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Measuring Customer Experience ROIwith Social Media

New Developments in Measurement and Analytics

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Let’s Get Started

3About Us

Bottom-Line Analytics is a full-service consulting group focused on marketing effectiveness and brand performance analytics

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

Everything we do is geared toward improving the commercial performance of our clients

Our experts have a total of more than 100 years of direct experience in research, insights, and ROI measurement

4Measuring the customer experience is imperative

“You’ve got to start with the customer experience

and work back toward the technology – not the other way around.”

~ Steve Jobs

5Customer Experience Leaders Outperform the Market

CX Leaders[VALUE]

[CATEGORY NAME]

[VALUE]

CX Laggards[VALUE]

0%

20%

40%

60%

80%

100%

120%

Cum

ulat

ive

Tota

l Ret

urn

Eight-year Stock Performance of Customer Experience Leaders vs. Laggards vs. S&P 500

(2007-2014)

CX LaggardsIn addition to posting a total return

that was 74 points lower than CX leaders, laggards also had higher

customer frustration, increased attrition, more negative word-of

mouth, and higher operating expenses

CX LeadersOver 8 years, the leaders of

Forrester’s CX Index enjoyed a higher total return, higher revenues from

better retention, less price sensitivity, greater wallet share and positive word-

of-mouth) and lower expenses from reduced acquisition costs, and fewer

complaints,

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4%

27.6%

11.8%

23.7%

31.6%

What does your company's executive leadership think about the ROI of CX?

Doesn't believe there's an ROI of CX

Unsure there's an ROI of CX

Believes there's a small ROI of CX

Believes there's a moderate ROI of CX

Believes there's a large ROI of CX

Most Companies Understand that There Is a Sizable ROI in Customer Experience

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18.9%

28.4%35.1%

12.2%

5.4%

How effective is your company at measuring the business impact of CX?

Very ineffective

Ineffective

Somewhat effective

Mostly effective

Very effective

But They Aren’t Sure How To Measure It

8The Answer Is with Social Media

United Airlines is never on-time, and their service sucks.

Your brand is what people say about you when you’re not in the room.

~ Jeff Bezos

9But Most Social Media Sentiment Ratings Are Not Very Accurate

"Sentiment analysis is a very complex task for a machine because of the multiple and often unpredictable soft and hard variables that come into play when interpreting it. The main problem being that the sentiment of a sentence only rarely lies in the sentence itself and is instead rooted in the cultural context around that sentence.”

~ Francesco D'Orazio, CIO at FACE Group

"Companies are making decisions based on data that is just 6% accurate."

~ Carol Haney, SVP at Toluna

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And They Fall Short In Measuring ROI

21.2%

11.2%

8.8%

8.2%

3.1%

-2.3%

-10% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Correlation to sales of $6B client with the sentiment metrics of the six leading social data vendors

Sentiment Metric 1

Sentiment Metric 2

Sentiment Metric 3

Sentiment Metric 4

Sentiment Metric 5

Sentiment Metric 6

SEI Pos/Neg Ratio

11One Exception Is Ours: The Social Engagement Index, a.k.a., The SEITM

83.1%

21.2%

11.2%

8.8%

8.2%

3.1%

-2.3%

-10% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Correlation to sales of $6B client with the sentiment metrics of the six leading social data vendors

Sentiment Metric 1

Sentiment Metric 2

Sentiment Metric 3

Sentiment Metric 4

Sentiment Metric 5

Sentiment Metric 6

SEI Pos/Neg Ratio

12The BLA Social Insights, Analytics, And ROI Framework

Fuse SEITM with advanced analytics to understand brand positioning, content drivers, reputation and critical elements of customer experience

Leverage known tools to listen and monitor high-level brand-experience conversations

Measure language based on engagement and importance via the Social Engagement Index, or SEITM

Listening,monitoring and basic sentiment

Measuringlanguage for

brand insightsSocial media

advanced analyticsSocial

monetization

Apply a trended SEITM

within media mix modelling to monetize customer experience (earned social media) alongside all other media and quantify any synergistic effects

BLA extends the value of social media insights

We will focus on this specific application of SEI today

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SEITMSEITMStance Shift

Syntax & Structure

Tonality & Sentiment Context

Custom Dictionary

A More Accurate Way To Mine Social Conversations

• Measures value of customer experience

• Links closely to sales

• Indicates brand health

• Uncovers “why’s” and underlying drivers, both positive and negative

Experiential Statement on Social

Media

Ex

Rx

Pr

Customer Experience &Engagement Rational

14The Difference Is Stance-shift Analysis, A Method That Measures What Really Matters In Language• Stance-shift analysis, published and peer-reviewed, reveals what really matters to the consumer:

– Stance-shift measures consumers’ verbal shifts in positioning as they talk.– We capture the emotion, intensity, appraisal, and commitment in the context of the conversations to uncover the deep subtleties

and what is said.

