The Value of Direct Individual Endorsements

The Value of Direct Individual Endorsements • March 2015
The Value of Direct Individual
Endorsements
Sanford Morton∗
Tommy Fad†
March, 6th 2015
Abstract
In an industry where celebrity endorsement dominates the advertising landscape, is it possible that the
pay-off from direct individual endorsement is being largely overlooked? Research to date has thoroughly
explained the impact of celebrity scale endorsements on stock returns as well as sales. However, academia
has yet to analyze the impact of individual endorsements on similar business related metrics. The results of
this inquiry on the value of individual endorsement finds that consumer purchasing decisions are heavily
influenced by individuals, when compared to celebrity counterparts. Insights regarding this result are
covered in the Conclusion section.
I. Introduction
In an industry where celebrity endorsement
dominates the advertising landscape is it
possible that the pay-off from direct individ-
ual endorsement is being largely overlooked?
Globally and within the US an increasing
trend in the number of marketing campaigns
that involve celebrity endorsements has been
recorded. Research has shown that in markets
where this increasing trend has reached a sat-
urated equilibrium consumer behavior shifts
and traditional endorsements no longer influ-
ence their decision making [3].
In the past, market conditions and technol-
ogy limitations made a direct form of endorse-
ment unfeasible. Businesses already had the
training and structure to comfortably handle a
small number of larger contracts, so endorsing
celebrities was a natural decision. Creating a
structure through which individual endorse-
ment could be possible would have been a ma-
jor logistical undertaking. Moreover, before
the social revolution individuals had small un-
traceable networks - rendering any attempts
to track impact impossible. However recently
many of these factors have been shifting. In-
dividuals have larger networks supported by
online social technologies. These technologies
not only support the equilibrium size of social
networks, but also simultaneously provide the
ability to quantify impact and automate con-
tract agreements between the individual and
the corporation. The advertising space also con-
tinues to become saturated with endorsements.
As this trend continues, the marginal value of
celebrity endorsement decreases, as consumers
begin to view endorsement as commonplace.
What follows is research on the likelihood
of an individual to purchase a product based
on influence from traditional professional ath-
lete endorsements versus influential individu-
als in their social and digital network.
∗sanford.morton@duke.edu | Student at Duke University
†tommyfad@gmail.com | Founder of Gritness, Inc.
1

II. Definitions
I. Reach
Reach has traditionally been measured for
mediums such as television, radio and even
film. For example, the BBC defines their broad-
casting reach using BARB (Broadcasters’ Audi-
ence Research Board). BARB states a specific
time period must be defined (and met) to be
considered in their reach calculation. By way
of illustration, 3 minutes or 15 minutes of view-
ing could be the measurement for a particular
reach. BARB also defines a household member
as someone who is 16 years of age or older. [1]
However, reach has come to mean different
things in the digital age and currently there
is no true standard for measuring this in the
digital space. For purposes of this paper, a fo-
cus is not placed on quantifying reach. Instead,
the focus is placed on likelihood of purchase
(for an individual). While reach is not being
discounted, the co-authors’ research for this
paper places the target consumer in a very nar-
row, addressable market. This target market is
defined by the following:
• American
• Has access to a smart phone
In reality, the digital audience is much larger.
Indeed, a user with access to a laptop or desk-
top computer is subject to digital advertising
but, for this particular analysis, was not consid-
ered as part of the addressable market. Based
on this definition of reach, any given brand
with a large enough budget would be able
to reach the same addressable audience as a
professional athlete or celebrity. Ultimately, it
comes down to where marketing dollars are
spent in the advertising strategy.
What follows is a summary of how to
roughly calculate the reach of a strategy. The
population of Americans who are 20-24 years
old and have access to a smart phone is
17,947,010 [5]. This is roughly 80% of the to-
tal addressable market, where the addressable
market is the entirety of Americans 20-24 years
of age (whether or not they have a smartphone).
Using this 17,947,010 figure as a network of
nodes, with each person representing a node,
a reach calculation can be applied for each
node in this network, since the network size is
known.
As there is no standard for measuring reach
in a digital market, it follows that determin-
ing the numeric value assigned to the reach
of an influential node in the given network is
difficult. While popular social network sites
typically have influential individuals with thou-
sands (or even millions) of followers or friends,
an alternative science to defining this reach can
be traced back to Dunbar’s definition of a sta-
ble cognitive relationship being limited to 150
nodes.[2]
The survey used for this paper grouped
influence from the following categories:
• Professional Athlete
• Acquaintance
• Close Friend
Based on these categories, reach can take
on different definitions. For example, it is prob-
ably reasonable to believe that an influential
node’s reach to his/her family and friends is
more closely judged with Dunbar’s number, as
this assumes that a strong personal relationship
exists. However, an acquaintance, by definition,
has a less intimate relationship. Likewise, the
percentage of the American population which
actually has a personal relationship with a pro-
fessional athlete is extremely low. Therefore,
the reach of an influential node, classified as
an acquaintance or professional athlete, can
use data attributed to the node’s followers and
likes in the node’s digital social network; since
there is less concern with a stable cognitive
relationship.
When a brand determines who an influen-
tial node/individual is for its given campaign,
the brand must make the investment in the
individual first. The digital medium for how
the influential promotes the brand/product
is secondary. For example, it is estimated
that Facebook’s cost to reach 1,000 people
2

