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Innovations In Marketing Effectiveness Measurement

January 4, 2016

2About 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

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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.

4It’s All About ResultsBrought first marketing ROI modeling to company in 1996. Developed models for Coca-Cola, Diet Coke, Fanta, and Sprite in 12 countries.. Sales gains in the following year exceeded $300 million over previous year.

Identified and quantified impact from the launch of iPhone. By identifying which ad copy messages were most effective, AT&T managed to increase its wireless telecom market share from 28 to 30%

Developed analytic system for measuring and evaluating ad copy used for Splenda brand. Enabled brand to reduce advertising production from eight commercials per year down to four executions, saving the client $6 million.

Developed SEI to quantify drivers of customer satisfaction, using TripAdvisorhotel reviews across 300 different properties. Insights lead to a 5% improvement in customer satisfaction in subsequent year and a +6% growth in total bookings.

Identified upside growth opportunity to drive sales by investing more in Dollar Menu items one year after launch in 2005. Our recommended higher investment made McD's the growth leader in its segment for the next two years.

Developed models to determine ROI of 12 different celebrity spokespeople used in L'Oreal commercials. By reducing number from 12 to the recommended 5 celebrities, leading to growth improvement from +3 to +5%.

Determined ROI of specific customer experiences using social media. Discovered brand’s core strength lies in its in-store experience. Refined product brand positioning for Frappucino and Via Coffee. Sales growth improved from +7% to +11%.

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0%

20%

40%

60%

80%

100%

Incremental Revenue

Current Spend Optimal Spend

Radio

Press

Outdoor

Television

Cinema

Digital

Sponsorship

67% 33%

Baseline

1%2%4%

5%

8%

12%

Television

Digital Media

Radio

Outdoor Boards

Press

Sponsorship

Cinema

Incremental Contribution from Marketing

Optimize Spend, Maximise Sales

Determine Sale-to-Sales Drivers Relationships

Key Deliverables for Mix Modeling

0.450.77 0.86

1.2

1.92

2.4

3.3

0

0.5

1

1.5

2

2.5

3

3.5

Sponsorship Outdoor Boards

Cinema Press Radio Digital Media Television

ROI per £1 Spent

Sales

Macro-Economic

Factors

Distribution

Seasonality

Price

Promotions & CouponsSponsorship

TV, Radio, Print, OOH

Digital Media

Social Media

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We fundamentally believe that marketing and media channels do not operate in silos, but most statistical models still treat them as such

We apply advanced non-linear methods of analytic modelling that account for direct and indirect effects from marketing drivers

No Silos

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Synergistic Effects

Long-term Effects

Social MediaEffects

Copy Quality Effects

Innovations In Multi-dimensional Media Measurement

Bottom-Line Analytics is at the forefront of innovations in media measurement. We have developed ways to measure media synergies, copy quality, long-term ad effects, and social media engagement.

8Our Mix Media Models Calculate the

Often-Overlooked Long-term Advertising Effects

Most advertising creates an initial short term lift in sales and a prolonged long termimpact. This is generated through repeat purchase and customer loyalty.

-30

-20

-10

0

10

20

30

40

50

60

2007 2008 2009 2010 2011 2012

Digital Baseline Brand Marketing Social Media

Radio Radio Website Distribution

Cable Long-term Ad Effects Retail Price

Long-term Ad Effect

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0

20

40

60

80

100

120

140

160

180

TV Copy 1 TV Copy 2 TV Copy 3 TV Copy 4

Copy Effect GRP Effect

Media content and copy quality can be separated and measured. This has implications for design, content and message mix.

Media Copy Quality Measurement

10Effective Measurement of Digital MediaAnnual Marketing Contributions

86.2%

0.0%2.9%

0.7%0.9%1.9%1.2%1.2%

3.0%0.2%1.8%

13.8%

BaselineDisplay Premium Display Network Paid Search

SEOBranded TCP TV GRPsSponsorship (TV Weather)CinemaRadio Press

GDP Effect

A 1.4 million-pound spend in marketing generated almost 13.4 million pounds in revenue sales. Total media accounts for about 12% of total sales. Radio, Digital Display and TV were the largest drivers of car sales.

