.

– We directly compare our SEI with other social media sentiment metrics from a leading social media aggregator company.

SEI AND SOCIAL SENTIMENT METRICS

• The comparison is with our Semantic Engagement Indexsm and a Social Media Sentiment indicator from a leading social media data company. As you can see, the Sentiment Indicator has poor and somewhat contradictory correlations with our selected company’s sales. The SEIsm metric, however, shows strong and robust correlation and logically consistent to the positive and negative forms.

Correlations to Sales

SEMANTIC ENGAGEMENT INDEX: NUTS & BOLTS

• This metric is based on an algorithm devised with the assistance of Boyd Davis, Professor of Applied Linguistics at the University of North Carolina and a vendor partner named Linguistics Insights. The process we go through here involves four steps and it leverages linguistics science heavily. 1. First we secure large quantities of social media conversations

filtered for topics on the specific brand of interest. In the case of the hospitality client, this was focused on online review sites pertaining to hotels, resorts and cruise lines.

2. Next we parse these conversations data into positive and negative toned conversations.

3. Next we apply our proprietary algorithm which quantitatively “scores” each of the positive and negative groups along the two dimensions of “emotional affect” and “personalization”. This scoring algorithm applies the science & rules of Linguistics.

4. Finally, we time-code each conversation into topics and aggregate into a time series metric.

CASE STUDIES

• To fully leverage the SEIsm for our clients, the task is to understand its impact on their business.

• To do this, we do exploratory analysis to see how relevant the metric is to the customer demand of a number of clients.

• Then we utilize the SEI within a full marketing response (aka, mix) model in order to not only understand its impact on the business, but also how it interacts with and is affected by direct marketing.

• First, however, we compare the customer SEIsm metric to 2 clients’ customer demand over time. – One client is a food & beverage retailer, while the other is in the

hospitality industry – The specific SEIsm metric we use here, and in our model, is the SEIsm

ratio of positive to negative tonality conversations.

TOTAL HOSPITALITY BOOKINGS

-

20

40

60

80

100

120

140

160

-

20

40

60

80

100

120

140

1/7/2008 1/7/2009 1/7/2010

SEI

Po

siti

ve/N

ega

tive

In

dex

Bo

oki

ngs

Ind

ex

Bookings.Index SEI Positive/Negative Ratio

• For our hospitality client, the key focus of our SEIsm metric was “online” review sites for hotels, resorts and cruise lines. This makes the metric a proxy for customer satisfaction. As shown, the correlation is a very robust +76%!

0

50

100

150

200

250

300

350

400

80

85

90

95

100

105

110

115

120

125

130

07/09/07 08/04/08 08/31/09

Ret

ail S

ales

Ind

ex

TOTAL Retail.Sales SEI Positive/NegativeRatio

SEI P

osi

tive

/Ne

gati

ve In

dex

7

TOTAL FOOD & BEVERAGE SALES

Correlation of Sales to SEI Metric is 87% (Total 156 Weeks)

SEI AND MARKETING RESPONSE MODELS

• To fully leverage the SEIsm for our clients, the task is to understand its impact on their business.

• By incorporating SEIsm metrics into marketing response (aka, mix) models, we can: – Come to a better & more precise understanding of how

social media buzz affects a client’s business performance

– Understand the impact and interactions of the client’s marketing and media as it affects social media conversations about their brands.

– Provide strategic guidance as to the most effective ways for monitoring and managing social media conversations on brands

9

THE IMPACT OF SOCIAL MEDIA TONALITY

• A key insight we uncovered across clients is the difference between “positive” and “negative” conversations about a brand. In absolute terms, the negative-toned conversation has a significantly greater net impact. It is actually better for a firm to try to manage a reduction in negative toned conversations than to increase positive ones.

