Measurement and monetizing customer experience with social media.

Monetising Social Media Engagement and the Measurement

Measuring the Value of the Customer Experience

FORWARD

• Contained in this document is valid proof that social media brand conversations can be quantitatively measured and monetized. This represents a significant development and innovation in marketing measurement. It monetizes the customer experience and brings tangible and measureable value to the voice of the customer.

THE AGENDA

• Who we are• Social Media Measurement: Search for a New & Valid Approach• Leveraging Social Media Engagement Metrics for Deeper Insights

– Monetizing Social Media Word-of-Mouth & Marketing: The Marketing Mix Model

– The volumetric impact of Positive and Negative Buzz– Determining Which Social Channels are Driving Brand Performance– The Key Factors or Reasons Driving Consumer Engagement with Your

Brand– Using Social Metrics to Monetize the Value of Marketing Sponsorships– Valuing Facebook marketing campaigns– Leveraging Social Media Analytics to Find Out Why Consumers Use

Your Brand• Social Media Measurement and the Blue Ocean?

A NEW APPROACH TO SOCIAL MEDIA MEASUREMENT: THESOCIAL ENGAGEMENT INDEX OR SEI

• This analysis will trace the development and value of an approach for measuring consumer engagement on social media. This approach is called the “Social Engagement Iindex” or SEI.

• This metric is based on an algorithm developed with the assistance of Dr. Boyd Davis, Professor of Applied Linguistics at the University of North Carolina and Dr. Peyton Mason, CEO of Next Generation Marketing Insights The involves four steps and it leverages linguistics science heavily.

1. First we scrape large quantities of social media conversations filtered for topics on the specific brand of interest. The data source is social media sites like Twitter, Facebookand Blogs; but this same method has also been used to “score” customer reviews from various hospitality review sites like Hotels.com and Trip Adviser.

2. We next divide these conversations data into positive and negative sentiment conversations.

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

4. We finally time-code each conversation and aggregate into a time series metric.5. This approach differs from standard sentiment metrics, text analytics and even

natural language processing because 1) it evaluates the entire conversation not just key word, 2) it evaluates conversations within context and 3) it is based on language structure and rules, not just counting words.

DERIVING THE SOCIAL ENGAGEMENT IINDEX: THE NUTS & BOLTS

5

1. SCRAPE ALL SOCIAL MEDIA CHANNELS FORBRAND CONTEXT CONVERSATIONS, E.G. BRAND MENTIONS

2. DIVIDE INTO POSITIVE & NEGATIVE REVIEWGROUPS. FURTHER DIVIDE INTO KEY TOPICS.

3. DERIVE ENGAGEMENT INDEX BYCONVERSATION FROM 30 LINGUISTIC RULESTO “SCORE” MINED BRAND/TOPIC SOCIALMEDIA CONVERSATIONS

4. TIME CODE BY WEEK & AGGREGATEMETRICS

POSITIVEREVIEWS

NEGATIVEREVIEWS

POSITIVESCORES

NEGATIVESCORES

SOCIAL MEDIACHANNELS

LOW MED HIGH

High

Med

Low

EMOTIONAL SCORE

PERS

ON

ALIZ

ATIO

NSC

ORE

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1

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8

Per 1

Per 2

Per 3

Per 4

Per 5

Per 6

Per 7

Per 8

Per 9

Per 1

0

SEI SCORE

SEI Ratio

* Next Generation Marketing Insights, 2011

THE SOCIAL MEDIA MEASUREMENT LANDSCAPE AND THEVALIDATION TASK

• Presently, there are 3 approaches to social media measurement:– Standard Sentiment Method. This approach classifies conversations as being primarily

positive, neutral or negative with respect to the subject. Metrics are aggregated purely by word-count or frequency

– The Influence Approach. This approach scores conversations based on the influence of the author (number of friends, connections, etc.). Klout score is an example.

– The Language or Linguistics Method. This approach uses Linguistic science or rules to classify sentiment and score the conversations based on some measure of emotion or intensity from the language & context of the conversation. This is the Social Engagement Index Method we have developed.

• When comparing methods, we were limited with comparison on the Influence Approach, since this is an individual scoring algorithm and there is no aggregate time-series sentiment-based metric to correlate to brand sales.