is roughly $0.25. However this is just a tra-
ditional digital advertisement and does not
account for using an influential person to pro-
mote the brand/product. Therefore, reach
as defined by Facebook’s advertising orga-
nization, can mean something completely
different than, say, Google’s AdWords. An-
other important thing to mention is the fact
that digital advertisements have been los-
ing traction with consumers. The Red Bull
West Business unit manager discusses this
trend in a talk given at the Fuqua School
of Business, in which he characterized the
daily experience of a consumer: "a consumer
on average will see 3000-6000 brand adver-
tisements per day".[7] This is a nauseating
number, and the simple conclusion was that
"traditional brand advertisements no longer
have relevance in a digital landscape" [7].
II. Likelihood To Purchase
As explained in the reach section, this paper as-
sumes that the addressable market is reachable
by both the professional athlete and the influen-
tial node in the network model. The likelihood
of purchase calculation thus becomes the per-
centage of likelihood to buy (based on survey
results), multiplied by the addressable market
(note that the table segments the market based
on age). The higher likelihood of purchase
rates clearly show that on average, addressing
the influential node leads to a higher likelihood
to purchase than a celebrity or professional ath-
lete endorsement.
In terms of a digital marketing strategy
from a budgetary standpoint, it is crucial to
determine the cost that will be spent on influ-
ential nodes. The survey used in this paper
specified apparel and equipment as the focus;
specifically on the sports and fitness industry.
Since the cost of endorsement by an influential
node is variable, it would be worthwhile for a
brand to research what this cost (per node) is
and how it changes with other variables, such
as: age, sport, geographic location, etc.
III. Methodology
A two part approach was taken to analyze the
magnitude of each strategy. In the case of the
direct individual endorsement demographic
data was taken describing the number of indi-
viduals in the US broken down by age range [4].
The study focuses on the US because this is the
source from which the data was most readily
available. From this data, a subset describing
the number of users who also use smartphones
is calculated [5]. The next logical step was to
multiply by the mean probability of an action
being taken by a person acquainted with the in-
dividual endorser. However, no data currently
exists to describe this probability. Therefore, a
survey was created that targeted active individ-
uals to gather information which could be used
as a representative estimator for the "likelihood
of purchase" probability distribution. Finally,
the quantified likelihood of purchase can be
calculated for each age range. This total rep-
resents the number of people who would act
on purchasing a product if every single influ-
ential individual were to endorse a product to
their entire network. This analysis is located at
Table 1.
When performing this magnitude calcula-
tion, it was understood that open data does not
exist on celebrities and athletes, which could re-
sult in a completely generalized result. For the
sake of having a comparison, a single celebrity
endorsement scenario was selected to represent
the general strategy. The National Basketball
Association (NBA) was selected for this sce-
nario because of its historic prevalence within
the U.S. and because of recent public contracts
that provide a baseline for the total investment.
3

Figure 1: Bar graph depicting the proportion of "yes" responses received for each question. The questions are grouped
by influencer.
IV. Results & Discussion
Results from the poll show that individuals are influenced significantly more by friends than by
celebrities. The proportion of "Yes" responses for each question and age range is located at Figure
1. This result is not highly surprising, one could suspect a consumer would be influenced more by
a friend with whom he/she is close, than by a celebrity. However, this does not fully answer the
original question. The magnitude of reach must be taken into consideration when evaluating the
value of each strategy. While it can be true that individuals are more influential than celebrities,
celebrities will inherently reach a much larger audience. So even with a lower likelihood of
purchase probability, a celebrity gains value through the sheer magnitude of consumers to whom
he/she can broadcast. These two competing factors, reach and influence, must be analyzed to
conclude what strategy proves more valuable.
As discussed in the methods section, for the sake of comparison, the magnitude analysis that
follows is restricted to a specific case for the celebrity endorsement and individual endorsement
strategies. Because of this, the calculations that follow roughly represent the analysis that a
practitioner might undergo to determine what strategy is most applicable.
I. Magnitude of Direct Individual Endorsement Reach
The following outlines how the total number of nodes who are likely to purchase is calculated
for this individual strategy. First, the total number of individuals who could potentially become
endorsers is calculated from demographic and smartphone data. From there, the percentage of
consumers that would act on recommendations from these individuals is calculated using results
from the poll that can be seen in section I of the appendix. Table 1 shows this calculation for each
4

