What is Black Friday
Black Friday is one of the biggest and busiest shopping days of the year in the United States.
The day is usually marked by endless shopping and shoppers’ frenzy. Deals, sales & bargains, hysteria, and a bit of name-calling. An average shopper is expected to spend at least $1000. Last year alone, Black Friday marked a record $7.4 billion in second largest online sales day ever, only second to 2018’s Cyber Monday record holder at $7.9 billion. This year, Friday, November 27, 2020 might be no different as adults in the US are expected to drop a total of $148.5 billion on Black Friday and Cyber Monday.
Big Data & Black Friday
A few things drive the success of Black Friday and consequently Cyber Monday: The discounted prices play a big role in attracting consumers; more people are getting comfortable with buying online to avoid crowded stores especially with the pandemic and there is an insane amount of consumer data being collected to predict buyers’ behavior.
The rise of online sales and Big Data has ameliorated predictive analysis of what people would want to buy through the collection of historical shopping data. Data collected from tracked consumers as they browse through websites is stored for such analyses. This can be the items you view as you scroll and browse on the internet, how long you view specific items, those you add to or remove from your cart or the stuff you end up buying. This information is then used to build machine learning models that test and predict what you are likely to purchase as well as to conduct target advertising.
Studying this data reveals patterns, popular items, and trends that can be used to establish consumer behavior and predict future demands. One of the biggest problems for traditional and online retailers is managing their inventory especially on a day when they are expecting a massive influx of human traffic on their websites and in their stores. Knowledge of on-demand items alleviates this mystery and helps them manage what to display more efficiently. Your retailer probably knows about you even beyond your shopping habits than you know about yourself. The machine learning algorithms have only gotten better since last Christmas.
Although the spending volume might be lower this year because of Covid-19 and unemployment, data analytics is still useful in predicting and anticipating such potential shifts in consumer behavior. Big Data plays a fundamental role in tailoring online and traditional retail shopping to meet the buyer’s needs and interests. E-commerce platforms collect your shopping data, browsing habits and online activity with or without your consent to “customize” their advertising. Your personalized shopping experience might make you feel recognized and appreciated, but is the data trade-off perhaps an even better bargain for the retailers than it is for you?