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Measuring Customer-Experience ROI with social media

Validates and describes a very innovative and powerful approach for measuring the customer-brand-experience using social media experiential commentary. Not only is this a brea-through, but demonstrates the importance and value of the CX for brands.

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Measuring Customer-Experience ROI with social media

  1. 1. 1 Measuring Customer Experience ROI with Social Media New Developments in Measurement and Analytics
  2. 2. 2 Let’s Get Started
  3. 3. 3 About 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
  4. 4. 4 Measuring 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
  5. 5. 5 Customer Experience Leaders Outperform the Market CX Leaders [VALUE] [CATEGORY NAME] [VALUE] CX Laggards [VALUE] 0% 20% 40% 60% 80% 100% 120% CumulativeTotalReturn Eight-year Stock Performance of Customer Experience Leaders vs. Laggards vs. S&P 500 (2007-2014) CX Laggards In 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 Leaders Over 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,
  6. 6. 6 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
  7. 7. 7 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 TheyAren’t Sure How To Measure It
  8. 8. 8 TheAnswer 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
  9. 9. 9But Most Social Media Sentiment Ratings Are Not VeryAccurate "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
  10. 10. 10 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
  11. 11. 11 One 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
  12. 12. 12The BLASocial 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 Measuring language for brand insights Social media advanced analytics Social 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
  13. 13. 13 SEITM SEITMStance Shift Syntax & Structure Tonality & Sentiment Context Custom Dictionary AMore 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 E x R x P r Customer Experience & Engagement Rational
  14. 14. 14 The Difference Is Stance-shiftAnalysis, AMethod That Measures What Really Matters In Language • Stance-shiftanalysis,publishedandpeer-reviewed,revealswhatreallymatterstotheconsumer: – Stance-shiftmeasuresconsumers’verbalshiftsinpositioning astheytalk. – Wecapturetheemotion,intensity,appraisal,andcommitmentinthecontextoftheconversationstouncoverthedeepsubtleties andwhatissaid. • Itenablesustosolvewhatothersmiss:Size,TrendandNewConcepts – Focusingonlyonwhatmatters:Wefilterandsizerelativeimportancethroughengagement–farsuperiortosimplewords/comment frequency. – Consumertrends:Wecapturetheshiftsandprioritizegettingthetrendright,validatedthroughtheindependentmeasureofour metricsvssales. – Stanceistunedtodetecttopicsandconcepts,whichwelinktoquantifiedopinions,evaluationsandendorsementsthroughadaptive tonality,allowingustomapstrengths,weaknesses,opportunities&threats. • SemanticEngagementIndex:SEITM integrates ourstance-shiftmeasurementtopowerourconsumerinsights.
  15. 15. 15 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
  16. 16. 16 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-StanceAnalysisAccounts For Context, Industry TerminologyAnd Channel-Specific Language
  17. 17. 17 Our Process Brings Structure To Consumer Data Chaos From millions of cleaned social media conversations We detect thousands of interesting “nodes” of consumer information Our supervised learning pattern detection organizes the nodes Small Pepermint Afternoon Snack 12Pack Great Deal Breakfast yum Large Miss it Get me one Orange on sale Morning Half Priced got coupon Drive Home Vanilla Mocha 8Oz need a hit Clear themes and topics of importanceemerge Powerful social insights on themes and topics that are most important to consumers Advanced analytics to help drive content strategy and measure social ROI
  18. 18. 18The Correlation to Sales Over Time Shows the SEI™ Has Strong Predictive Power 18 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 & Bev Brand 83% Hospitality Brand
  19. 19. 19The SEITM Has Been ValidatedAcross 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 Brands Validated more than any other social metric
  20. 20. 20The SEITM Has Broad-based Application $ Monitor and manage consumer conversations that 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 and the customer experience with our media mix models
  21. 21. 21 Case 1: Defining the Coffee Retailer Brand and Position
  22. 22. 22 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 people 188 Atmosphere 288 Atmosphere 466 Note: Separate analysis - Classification & Regression Trees (CART) Positive Social Engagement 100 To meet people 229 Place to hang out 83 Beverage A 271 Beverage A 74 To meet people 85 To meet people 325 Insight & Outcomes Key drivers to positive SEI™: 1. A place to hang out 2. To meet people 3. 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 out 211
  23. 23. 23 Case 2: Social Content Drivers for Brand Positioning
  24. 24. 24 SEITM 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 Contributions Baseline SEI/Mktg Synergy SEI-Social Media Radio POS Signage TV Digital Display Sampling Pub.Reltns OOH Zip’s Marketing Contributions By 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.
  25. 25. 25 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 2/23/2009 3/23/2009 4/23/2009 5/23/2009 6/23/2009 7/23/2009 8/23/2009 9/23/2009 10/23/2009 11/23/2009 12/23/2009 1/23/2010 2/23/2010 3/23/2010 4/23/2010 5/23/2010 6/23/2010 7/23/2010 8/23/2010 9/23/2010 10/23/2010 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.
  26. 26. 26 188 3,516 103 128 300 301 350 491 724 930 - 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 BaselineNetPositive SEI GreatAroma YummyFlavors GreatGiftIdea Convenient TastesGreatColdor Hot TastesGreat GreatforTakingtothe Office TastesLiketheReal ThIng TotalNetPositiveSEI 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 Optimized Positioning By focusing its communications toward these benefits, Zip managed to continue a strong 11% growth in Year Two.
  27. 27. 27 Case 3: Scoring and Evaluating Sports Sponsorships
  28. 28. 28 Assessing the ROI of Sport Sponsorships This 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 NFL could 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.
  29. 29. 29 Social Media ROI Marketing Mix Modelling Pricing Optimization Radial Landscape Mapping Key Drivers Analysis Demand Forecasting Customer Satisfaction Modelling Digital Performance Analytics Dashboards Segmentation Analysis BLAIs a TrustedAdvisor to a WideArray of Clients We believe in the continuous innovative application of analytics to advance customer-centric decision making for improved business performance.
  30. 30. 30 Our Leadership Team
  31. 31. 31 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 Wolfe David 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 Weinberger Masood 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-LineAnalytics Leadership
  32. 32. 32 EMEA Office: 5th Floor, 39 Deansgate, Manchester, M3 2BA, United Kingdom Contact Us US Office: Suite 100, 1780 Chadds Lake Dr, NE Marietta, Georgia, 30068-1608 Atlanta, USA