• The key to understanding the attraction of any metric for statistically measuring its impact on a brand begins by looking at simple correlations to brand sales. In this context, we took one client brand and compared Standard Sentiment Metrics to the Social Engagement Index in terms of their core statistical correlation to brand sales over time.

AVAILABLE SOCIAL MEDIA “SENTIMENT METRICS” FALL SHORT AS A TOOLFOR MEASURING ROI

-20% 0% 20% 40% 60% 80% 100%

METRIC 1 POS/NEG RATIO






SOCIAL ENGAGEMENT INDEX POS/NEG RATIO

11.2%

3.1%

-2.3%

8.8%

21.2%

8.2%

83.1%

Figure 1: Compares correlation to sales of $6B client with SEI and sentiment metrics for 6 leading social data vendors, there is a wide gap.







SOCIAL ENGAGEMENT INDEXPOS/NEG RATIO

CASE STUDIES: THE SEI METRIC AND LINKS TO BRAND SALES

• To fully leverage the SEI 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 SEI metric to 3 clients’ customer demand over time.– Our comparisons come from three different clients, one in the food &

beverage industry, a telecom client and one from the hospitality industry.

– The specific SEI metric we use here, and in our model, is the SEI ratio of positive to negative tonality conversations.

IN THE TELECOM INDUSTRY, THE SEIsm IS STRONGLY CORRELATED TONEW CUSTOMER ADDITIONS (85%)

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New Customer Sales Index SNI Ratio Index

SEI P

ositi

ve/N

egat

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Inde

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TELECOM NEW CUSTOMER ADDITIONS

IN THE FOOD & BEVERAGE INDUSTRY, THE SEIsm MIRRORSCOMPANY SEASONAL PATTERNS (84%)

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TOTAL FOOD & BEVERAGE SALES

SEIsm IS A REFLECTION OF TOTAL "WORD-OF-MOUTH" AND A PROXY FOR CONSUMER GOOD WILL

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TOTAL HOSPITALITY BOOKINGS

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Bookings.Index SNI Positive/Negative Ratio

FOR A HOSPITALITY CLIENT, SEIsm IS A STRONG CORRELATE TO NEWBOOKINGS (77%)

THE METRIC USED WAS “ONLINE” REVIEW SITES FOR HOTELS, RESORTS AND CRUISE LINES. WEFOUND THE METRIC TO BE A PROXY FOR CUSTOMER SATISFACTION 11

MONETIZING THE VALUE OF SOCIAL MEDIA THROUGHMARKETING-MIX MODELS

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

• By incorporating SEI 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• Our task is to build a “nested model” where SEI is both a dependent and a

predictor variable. In the former, SEI is a function of all media & marketing efforts. In the latter, sales is a function of all media & marketing plus the SEI.– This approach not only enables us to understand the impact of Social Media

Word-of-Mouth, but also the influence of media and marketing on social media brand conversations.

A TWO-STAGE MODEL IS USED TO QUANTIFY THE DIRECT IMPACT OFMARKETING AND SOCIAL MEDIA ACTIVITIES ON SALES

1. Model the Social Engagement Iindex as a function of key marketing & media drivers

2. Model retail time-sales as a function of media & marketing drivers plus the SEI

56%

7%2%

5%

11%

19%

35%

Base Sales Conventional Marketing Campaigns Mkting campaigns on SM

Net Contribution of Marketing

2%+6%

+6% +13% = 27% Social Media Conversations

(SEI)

Sub-modelTotal Retail Sales Contribution

13

19%

A KEY INSIGHT DISCOVERED IS THAT NEGATIVE-SENTIMENTCONVERSATIONS HAD A SIGNIFICANTLY GREATER EFFECT THAN

POSITIVE ONES

ENSURE THAT YOUR BRAND IS REDUCING NEGATIVE TONED CONVERSATIONS

+4.4%

+16.5%

0%

5%

10%

15%

20%

Increase Positive Decrease Negative-30%

-20%

-10%

0%

10%

20%

30%

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

Sale

s Im

pact

Sale

s Im

pact

Change in "Engagement" by Tone

Total Retail Sales Sensitivity of Response(chg in Sales vs chg in Sentiment components of "Engagement")

Absolute Response (Based on Standard Favorable Move)

negative

positive

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(Assumes 100% Decrease in Negative is not realistic)

HOW SOCIAL MEDIA CHANNELS ARE DRIVING BRANDENGAGEMENT AND SALES

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Sales & Total Social Network Engagement Drivers by Channel

Facebook Twitter Boards Blogs &Groups Sales Index

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WHAT ARE THE “STORIES” OR CONTENT SHARED ABOUT YOUR BRANDTHAT IS MOST RELEVANT TO DRIVING REVENUE?

