By Enyu Fan, Danni Long, Zhuokun Liu, Zihao Liu
Big data refers to an accumulation of all valid information in a period of time, which could take up to Zettabytes, taking the related portion for the future potential using. Online shopping is an example in data utilizing. If you try to open a page on Taobao, a typical B2C platform, you would find out that the products combinations have 1000 visions on 1000 people’s screen. There is an algorithm behind it, which collects all history reviews and sends it back to the back stage. From there, it draws pictures from your purchasing habit and differentiates target markets with people who share similarity with you. Therefore, you would easily see similar products you searched before on the homepage of Taobao.
What’s more, the data could analyze your next movement, based on similar human behaviors. For instance, it could draw a conclusion of pregnancy from vitamin E, vitamin B9 and non-chemistry facial cream purchasing records, which usually was bought in the first 2-3 months of pregnant period. Then there may be gift cards of some baby-related product showed up in your email. After purchasing online for a long time, there is an official credit record for your own, showing your capacity of purchasing. Then it comes up with online credit card, which is not really a card but it contains actual money, and the credit limit depends on your records. There will not be man-made errors on 10000,000 people’s credit limits since they are based on a neat and flawless algorithm. From there, it could derive a lot of things in that personal data tells more reliable truths.
Big Data in B2C Advertising
Upon browsing the Amazon, we can always find goods that we searched before, some of which are pretty useful and fill in our interests. This is a marketing strategy applied with big data and it plays an important role in e-commerce. Companies use this strategy to improve the marketing efficiency and provide people with more customer-oriented items, thus satisfying customers (Jobs, C. G., Gilfoil, D. M., & Aukers, S. M., 2016). However, the privacy becomes a controversial topic. The data from people may be an open resource that some with bad intentions would exploit it. Companies, to give a safe purchasing environment, use algorithms to add “noises” to the data so that the private information can be obscure (Economists, 2014).
Ways to enhance efficiency
Currently most companies are working on the optimization of data analysis procedure and data management approaches (Raisch, W., & Foreword By-Gartner, G., 2000). New opportunities will emerge along with new calculation methods, better data collection method and artificial intelligence.
While we do have technologies like hyper-thread, double float precision calculation and virtual machine, data analysis burden is gradually exceeding the capacity of calculation. Quantum computing provides a solution to the case, but it is still in the laboratory phase.
Better data collection approaches can help the system deal with data burdens, especially during data peaks. Advanced AI provides preprocessing of the data and great relief to data analysts.
The exponentially growing e-market aroused the concern of Internet tycoons: Alibaba, eBay, Amazon, etc. Capital rushed into this burgeoning industry, which changes people’s lives unprecedentedly. Under this big circumstance, e-commerce companies have opportunities to nurture a compact relationship with customers. Using big data marketing strategy on mobile terminal and offline service, companies can thus upspring in the future.
Background – Danni Long
Big Data in B2C Advertising – Zhuokun Liu
Ways to Enhance Efficiency – Enyu Fan
Opportunities – Zihao Liu
SWOT Analysis – The Whole Group
Jobs, C. G., Gilfoil, D. M., & Aukers, S. M. (2016). How marketing organizations can benefit from big data advertising analytics. Academy of Marketing Studies Journal, 20(1), 18-35.
Hiding from big data. (2014, June 7). Retrieved from http://www.economist.com/news/technology-quarterly/21603233-it-security-increasing-commercial-use-personal-data-and-multiple
Raisch, W., & Foreword By-Gartner, G. (2000). The eMarketplace: Strategies for success in B2B eCommerce. Location: McGraw-Hill Professional.