Word of Mouth's Role in Driving Sales

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Presentation by Brad Fay of Keller Fay, Greg Pharo of AT&T and Matt Sato of Accenture at ARF AM 6.0

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  • Word-of-mouth and social marketing techniques have continued to grow in importance. Ive read stunning reviews from clients of the 1st 'SocioViral' marketing company, MagicBuz, which is producing dramatic results and an excellent ROI. Their approach includes engaging in conversations with communities where decisions are being made. After all, Nielsen says that 90% of consumers trust peer recommendations. Sounds like an interesting approach that shows some of the things discussed in this article. If youre interested in more, their site is www.magicbuz.com obviously.
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Word of Mouth's Role in Driving Sales

  1. 1. Word of Mouth’s Role in Driving Sales Greg Pharo Director, Market Research & Analysis AT&T Matt Sato Manager Accenture Brad Fay COO Keller Fay GroupJune 13, 2011ARF AM 6.0, New York, NY
  2. 2. Spending on WOM Rising Fast“Word of Mouth Marketing” and “SocialMedia” Are Among the Most Exciting NewTools in the Arsenal of Marketers Today $3,043 $2,572 $2,204 $1,918 $1,701 $1,543 $1,351 $981 $722 $487 $313 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 WOM Marketing Spending WOM Marketing ForecastSource: PQ Media
  3. 3. Does Word of Mouth Drive Sales?Questions Remain on Word of Mouth’s Rolein Generating Sales Does word of mouth directly influence sales volume, and to what extent? Where does word of mouth fit into the “owned- earned-paid” media model? Is it really a metric of interest to companies? #ARFAM6
  4. 4. Background - AT&T Marketing ROI AT&T is one of the nation’s largest advertisers Well-developed Marketing ROI program Uses Market Mix Modeling to optimize DMA- deployment of media – Partnered with Accenture and Mediaedge to develop advanced analytics capabilities for market mix optimization AT&T also tracks weekly and monthly brand awareness, attitudes, and usage with a multitude of market research studies #ARFAM6
  5. 5. Problem - “Metrics Clutter” AT&T’s tracking studies collect a constellation of market metrics: – Brand perceptions – Usage – Customer satisfaction – Literally hundreds of data series Management wanted to know which metrics – in addition to media - are most impactful on Mobility sales (i.e., “Gross Adds”) and on disconnects (i.e., “churn”) #ARFAM6
  6. 6. Methods - Create a PurchaseFunnel Model AT&T and Accenture created both a Purchase Funnel model which identifies which metrics are the most significant influencer Gross Adds The model also shows what other upstream metrics drive these key metrics #ARFAM6
  7. 7. Methods - Using a Two-stepProcess to Identify Key Metrics Analytical techniques are used to winnow the myriad of earned media metrics – Highly-related metrics were grouped together using a cluster analysis – A short-list of metrics that are most correlated with their group are selected These representative metrics are then input into a separate model – Reduces the burden of incorporating potentially hundreds of metrics – Ensures the earned media impact is not “diluted” by having related metrics in the same model #ARFAM6
  8. 8. Methods - SEM Modeling Traditional regressions  The SEM structure, used here, assume no interactions allows for interaction among among sales drivers sales drivers Brand Health Brand Health Gross Gross Paid Media Paid Media Adds AddsWord of Mouth Word of Mouth #ARFAM6
  9. 9. Methods -Measuring ALL Word of Mouth Keller Fay Group’s TalkTrack®, a national syndicated program measuring WOM in all forms Mode of Conversations – Over 3 in 4 conversations occur face-to-face Across All Categories The study involves 36,000 online consumers surveyed annually, Other – 100 every day 2% Face- – Yielding about 1,000 weekly mentions of to-Face brands; 350,000 per year 77% Online Respondents are representative of the 6% US population aged 13 to 69 Phone – use a diary to keep track of their brand 15% conversations, then complete an online survey to gather detailed information about these conversations – Quotas/weights by age, gender, education, race, etc. #ARFAM6
  10. 10. Finding - WOM Is a MajorDriver of Sales The number of positive WOM “mentions” in TalkTrack® proved to be one of the more powerful metrics directly influencing “Gross Adds” (sales) Unaided Advertising Awareness, a top-of-funnel metric, was also a strong driver of Gross Adds In turn, the Structural Equation Model identified which metrics influence Word of Mouth and Unaided Advertising Awareness Paid media drivers are also included, as they directly impact Gross Adds, Word of Mouth and brand health metrics #ARFAM6
  11. 11. Unaided Ad Awareness and WOM Are Two Strong Direct Influencers of Gross Adds Unaided Ad Awareness Word of Mouth- Positive Mentions Device Gross Adds perception #1 (non-customers) Strength of Network Relationship perception #1 (non-customers)StrongModerateWeak Provider Consideration #ARFAM6
  12. 12. The Model Also Identified Attitudinal Metrics Which Influenced Word of Mouth Customer Service Perception #1 Network Network Willingness to perception #2 Perception #3 Recommend Word of Mouth- Positive Mentions Strength of RelationshipStrongModerateWeak Gross Adds #ARFAM6
  13. 13. Word of Mouth Data Was “Clean” Enoughto Model, in Contrast to Online “Buzz” Data Word of Mouth variables were easily incorporated into the model In contrast, online “buzz” data proved difficult to incorporate into models – Computer-scored online buzz sentiment data did not prove to be as accurate as hoped – Online buzz may not always include all relevant online sites – WOM captures a broader spectrum of discussions; fewer than 10% of conversations are online #ARFAM6
  14. 14. Next, Word of Mouth Was Trialed inTraditional Market Mix Models AT&T next introduced Word of Mouth variables into traditional Market Mix Models – AT&T constructed market mix models for itself and key competitors – Each model uses Gross Adds as dependent variable – Media, pricing, product innovation, messaging performance, competitive, other relevant marketing/environmental factors incorporated as independent variables – Modeling Approach: Multiple regression analysis Word of Mouth proved to be a powerful and statistically significant sales driver in Mix Models – Word of Mouth explained 10%+ of sales volume – Paid Media remains #1 sales driver, driving ~30% of sales – but WOM is one of the top influencers of Gross Adds #ARFAM6
  15. 15. AT&T Conclusions Word of Mouth is an impactful, relevant variable for influencing sales in the Wireless category WOM metrics belong on a CMO dashboard as a key performance indicator #ARFAM6
  16. 16. AT&T Next Steps Leverage Word of Mouth data in other analytics projects, including tactical campaign analysis Deeper learning on paid media/WOM interaction Making it actionable: influencing conversations Work with research vendors to improve quality of online buzz data #ARFAM6
  17. 17. Keller Fay Observations AT&T analysis provides strong evidence that “conversation” should be a marketing objective – Today, about half of WOM is influenced by marketing, including 20% by paid advertising – These numbers ought to grow as marketers adopt word of mouth as an objective Ways to Stimulate WOM – Messages should be “talkworthy” and easy to share  Think about providing “triggers” – Targeting: Aim for consumers with larger social networks  Seek out “influencers” – Channels: Favor those that facilitate conversations  Not just “social media”, but any media that reaches people in a social context Pay-off: Conversation, advocacy, SALES #ARFAM6

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