age group, along with totals. Age groups above 60 were not considered because of low response
rates.
Friend Acquaintance Celebrity
Age US
Pop
[4]
Smart
Phone
Users
(%) [5]
Nodes LTP
(%)
EP LTP
(%)
EP LTP
(%)
EP
15-19 22758890 50% 11379445 87% 9900117 33% 3755217 47% 5348339
20-24 22433763 80% 17947010 83% 14896018 61% 10947676 52% 9332445
25-29 21783509 81% 17644642 52% 9175214 45% 7940089 48% 8469428
30-34 20808128 81% 16854584 71% 11966755 43% 7247471 11% 1854004
35-39 20483001 69% 14133271 77% 10882619 42% 5935974 23% 3250652
40-44 21133255 69% 14581946 77% 11228098 46% 6707695 38% 5541139
45-49 22433763 55% 12338570 73% 9007156 45% 5552357 45% 5552357
50-54 22108636 55% 12159750 20% 2431950 20% 2431950 40% 4863900
Table 1: Likelihood To Purchase (LTP) calculation for direct individual endorsement. Likelihood To Purchase Multiplier
derived from constructing a rough estimator based on polling results. EP represents the number Expected
Number of Purchases based on the defined audience multiplied by Likelihood To Purchase.
This table can then be used to calculate the effectiveness of a campaign given an initial investment.
This calculation can be seen in the comparison section.
II. Magnitude of Celebrity Endorsement Reach
As discussed in the methods section the reach of a specific strategy within the NBA was focused on.
The total potential reach for an NBA strategy was calculated using Neilson ratings and household
demographic data with the following equation:
total reach = (average NBA Neilson rating) * (# households per Neilson point) * (# people per household)
(1)
total reach = (9.54) ∗ (931000) ∗ (2.55) (2)
total reach = 22, 648, 437 consumers (3)
III. Magnitude of Acquaintance Reach
As discussed in the definition section, reach in a digital network has no standard definition.
Furthermore, this paper assumes that a "close" relationship (friend of family) should use Dunbar’s
number as a network multiplier when discussing reach. Determining reach by using follows or
likes can be difficult for a number of reasons. Having a specific number of followers or likes
does not equate to that particular number in terms of reach. Therefore, the following calculation
is done with the assumption that an "influential" acquaintance (but not a professional athlete)
has a reach larger than 150 to their followers. While some users of these social networks have
hundreds of thousands (if not millions) of followers, the number below is assumed to be somewhat
conservative.
total reach = (# of influentials) * (# reach of each influential) (4)
5

22, 648, 437 = x ∗ 3, 000 (5)
# of influentials = 7, 549.48 (6)
The equation above assumes that an "influential" can reach 3,000 individuals. Since there are
no data on the reach of "influentials," this number is estimated. Brands typically have a 4.21%
engagement with their Instagram followers[8]. So a big name athletic brand has a reach a reach
of 555K (based on 13.2M followers, multiplied by 4.21%). If a big name NBA athlete has 4.2M
followers on Instagram, then this would put his reach (treating him closer to a brand and using
the 4.21%) at roughly 177K. Therefore, 3,000 as a reach for an individual influencer who is a non
professional athlete, is not unrealistic.
IV. Comparison
As previously stated, broadcast ratings are done over a specific time period. So if an NBA athlete
has a $300M endorsement contract over 10 years and appears solely on games on TV, at an average
of 30 games per year, then the cost to reach the audience in a broadcast medium is almost $1M
per game. If a brand wants to reach a similar audience via a digital marketing campaign, then the
brand would have to engage 7,550 influencers. Even if the brand’s cost to do this was $100 per
influencer, the brand would still be below the cost to endorse a professional athlete, and have a
higher likelihood of purchase.
V. Conclusion
For some age groups, the average likelihood of a consumer purchase is significantly higher
when individuals are influenced by acquaintances and personal friends, versus influence from a
professional athlete. However, often there is a limited number of professional athletes who can
propel a brand’s signature line by measures which far exceed the dollars invested in them by the
brand. This small group of athletes are typically the best of the best and make up a very small
percentage of the whole, thus making a risky bet for the brand.
Brands that implement a strategy of using influential nodes in their marketing campaign
should also measure the influence of the nodes/individuals with quantifiable data. There is no
standard measurement to define reach in the digital space, but this paper ties reach closely to
relationships. Quantitatively measuring the reach of influential individuals is crucial to judging
the financial effectiveness of a marketing strategy that employs these principals. Making more of
these marketing strategies digital actually gives the brand the ability to quantify the effectiveness
of reach with actual measurable data.
References
[1] BBC Audience Information Context & Glossary (Document 2) [Online] [Accessed on 18th
March 2015] http://www.bbc.co.uk/
[2] Abramiuk, Marc A. "The Foundations of Cognitive Archaeology" Massachusetts Institute of
Technology(2012): 240.
[3] Millard Brown. (2012) What are the Benefits of Celebrity-Based Campaigns? [Online] [Ac-
cessed on 4th March 2015] http://www.millwardbrown.com/
[4] Social Isolation in America: Changes in Core Discussion Networks over Two Decades
American Sociological Review June 2006 71: 353-375
6

