The document discusses Rule 40 of the IOC, which regulates athlete sponsorships and social media use during the Olympics. It summarizes an analysis of Instagram posts by Nike, Adidas, and Under Armour during the 2016 Rio Olympics. While Nike had more total followers and engagement, Under Armour had higher engagement relative to its follower count. Statistical tests found significant differences in likes and comments between Nike and the other brands, but not between Adidas and Under Armour, suggesting Nike did not have a clear social media advantage as an official sponsor.

1. Introduction
The International Olympic Committee (IOC) adopted Rule 40 in 1991 to "preserve the unique nature of
the Olympic games by preventing over-commercialization" and protect sponsors who spend millions of
dollars for exclusive marketing rights. Preventing Olympians from hawking their own sponsors became
increasingly problematic in the run-up to the 2012 London Olympic Games due to Facebook and Twitter’s
emergence. Rule 40 was updated in 2015 so that unofficial sponsors could feature their athletes in
campaigns. However, using “Olympic-related terms”, official Twitter hashtags, logos, or referencing
Olympic location was prohibited. Athletes could be disqualified and stripped of medals if found in
violation of Rule 40.
Attorneys argue that hashjacking, using a hashtag for something different than its intended purpose, is
not trademark infringement because products or services are not being sold. Sally Bergesen, whose
apparel company Oiselle sponsored 15 Olympic hopefuls, feels Rule 40 is too restrictive and effectively
bars lesser-known athletes from earning money from their Olympic appearances. Zaileen Janmohamed,
SVP of Client Services for GMR Marketing, thinks the wider playing field could devalue Olympic
sponsorships.
Starting in late March and throughout the 2016 Rio Olympic Games, Origami Logic, a marketing analytics
company and global leader in marketing performance measurement, tracked Olympics-related social
activity of 40 brands, 38 worldwide and Team USA sponsors, and two non-sponsors (Adidas and Under
Armour), highlighting the results on a campaign microsite developed by their demand generation agency,
Spear Marketing Group. Origami Logic drove traffic to the microsite and campaign awareness through
ads on Google AdWords and LinkedIn. Microsite visitors could click through to learn more about
successful campaigns, engage with social media, and sign up to receive a “Brand Olympics” newsletter.
Results were also promoted on Twitter (@brandolympics) and using the hashtag: #BrandOlympics2016.
Materials and methods
Picodash, an advanced Instagram search engine and social media management tool that helps Brands,
Publishers, Researchers and Journalists search and curate Instagram content by location, hashtags and
places, was used to obtain Nike, Adidas and Under Armour posts between March 27, 2016, through
August 21, 2016, coinciding with the date non-sponsors were required to start advertising and ending on
the date of the 2016 Rio Olympic Closing Ceremonies. Previously known as Gramfeed, the transition to
Picodash complies with the new Instagram API Platform changes as of June 1, 2016, which no longer
permit 3rd-party apps to display public Instagram content to just anyone accessing the app. Picodash
provides its services via a paid subscription model, which includes a three-day trial period that does not
charge Instagram users if cancelled within aforementioned time frame, and charges an $8 monthly
subscription fee.
Based on communication with Picodash, although it was not publicly visible at the time, exporting data to
a spreadsheet was possible. Once posts were loaded from Nike, Adidas and Under Armour accounts in
Google Chrome, open console, (right click - inspect - console tab) and type exportMedia() to save as a csv
file. While both regression and classification models were explored, which proved to be a rather
frustrating experience, counsel from instructor prompted a change in direction since the data was
nowhere near 1,000 instances. As a result, two-sample t-tests were done in statistical software Minitab
17.
Acknowledgments
Special thanks to Vincent Malic for his invaluable counsel
during the course of this project and Picodash for having a
platform to work around Instagram API challenges.
Results Conclusions
While Nike had more followers, like and comments
than Adidas and Under Armour, they did not dominate
both likes/followers and comments/followers. Under
Armour, which has far less followers than Adidas, had
a much higher likes/followers score than both Adidas
and Nike, which were nearly identical. When
comparing comments/followers, although Nike had the
highest score of the three brands, substantially higher
than Adidas, there was very little separation between
Nike and Under Armour. Not only does the data
suggest that Nike did not have a huge advantage as
an Olympic sponsor, based on likes/followers and
comments/followers, Under Armour potentially had the
most engaging Instagram content.
Roderick Head
rthead@indiana.edu
Literature cited
Alba, D. (2016, August 12). Athletes Battle the Olympic Brass for the Right to Make Money. Retrieved
from Wired: wired.com/2016/08/olympians-take-back-social-media-rule40
Chavez, C. (2016, July 25). What is Rule 40? The IOC’s rule on non-Olympic sponsors, explained. Retrieved
from Sports Illustrated: http://www.si.com/olympics/2016/07/27/rule-40-explained-2016-olympic-
sponsorship-blackout-controversy
Chemi, E. W. (2016, July 28). Olympic committee on the prowl — for misuse of hashtags. Retrieved from
CNBC: http://www.cnbc.com/2016/07/28/olympic-committee-on-the-prowl--for-misuse-of-
hashtags.html
Origami Logic. (2016). Brand Olympics 2016 Report. Mountain View.
Origami Logic Scores Gold with “Brand Olympics” Campaign. (2016, August 16). Retrieved from thepoint:
http://spearmarketing.com/blog/origami-logic-scores-gold-with-brand-olympics-campaign/
Uyoe, I. (2016, June 2). IOC Rule 40: Olympic Sponsorship Achilles. Retrieved from LinkedIn:
linkedin.com/pulse/ioc-rule-40-olympic-sponsorships-achilles-heel-idy-uyoe
Future Directions
Due to conclusiveness of the data, no additional work is
needed to solidify the results.
N Mean StDev SE Mean
Nike Likes 32 384979 175936 31101
Adidas Likes 32 72384 15007 2653
Difference = μ (Nike Likes) - μ (Adidas Likes)
Estimate for difference: 312594
95% CI for difference: (248932, 376256)
T-Test of difference = 0 (vs ≠): T-Value = 10.01 P-Value = 0.000 DF = 31
N Mean StDev SE Mean
Nike Likes 32 384979 175936 31101
Under Armour Likes 32 23320 7591 1342
Difference = μ (Nike Likes) - μ (Under Armour Likes)
Estimate for difference: 361659
95% CI for difference: (298168, 425150)
T-Test of difference = 0 (vs ≠): T-Value = 11.62 P-Value = 0.000 DF = 31
N Mean StDev SE Mean
Nike Comments 32 2485 1538 272
Adidas Comments 32 165 187 33
Difference = μ (Nike Comments) - μ (Adidas Comments)
Estimate for difference: 2319
95% CI for difference: (1761, 2878)
T-Test of difference = 0 (vs ≠): T-Value = 8.47 P-Value = 0.000 DF = 31
N Mean StDev SE Mean
Nike Comments 32 2485 1538 272
Under Armour Comments 32 91 110 19
Difference = μ (Nike Comments) - μ (Under Armour Comments)
Estimate for difference: 2393
95% CI for difference: (1837, 2949)
T-Test of difference = 0 (vs ≠): T-Value = 8.78 P-Value = 0.000 DF = 31
T-tests are called such because the test results are
based on t-values, an example of what
statisticians call test statistics. The higher the t-
value, the lower the p-value, increasing the
likelihood of statistical significance between the
two groups. Coupled with a zero p-value, there is
a zero percent chance there is no significant
difference between Nike and Adidas and Nike and
Under Armour with both likes and comments. DF
refers to degrees of freedom, which is one less
than the sample size.