• It enables us to solve what others miss: Size, Trend and New Concepts– Focusing only on what matters: We filter and sizerelative importance through engagement–far superior to simple words/comment

frequency.– Consumertrends: We capture the shifts and prioritize getting the trendright, validated through the independent measure of our

metrics vssales.– Stance is tuned to detect topicsand concepts, which we link to quantified opinions, evaluations and endorsements through adaptive

tonality, allowing us to map strengths, weaknesses, opportunities & threats.

• Semantic Engagement Index: SEITM integrates our stance-shift measurement to power our consumer insights.

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I just got my cool new iPhone from BestBuy; however, I keep getting dropped calls on the Brand X 4G network.

Most social sentiment tools would bungle the analysis of this statement.

Positive

Negative

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I just got my cool new iPhone from BestBuy; however, I keep getting dropped calls on the Brand X 4G network.

Positive

Negative

Flag Brands & Relative Importance

Custom Coding

Engagement

Transitional word (Shift in

Stance)

Shift-Stance Analysis Accounts For Context, Industry Terminology And Channel-Specific Language

17Our Process Brings Structure To Consumer Data Chaos

From millions of cleanedsocial media conversations

We detect thousands of interesting “nodes” of consumer information

Our supervised learning pattern detection organizes the nodes

Small Pepermint Afternoon Snack 12 PackGreat Deal Breakfast yum LargeMiss it Get me one Orange on saleMorning Half Priced got coupon Drive HomeVanilla Mocha 8 Oz need a hit

Clear themes and topics of importance emerge

Powerful social insights on themes and topics that are

most important to consumers

Advanced analytics to help drive content strategy

and measure social ROI

18The Correlation to Sales Over Time Shows the SEI™ Has Strong Predictive Power

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Correlation = 84%

Note: Lead-lag analysis has confirmed that causation is only one way. The SEI™ to a large degree is capable of driving hard commercial metrics.

86%

Telecom Brand

81%

Soft Drink Brand

84%

Food & BevBrand

83%

Hospitality Brand

19The SEITM Has Been Validated Across a Diverse Set of Brands in the US and Internationally

52%53%

56%57%

59%68%

73%74%

77%79%79%79%79%

81%81%

84%86%86%

88%

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

Haircare Brand

Personal Care …

Personal Care …

AVERAGE

Hospitality Brand 2

Cosmetic Brand

Softdrink Brand

DIY Retailer …

Telecom Brand

Movie 2

SEI Correlation To Sales for 18 BrandsValidated more than any other social metric

20The SEITM Has Broad-based Application

$Monitor and manage

consumer conversationsthat are impacting your

brand reputation

Apply deep understanding to consumer conversations to

develop Content and Marketing Strategy

Enhance the in-market execution of promotions, sports sponsorships, and events based on real consumer conversations

Monetize your social media campaigns andthe customer experience with our media mix models

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Case 1: Defining the Coffee Retailer Brand and Position

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For a coffee retailer, we uncovered 26 “content drivers,” which are topical themes and components of the SEI. We conducted CART regression analytics, which arrays these themes in order of importance for prediction of SEI. Of these 26 drivers, 18 were beverage or food product-related, while 8 were topics related to the store experience.

Store experience was found to be a more important than the products in terms of driving sales and defining the brand.

Key Content Drivers of Retail Sales

To meet people188

Atmosphere288

Atmosphere466

Note: Separate analysis - Classification & Regression Trees (CART)

Positive Social Engagement

100To meet people

229Place to hang out

83Beverage A

271

Beverage A74

To meet people85

To meet people325

Insight & Outcomes

Key drivers to positive SEI™:1. A place to hang out

2. To meet people3. Atmosphere

4. Beverage products

Based on these findings, the client developed a “2 for 1” promotion

to drive store-level sales.

This was the most effective promotion run on any product over the previous three years, generating a lift in three weeks equal to approximately 4% of

total sales.

Place to hang out211

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Case 2: Social Content Drivers for Brand Positioning

24SEITM and Marketing Contributions for “Zip”

78.6%

2.1%

6.8%

3.3%3.0%2.5%2.4%1.9%1.1%0.4%

23.5%

Zip Modeled Incremental ContributionsBaselineSEI/Mktg SynergySEI-Social MediaRadioPOS SignageTVDigital DisplaySamplingPub.ReltnsOOH

Zip’s Marketing ContributionsBy modeling Zip with SEITM, BLA found

that buzz and advocacy stimulated by its marketing efforts drove almost 7%

of its volume, and marketing efforts helped boost a sizable synergistic dividend.

