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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
3
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%.
5
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
6
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
7
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
9
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.
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.
18
\
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
21
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
23
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
24
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
25
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%
26
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
27
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
28
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
30
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