Forecasting Nike’s Sales using Facebook Data
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings
Links
- http://openarchive.cbs.dk/bitstream/handle/10398/9448/2016-IEEE_BigData-NileSales_Facebook.pdf?sequence=1
Accepted author manuscript
This paper tests whether accurate sales forecasts for Nike are possible from Facebook data and how events related to Nike affect the activity on Nike’s Facebook pages. The paper draws from the AIDA sales framework (Awareness, Interest, Desire,and Action) from the domain of marketing and employs the method of social set analysis from the domain of computational social science to model sales from Big Social Data. The dataset consists of (a) selection of Nike’s Facebook pages with the number of likes, comments, posts etc. that have been registered for each page per day and (b) business data in terms of quarterly global sales figures published in Nike’s financial reports. An event study is also conducted using the Social Set Visualizer (SoSeVi). The findings suggest that Facebook data does have informational value. Some of the simple regression models have a high forecasting accuracy. The multiple regressions have a lower forecasting accuracy and cause analysis barriers due to data set characteristics such as perfect multicollinearity. The event study found abnormal activity around several Nike specific events but inferences about those activity spikes, whether they are purely event-related or coincidences, can only be determined after detailed case-bycase text analysis. Our findings help assess the informational value of Big Social Data for a company’s marketing strategy, sales operations and supply chain.
Publication information
Original language | English |
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Title of host publication | Proceedings of the 2016 IEEE International Conference on Big Data (BigData '16) |
Editors | James Joshi, George Karypis, Ling Liu |
Place of Publication | Piscataway, NJ |
Publisher | IEEE |
Publication date | 2016 |
Pages | 2447-2456 |
ISBN (Print) | 9781467390057 |
State | Published - 2016 |
Event | 2016 IEEE International Conference on Big Data - Washington, DC, United States Duration: 5 Dec 2016 → 8 Dec 2016 http://cci.drexel.edu/bigdata/bigdata2016/ |
Conference
Conference | 2016 IEEE International Conference on Big Data |
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Land | United States |
By | Washington, DC |
Periode | 05/12/2016 → 08/12/2016 |
Internetadresse |
- Predictive analytics, Big data analytics, Big social data, Event study, Nike, Facebook data analytics
Research areas
ID: 45692435