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Professor Barak Libai of Tel Aviv University looks at the latest research into the value and ROI of consumer WOM.
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Prof. Barak LibaiProf. Barak Libai 1
ASSESSING THE VALUE OFCUSTOMERS’ WORD–OF–MOUTH
Prof. Barak Libai
Tel Aviv University
WOM UK , London, April 2010
By 2010, most mangers are informed about the power ofcustomer word of mouth
Prof. Barak Libai
We also know that assessing the economiccontribution of word of mouth is critical
Understanding the real valueof customers
What is the “social value” of aperson?
Prof. Barak Libai 4
value of advertisingrealUnderstanding the
Prof. Barak Libai 5
• Valuing investments in social networksand social media in general
Planning and valuing WOMcampaigns E.g., should we target “influentials”?
Prof. Barak Libai
Yet for many, the way WOM turns into ROIstays a mystery
Prof. Barak Libai
Here are I will argue that:
The issue is not trivial. No “one number” or “one equation” youneed to know
We need to “speak CRM”. The WOM value measure (“socialvalue”) should be monetary: The effect on the value of the cashflows from other customers
We need to see the larger network. Because word of mouthcreates a complex effect, its impact should take into account thelarger social system, and not only close neighbors
We want to understand the value of time. Early is often MUCH better.
The value a customer brings us via WOM
Current Approaches
Indirect measures do no assess monetary value
Direct aggregate measures
Measures for a “social value” of a customer
Prof. Barak Libai 8
Indirect measures
A) How do customers talk? Or are willing to recommend?
E.g, Net Promoter Scores
Prof. Barak Libai 9
Prof. Barak Libai 1010
Keiningham, B Cooil, TW Andreassen, L Aksoy - Journal ofMarketing, 2007
Conclusions are not straightforward
B) How do customers listen? How did you hear of us? How much were you affected by word of
mouth?
Possibly used with brand equity measures
Recent research found that the long term value ofcustomers that had arrived via WOM was higher thanthat of customers that had arrived via advertising.
Prof. Barak Libai 11
Direct “aggregate” measuresHow word of mouth affects overall sales
Experiments Before and after a WOM campaigns
In different areas
Prof. Barak Libai 12
Advanced statistical regressions
Especially as data on sales, WOM activities and othercustomer data is available from websites
Issues of “identification”: For example, WOM may be affected by advertising which may
affect the level of WOM
People may behave the same because there are similar, or wereaffected by the same external phenomenon, and not becausethey talked
Prof. Barak Libai 13
The problems with the previousapproaches
We still do not understand the “how” in terms of valuecreation
Monetary value of the individual is not assessed
Prof. Barak Libai 14
Prof. Barak Libai
The “social value” of a customer
The extra monetary value a customer adds (or subtracts)to the firm due to social interactions with others
Three issues to be discussed: Lifetime Value, Network,Time
Issue 1: “where the money is”?
Prof. Barak Libai 16
The “regular” profitability of customers
Customer Lifetime Value (CLV) - the net present value(NPV) of the future cash streams from a customer
Prof. Barak Libai 17
Time
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The money that comes from a customer’sword of mouth is in other customers’
regular lifetime value!
Prof. Barak Libai 18
$
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Often, we consider the social effect of in acquiring newcustomers What is their lifetime value?
Do friends have a similar lifetime value?
But it can also be an issue of costs E.g., via reduced customer support in online communities
A case of customer “development”- cross sell or up-sell
Or affecting the probability of customer defection The effect of retention (defection) on customer lifetime value is
very strong!
Prof. Barak Libai 19
Where’s the money?
Reichheld: The Loyalty Effect
Recent research in the telecommunication industry
ברק ליבאי'פרופ-שיווק בתקשורת חברתית 21
Exposure to Defecting Neighbors - Defecting and Non-DefectingCustomers
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Mar08 Apr08 May08 Jun08 Jul08 Aug08 Sep08 Oct08 Nov08 Dec08
Average number ofdefecting neighbors
Month
Defectors
Non-Defectors
Prof. Barak Libai 22
How the social effect of a defection decreases with time
It can also be mere acceleration of cashflows
“Discount rate” plays a large role in customer lifetimevalue A customer starting to buy today may be worth much more than
a customer starting to buy later
Prof. Barak Libai 23
$
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My conclusion on this issue
The same way that CRM people start “talking social”
Prof. Barak Libai 24
Social people should start “talking CRM”
Issue 2: Where is the network?