11Marketing Synergies

2,308 2,308

1,060 1,060

1,434

-

1,000

2,000

3,000

4,000

5,000

6,000

Separate Impact Simultaneous Activation

Digital Radio Marketing Synergy

Radio and Digital Media are most effective when executed together. There is about a +43% synergy or additional lift due to simultaneous activation.

12Marketing Synergies

2,308 2,308 584 584

1,909

-

1,000

2,000

3,000

4,000

5,000

6,000

Separate Impact Simultaneous Activation

Digital TV Synergy

Television and Digital Media are most effective when executed together. There is about a +66% synergy or additional lift due to simultaneous activation.

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A Breakthrough In Measuring Social Media Engagement

14Our Approach to Measuring Social Media

Develop SEIMeasure language based on engagement and importance via the SEITM

Advanced AnalyticsApply analytics to SEI to evaluate reputation, content drivers, positioning, and customer experience

Social Monetization Trend the SEI within media mix modelling to determine ROI customer experience and quantify any synergistic effects

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

15A More Accurate Way To Mine Social Conversations

Stance Shift

Syntax & Structure

Tonality & Sentiment Context

Custom Dictionary

Stance-shift analysis is a published and peer-reviewed methodology that reveals what really matters to the consumer: It looks beyond the words and takes into account the consumers’ verbal shifts in positioning as they communicate. It accurately captures the emotion, intensity, appraisal, and commitment in the context of the conversations, uncovering the deep subtleties of what is being said. This enables us to solve what others miss: Size, Trends, and New Topics andConcepts.

16A More Accurate Way To Mine Social Conversations

Stance Shift

Syntax & Structure

Tonality & Sentiment Context

Custom Dictionary

• Size - We filter and size relative importance through engagement

• Consumer trends - we capture the shifts and prioritize getting the trend right,

• New topics and concepts - Stance is tuned to detect topics and concepts, which we link to quantified opinions, evaluations and endorsements via adaptive tonality. This allows us to map strengths, weaknesses, opportunities & threats.

17A More Accurate Way To Mine Social Conversations

Stance Shift

Syntax & Structure

Tonality & Sentiment Context

Custom Dictionary

The Semantic Engagement Index integrates our stance –shift measurement to power our consumer insights.

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\

SOCIALENGAGEMENTINDEX (SEI)

Conversations are Scored on Personal and Emotional Content

“I had a diet coke for lunch today”

“The warm Diet Coke was rather bland”

“I really love my coke with pizza”

“I like the taste of sprite with lemon”

“My coke has lost its fizz and tastes awful”

19Calculating the Social Engagement Index (SEI)

1. Mine all brand-related social media reviews and commentary.

2. Parse into positive & negative review groups

3. Apply Social Engagement Indexalgorithm to “score” reviews

4. Time-code by period and aggregate metrics

Positive Scores

Emotional Effect

Per

sona

lisat

ion

LOW MEDIUM HIGH

HIGH 0 5 7

MEDIUM -5 0 5

LOW -7 -5 0

8

1519

2421

28

0

10

20

30

January February March April May June

Num

ber o

f Van

dals

Net Positive SEI Index

NegativeReviews

Positive Reviews

NegativeScores

20The SEI Out-preforms Other Social Sentiment Metrics in Measuring the ROI of Customer Experience

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 SEI and the sentiment metrics of the six leading social data vendors

Sentiment Metric 1Sentiment Metric 2Sentiment Metric 3Sentiment Metric 4Sentiment Metric 5Sentiment Metric 6SEI Pos/Neg Ratio

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The correlation* to sales over time shows the SEI has predictive power

SEITM Has Proven Linkage with Brand Sales

Correlation = 86.4% Correlation = 84%

Correlation = 81.1%

Correlation = 83%Correlation = 83%

* Lead-lag analysis has confirmed that causation is only one way – the SEI to a large degree is able to drive hard commercial metrics.