Zip’s Situation In 2009, a beverage retailer launched “Zip” (masked name), an “instant” beverage, which was a deviation from its naturally brewed products. Zip was one of the most successful product launches in 12 years.

Previous modeling research had shown that Zip actually generated a +3% lift to total retail sales. The successful launch strategy was aimed at getting maximum trial and exposure, driven by an extensive sampling period and early-stage price promotions.

The challenge in Year Two was to understand how to position the brand in order to sustain growth momentum.

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Zip Sales and SEITM Correlations Over Time

-

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

-

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

12,000,000

14,000,000

2/23

/200

93/

23/2

009

4/23

/200

95/

23/2

009

6/23

/200

97/

23/2

009

8/23

/200

99/

23/2

009

10/2

3/20

0911

/23/

2009

12/2

3/20

091/

23/2

010

2/23

/201

03/

23/2

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4/23

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23/2

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6/23

/201

07/

23/2

010

8/23

/201

09/

23/2

010

10/2

3/20

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Zip Sales Zip.SEI.Ratio SEI Ratio Norm

Tracking the SEITM over time revealed a high correlation to

Zip’s first year sales. This was clear evidence

of a powerful and effective effort to generate strong buzz and advocacy

toward the brand, with a strong linkage to sales.

Note: Plotted metric is ratio of Positive to Negative SEITM

The SEITM proved to have a leading-indicator relationship

with Zip sales.

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188

3,516

103 128 300301

350491

724

930

-500

1,000 1,500 2,000 2,500 3,000 3,500 4,000

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reat

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Zip Powder All Social Channels Engagement Content Drivers

Content Motivation Drivers of Sales Conversion for Zip Powder

Further analytics of Zip’s “content drivers” of SEITM consumer

engagement revealed key drivers to be “tasted like the real thing” and was great for “taking to the office” and enjoying that original taste of

the parent brand.

Current Positioning

OptimizedPositioning

By focusing its communications toward these benefits, Zip managed to continue

a strong 11% growth in Year Two.

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Case 3: Scoring and Evaluating Sports Sponsorships

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Assessing the ROI of Sport SponsorshipsThis client spent 65% of its total

marketing budget on sports marketing without understanding what they were getting back they were getting for any

of the sports they sponsored.

We used the SEI for each sponsorship to determine the ROI,

which showed that the NFLcould provide high returns

and high growth.

By investing more in NFL Football and less on NASCAR and NCAA

Basketball, this client managed to accelerate YOY growth from 3% to +8%

the following year.

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Social Media ROIMarketing Mix Modelling

Pricing Optimization

Radial Landscape MappingKey Drivers AnalysisDemand Forecasting

Customer Satisfaction ModellingDigital Performance Analytics

Dashboards

Segmentation Analysis

BLA Is a Trusted Advisor to a Wide Array of ClientsWe believe in the continuous innovative application of analytics to advance

customer-centric decision making for improved business performance.

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Let’s Get Started

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Michael is CEO of Bottom-Line Analytics LLC in the US. Michael has 30 years of direct experience in marketing science and analytics. On the client-side, he’s

worked for Coca-Cola, Kraft Foods, Kellogg’s, and Fisher-Price. As a

consultant, he’s worked with such blue-chip firms as AT&T, McDonald’s, Coca-Cola, Hyatt Corp., L’Oreal, FedEx, and Starbucks. He has broad experience in

marketing analytics covering marketing ROI modeling, social media analytics, pricing research, and brand strategy.

Michael WolfeDavid Weinberger is CMO of Bottom-

Line Analytics. David’s career has taken him to such blue-chip firms as Coca-

Cola, Kraft Foods, Georgia Pacific, and Home Depot. David’s consulting

experience has focused on such verticals as retailing, financial services, apparel,

consumer products, and insurance. David has considerable expertise in the

areas of customer analytics, life-time value, shopper marketing, social media,

brand strategy, segmentation, and marketing ROI analytics.

David WeinbergerMasood is the Bottom-Line Analytics

partner in the UK and heads the company efforts across EMEA. Before

joining Bottom-Line Analytics, Masoodwas Director of Analytics for McCann-

Erickson and has worked for Mintel International Group, JWT, Costa

Coffee, Coca Cola, and Hyatt Corp. He is an accomplished econometrician

with extensive experience in marketing ROI analytics, marketing research,

market segmentation, social media analytics, and marketing KPI

dashboards.

Masood Akhtar

Bottom-Line Analytics Leadership

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EMEA Office:5th Floor, 39 Deansgate,Manchester, M3 2BA, United Kingdom

Contact Us US Office:Suite 100, 1780 Chadds Lake Dr, NEMarietta, Georgia, 30068-1608Atlanta, USA