Prof. Barak Libai 25
Prof. Barak Libai
The complexity of calculating person A’s social value
A
B C
Is it the “lifetime value” of the people s/he affected?
D
Prof. Barak Libai
The complexity of calculating person A’s social value
A
B C
How many of them could we get via advertising?
If this is the case, we should look only at savings in advertisingexpenses
D
Prof. Barak Libai
The complexity of calculating person A’s social value
A
B C
Person A ’s word of mouth may create a “chain effect”beyond the neighbors
D
Prof. Barak Libai
The complexity of calculating person A’s social value
A
B C
If A would not talk with B, C may do it in a later time
Is social value about “customer acquisition” or“customer acceleration”?
D
Prof. Barak Libai
The complexity of calculating person A’s social value
A
B C
Can we add the social value of A and B ?
D
Prof. Barak Libai
Conceptually, the real social value of a customerif weonlyor a group of customers) can be assessed(
Let the customer disappear And measure the change of the net present value of the whole social
system
Prof. Barak Libai
Can it really be calculated?
We are working on it !
I’ll next present a possible approach.
Prof. Barak Libai
Stage A- Collect data on real social networks
Prof. Barak Libai
Stage b: Based on these networks create simplesimulations in which products are sold to
connected customers
For example: what would happen if a new product wouldbegin to grow on such networks
Individual level simulations in which a “would-be-world”is created are sometimes called agent based models
Prof. Barak Libai
Stage 3: Conduct experiments
What is the profitability (NPV) of the system
If person A is there, or is not there
If we target “influentials” or random customers
If competition is strong or not
In the absence of tools such as agentbased models
Try to better understand social network analysis
Prof. Barak Libai 36ברק ליבאי'פרופ-שיווק בתקשורת חברתית 4
Prof. Barak Libai 37
•Degree Centrality -the number of direct connections a node has
•A node with high degree centrality is a “Hub”
•We can also differentiate between in and out degree
•Eigenvector centrality – Gives weights to the centrality of the nodes thatare direct connection ( the “degree”)
•Google’s “PageRank” is a variation on this
•Closeness centrality – the sum of shortest paths to all others
•The shorter the better
•Betweenness Centrality - How many shortest paths between otherspass through that person
Who is important to us?
Issue 3: The Value of Time ?
Prof. Barak Libai 38
My (and others’) research has repeatedly indicated thatbeing early in the market has long lasting effects due toword of mouth
Prof. Barak Libai 39
Prof. Barak Libai 40
0
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0 1 2 3 4 5 6 7 8 9 10
Loss($)
Year Since Introduction
Indirect effect
direct effect
VALUE OF ONE LOST CUSTOMER IN THE ONLINE BANKING INDUSTRY
WOM
Regularpurchases
Prof. Barak Libai
Some recent results on the social value of WOM“seeding” programs
Using agent based models based on 12 real networks
WOM programs create a real pioneering advantageamong competitors. The social value of a program canbe five time as much when a competitor does not have aprogram
It is very worthwhile to be first, and alone!
How much value a customer creates viaword of mouth?
What is “value”?
Even before that: What is “word of mouth”?
Prof. Barak Libai 43
The classic view of “word of mouth”
Prof. Barak Libai 44
?Online or Offline
The vast majority of recent knowledge on socialinteractions comes from online environments
Yet much of the action may still be offline
Prof. Barak Libai 45
Other, 2%
E-mail, 3%
IM/Text, 3%Chat/Blog, 1%
Face-to-Face,
73%
Phone, 17%
Source: OMD/Keller Fay Group proprietary report based on TalkTrack®, June 5th 2006 through February 3, 2008
Source: TheKeller Fay group
“Organic” or “Amplified”?
Can we transferknowledge from firmincentivizedcampaigns to “natural”word of mouth ?
Prof. Barak Libai 46
Kumar, Petersen and Leone, HBR2007
What about “observational learning?”
We may be seriouslyunder-estimating thevalue of socialinteractions!
Prof. Barak Libai 47
I use the term “word of mouth” (WOM)
But the issues covered largely include various kinds ofsocial interactions
Prof. Barak Libai 48