+4.4%

+16.5%

0%

5%

10%

15%

20%

Increase Positive Decrease Negative

-20%

-10%

0%

10%

20%

-100% -50% 0% 50% 100%

Sale

s Im

pac

t

Sale

s Im

pac

t

Change in "Engagement" by Tone

Total Retail Sales Elasticity of Response (change in Sales versus change in Tone components of "Engagement")

Total Retail Impact of 90% Change (assumes 100% Decrease in Negative is not realistic)

negative

positive

10

THE IMPACT OF SEI, SALES AND MARKETING

• We also learned that a there is both a direct and an indirect effect from client media & marketing. As you can see, the impact of Semantic Engagement is quite large. The “indirect” effect of marketing is due to the impact on the SEI metric, itself. Overall, this indirect effect is shown to greatly enhance the impact of the client’s marketing and significantly improves marketing spend ROI.

55%

6% 2%

6%

13%

18%

37%

Base Sales Direct Alpha Brand Media & Mktg Direct Social Media Mktg Blended Media Other.Media Other Base

net driven by marketing

8% +6% +13% = 27%

Engagement

Sub-model

Total Retail Sales Contribution

PREDICTING POSITIVE CONSUMER ENGAGMENT (SEI)

The most important positive drivers are: 1. The Brand & Place 2. For Meeting People 3. The Beverage 4. The Store Atmosphere

POS SEI 3.76 =100

Brnd&Place >5.75 =219 9.9%

Brnd&Place <5.75 =87

90.1%

Brnd&Place >9.63 =320 2.1%

Brnd&Place <9.63 =192 7.8%

Brnd&Place >14.29 =461 0.3%

Brnd&Place <14.29 =298 1.8%

Meeting People>5.84

=229 3.6%

Meeting People<5.84

=81 86.5%

Beverage>6.29 =255 7.9%

Beverage<6.29 =79

78.6%

Brnd&Place>3.64 = 121

7.0%

Brnd&Place<3.64 = 72

71.6%

Atmosphere >5.25

=209.6 1.3%

Atmosphere <5.25 =70

70.3%

We apply CART (Classification & Regression Trees) to score subject groups to determine what conversational topics & issues are driving consumer engagement.

The tree starts with an average SEI score of 100; and each level indicates a higher or lower SEI based on an SEI score for a topic.. The percent represents the percent of the sample in each segment.

THE MOBILE RESEARCH ANGLE?

• Certain social media data companies can now collect social media data for specific geographies and demographics. – www.gabacus.com

– www.decooda.com

• Social media as a tool for prediction: – Bernardo Huberman, Hewlett Packard

• Predicting elections

• Test market analysis – www.bzzagent.com

LESSONS LEARNED

• Through a number of case studies, BBDO’s “the Worth” has attempted to push back the frontier on social media metrics and understanding

• By linking a metric of “Semantic Engagement” to client sales and demand, we have shown that this approach shows great promise as a diagnostic for understanding social media’s impact on a client’s business by including it as an input into marketing response (aka, mix) models.

• Some of the key lessons that we have learned include: – For a service-based hospitality client, the consumer’s rating of the quality of

the firm’s service, is in fact, the most important driver of that firm’s business. – That negative brand conversations have a greater absolute impact on a client’s

business than corresponding positive reviews, i.e. negative word-of-mouth travels wider & deeper than positive.

– That the direct impact of SEIsm on business is large and significant. A brand’s marketing and advertising affects the SEI sm which in turn, affects sales.

– We learned that the value and ROI of marketing is greatly enhanced due to the indirect effect it has on sales through its direct impact on Social Media Engagement (SEIsm )

– That our SEIsm metric is no Holy Grail, but it shows much promise in delivering un-matched insights on how social media conversations have a direct and tangible impact on company performance.

Presented at:

Market Research in the Mobile World 2nd International Conference | July 19 & 20, 2011 Atlanta

Organized by: Thank you to sponsors:

LinkedIn Group: Mobile MR

Upcoming Merlien Events: Merlien.org GreenBook Directory: GreenBook.org Market Research Blog: GreenBookBlog.org New Qual Blog & Directory: NewQualitative.org

Get Inspired. Stay Informed. Cut Through the Clutter. Sign up for our free email newsletter