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Engaging Social Topics for a Restaurant Chain

Promotion A Place to Hang Out To Meet Friends and Associates Product B Product A Sales Index

The key topics/subjects of conversation about brands are scored. we can understand the reasons behind brand social media performance and can quantify these in terms & monetize their value

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Sponsorship EngagementNFL-FootballSponsorship EngagementPGA Golf

Super Bowl

Sponsored PGATournament

UNDERSTANDING THE KEY EVENTS AND FACTORS DRIVINGSPONSORSHIP AND BRAND ENGAGEMENT

SEI has been successfully used to measure and monetize the value of sports sponsorships

VALUING AND MONETIZING FACEBOOK MARKETING CAMPAIGNS

• Because our Social Engagement Metric is part of a larger model, we can value events such as Facebook Campaigns. As shown below, the net consumer engagement is not necessarily the same as the volume of comments or the number of Likes.

Most Important Positive Drivers:

1. The Brand & Place2. For Meeting People3. The Beverages4. The Store Atmosphere

Positive SEI 3.93 = 100

Place2HangOut >5.46= 211

9.1%

Place2HangOut <5.46 = 83

91.9%

ToMeetPeople>9.43 = 325

2.6%

ToMeetPeople<9.63 = 188

6.5%

Beverage>14.0 = 4660.6%

Beverage<14.0 = 2881.9%

To Meet People>5.4 = 229

3.8%

To Meet People<5.4 = 85

85.5%

Beverage>6.4 = 271

7.7%

Beverage<6.4 = 74

77.8%

Place2HangOut>3.6 = 126

5.9%

Place2HangOut<3.6 = 76

71.9%

Atmosphere >5.2 = 211.1

1.6%

Atmosphere <5.2 = 67

70.3%

These starts show 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.

DETERMINING THE RELATIVE IMPORTANCE OF KEY CONCEPTS ORSOCIAL CONTENT IN DEFINING THE BRAND

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THE “BLUE-OCEAN” OF SOCIAL MEDIA MEASUREMENT: KEY INSIGHTS

• By linking a metric of “Social Network Engagement” to client sales, 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. We have thus succeeded in measuring and monetizing the impact of social media on consumer demand.

• We have also shown that these data provides deep insights about what moves brand performance in the market place, a new depth of understanding that could be considered a blue-ocean innovation.

• Some of the key lessons that we have learned include:– The impact of the SEI on brand performance tends to mirror the phenomena of “word-of-mouth”, which is a

known critical driver of most brands, but traditionally difficult to measure.– Negative sentiment towards a brand have substantially greater impact on its performance than positive. It is

imperative that firms address expressed issues with these consumers and prevent the negative buzz from going widely viral.

– For service based firms like the hospitality client, the social engagement from online reviews represents a measure of customer satisfaction, which is a dominant driver of these businesses. The social engagement metric here represents a promising tool for deriving customer service ratings for various business domains from such sites as Yelp, Expedia and Trip Advisor.

– Our approach to Social Media Measurement provides a wealth of insights into why consumers buy your brand, how consumers engage with your brand and sponsorships and what particular social channels are most important in driving your brand. It monetizes the consumer experience.

– That the direct impact of SEI on business is large and significant. A brand’s marketing and advertising has some effect on the SEI 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 (SEI )

– That our SEI 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.

Bottom-Line Analytics LLC is a consulting group focusing on a broad portfolio of marketing analytics, including marketing optimization modeling

Our modeling experts have a total of over 100 years of direct experience with marketing optimization modeling. This includes direct experience in over 35 countries and dozens of product categories.

We are dedicated to the principles of innovation, excellence and uncompromising customer service.

Most important, however, we are dedicated to getting tangible and positive business results for our clients.

ABOUT US

OUR EXPERIENCE

WAS THIS INTERESTING?

• Please contact for a direct discussion• Michael Wolfe, Principal

Bottom-Line Analytics LLC(o) 770.485.0270(m) [email protected]

mailto:[email protected]

Measurement and monetizing customer experience with social media.

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Transcript of Measurement and monetizing customer experience with social media.