word of mouth's role in driving sales
DESCRIPTION
Presentation by Brad Fay of Keller Fay, Greg Pharo of AT&T and Matt Sato of Accenture at ARF AM 6.0TRANSCRIPT
Brad Fay COO Keller Fay Group
Matt Sato Manager Accenture
Director, Market Research & Analysis AT&T
Word of Mouth’s Role in Driving Sales
Greg Pharo
June 13, 2011
ARF AM 6.0, New York, NY
Spending on WOM Rising Fast
Source: PQ Media
$313 $487
$722
$981
$1,351 $1,543
$1,701 $1,918
$2,204
$2,572
$3,043
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
WOM Marketing Spending WOM Marketing Forecast
“Word of Mouth Marketing” and “Social Media” Are Among the Most Exciting New Tools in the Arsenal of Marketers Today
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Does Word of Mouth Drive 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?
Questions Remain on Word of Mouth’s Role in Generating Sales
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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
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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”)
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Methods - Create a Purchase Funnel 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
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Methods - Using a Two-step Process 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
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Methods - SEM Modeling
Traditional regressions assume no interactions among sales drivers
The SEM structure, used here, allows for interaction among sales drivers
Gross Adds
Paid Media
Brand Health
Word of Mouth
Gross Adds
Paid Media
Brand Health
Word of Mouth
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Methods - Measuring ALL Word of Mouth
Keller Fay Group’s TalkTrack®, a national syndicated program measuring WOM in all forms – Over 3 in 4 conversations occur face-to-face
The study involves 36,000 online consumers surveyed annually, – 100 every day
– Yielding about 1,000 weekly mentions of brands; 350,000 per year
Respondents are representative of the US population aged 13 to 69 – use a diary to keep track of their brand
conversations, then complete an online survey to gather detailed information about these conversations
– Quotas/weights by age, gender, education, race, etc.
Mode of Conversations
Across All Categories
Face-to-Face
77%
Phone 15%
Online 6%
Other 2%
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Finding - WOM Is a Major Driver 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
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Unaided Ad Awareness and WOM Are Two Strong Direct Influencers of Gross Adds
Unaided Ad
Awareness
Word of Mouth-
Positive Mentions
Device perception #1
(non-customers)
Network perception #1
(non-customers)
Provider
Consideration
Gross Adds
Strong Moderate Weak
Strength of
Relationship
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The Model Also Identified Attitudinal Metrics Which Influenced Word of Mouth
Gross Adds
Word of Mouth- Positive Mentions
Willingness to
Recommend
Customer Service
Perception #1
Network
Perception #3
Network
perception #2
Strong Moderate Weak
Strength of
Relationship
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Word of Mouth Data Was “Clean” Enough to 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
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Next, Word of Mouth Was Trialed in Traditional 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
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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
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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
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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