22Many Applications of the SEI

Understand drivers ofpositive social engagement

Enhance and optimize the execution of sporting events

Measure the efficacy of individual ad campaigns

Assess brand perception in a competitive context

Develop content strategy that can cut through clutter

Understand consumer discourse and manage crises

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67%

8% 3%2%

2%10%

5%

11%

20%

Marketing Contributions

Base Sales Direct Alpha Brand Mass MediaDirect Alpha Brand Digital Media Direct Social Media Social Media on SEI Mass Media on SEI

Net driven by media

SEIEngagement

Sub-model

SEI to Measure Social Media ROI

We find that conventional advertising has both a direct and indirect impact on sales due to its influence on social media conversations and the SEI

The large contribution from the SEI support the notion that this is a word-of-mouth effect

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4.4%

16.5%

0%

5%

10%

15%

20%

Positive Sentiment Negative Sentiment

The Absolute Impact from Positive and Negative Consumer ReviewsA key insight we uncovered across clients is the

difference between positive and negative brand conversations

Negative-toned conversation have a significantly greater net impact on brand sales

Marketers need to develop strategies and tactics to immediately mitigate “negative news” and prevent them from going viral

The Impact of Social Media Sentiment

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Source: Nielsen BuzzMetrics data as of November 27, 2011

Social Channels Driving Consumer Engagement and Sales

Much like other marketing and media metrics, we can deconstruct the SEI metric into the channels that are driving social engagement and brand sales

CorrelationsFacebook: 86.8%

Twitter: 86.6%

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Positive SEI 3.93 = 100

Place to hang out

>5.46= 2119.1%

Place to hang out

<5.46 = 8391.9%

To meet people >9.43 = 325

2.6%

To meet people

<9.63 = 1886.5%

Atmosphere>14.0 = 466

0.6%

Atmosphere<14.0 = 288

1.9%

To meet people >5.4 = 229

3.8%

To meet people <5.4 = 85

85.5%

Beverage A>6.4 = 271

7.7%

Beverage A<6.4 = 74

77.8%

Place tohang out >3.6 = 126

5.9%

Place tohang out <3.6 = 76

71.9%

Beverage B>5.2 = 211.1

1.6%

Beverage B<5.2 = 67

70.3%Note: Separate analysis - Classification & Regression Trees (CART)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.

Develop In-market Strategies Based On Why Consumers Use Your Brand

.

Most Important Drivers to Positive SEI

Armed with this insight, the client developed a ‘Bring a friend, and get one

coffee free’ to drive store level sales

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Alpha_P1

Beta_P1

Note: Separate analysis - Adapted Statistical Correspondence AnalysisExample: Global Coffee ChainBubble size represents the buzz/volume of chatter (SEI Conversational Clusters)

Alpha_P2Beta_P2

Gamma_P1

Gamma_P2

Net chatter around value and price

Net chatter around coolness, funky, style, décor

Net chatter around taste and product quality

Net chatter around in-store customer experience

Delta_P2

Delta_P1

Good value

Coffee Price

Food prices

Staying in

Seating/chairs

Toilets

Richness

Latte

Amazing tasteLike no other

Cool brand

FunkyStylish Artwork/Decor

Visualize Social Media Brand Conversations

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Full Service Analytics Capability

Marketing Mix Modelling 3.0

Pricing Optimisation

Radial Landscape Mapping

Key Drivers Analysis

Demand Forecasting

Customer Satisfaction Modelling

Performance Analytics Dashboards

Segmentation Analysis

Why Bottom-Line Analytics?

Social Media MeasurementOur proprietary approach to social media

measurement is unrivalled.

Impartial and IndependentObjective approach to media measurement.

29Play Out Marketing What-if ScenariosAn interactive dashboard allows you to simulate

different marketing mix/spend scenarios and assess the resultant impact on sales and profitability.

1. Set marketing budgets.

2. Set your spend levels across media channels

3. Assess the resultant impact on sales & profit

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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, Masood was 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