[5] Edison Research. (2014) Smartphone Ownership Demographics. [Online] [Accessed on 1st
March 2015] http://www.edisonresearch.com/
[6] Hernando, A.; Villuendas, D.; Vesperinas, C.; Abad, M.; Plastino, A. (2009). "Unraveling the
size distribution of social groups with information theory on complex networks". Preprint.
arXiv:0905.3704.
[7] Webb, Christian Patino(2015). "Product Management and Strategic Marketing." Lecture. Duke
University - Durham, North Carolia. March, 16 2015.
[8] Forrester. (2014) Instagram Is The King Of Social Engagement. [Online] [Ac-
cessed on 22nd March 2015] http://blogs.forrester.com/nate_elliott/14-04-29-
instagram_is_the_king_of_social_engagement
7

VI. Appendix
I. Poll Proportions by Age Group and Question
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11
All 0.4* 0.48 0.72* 0.41* 0.45 0.69* 0.92* 0.62* 0.56 0.65* 0.38
15-19 0.47 0.33 0.87* 0.47 0.40 0.67 0.93* 0.80* 0.53 0.67 0.47
20-24 0.52 0.61 0.83* 0.51 0.65* 0.62* 0.93* 0.72* 0.54 0.70* 0.48
25-29 0.48 0.45 0.52 0.34* 0.50 0.77* 0.86* 0.61 0.59 0.59 0.32*
30-34 0.11* 0.43 0.71* 0.40 0.14* 0.69* 0.94* 0.60 0.63 0.63 0.26*
35-39 0.23* 0.42 0.77* 0.38 0.35 0.81* 0.96* 0.62 0.62 0.73* 0.46
40-44 0.38 0.46 0.77 0.46 0.38 0.77 0.85 0.54 0.46 0.46 0.38
45-49 0.45 0.45 0.73 0.36 0.45 0.64 0.82 0.55 0.45 0.64 0.36
50-54 0.40 0.20 0.20 0.20 0.40 0.40 1.00 0.20 0.40 1.00 0.20
55-59 - - - - - - - - - - -
60-64 - - - - - - - - - - -
65-69 - - - - - - - - - - -
Table 2: Descriptive statistics for poll where the proportion is calculated as (# yes)/(# no + # yes). An asterisk is used
to denote significance with α = 0.05.
II. Poll Structure and Format
Social Media Questions
Q1 Has a professional athlete’s social media presence led you to purchase equipment or
apparel for your fitness routine?
Q2 Has the social media presence of someone you arent acquainted with led you to purchase
equipment or apparel for your fitness routine?
Q3 Has the social media presence of a close friend led you to purchase equipment or apparel
for your fitness routine?
Q4 Has the social media presence of a family member led you to purchase equipment or
apparel for your fitness routine?
Advertisements
Q5 Has the commercial, print, or broadcast presence of a professional athlete led you to
purchase equipment or apparel for your fitness routine?
Word of Mouth
Q6 Have in person recommendations from a person you aren’t acquainted with led you to
purchase equipment or apparel for you fitness routine?
Q7 Has a close friends personal recommendation of equipment led you to purchase equip-
ment or apparel for you fitness routine?
Q8 Has a personal recommendation from a family member led you to purchase equipment
or apparel for you fitness routine?
During a Fitness Activity
8

Q9 While playing a sport have you seen someone you don’t know use equipment or apparel
that you later considered purchasing because they performed well?
Q10 While playing a sport have you seen a close friend use equipment or apparel that you
later considered purchasing because they performed well?
Q11 While playing a sport have you seen a family member use equipment or apparel that
you later considered purchasing because they performed well?
9

The Value of Direct Individual Endorsements

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