The Big Data behind Black Friday

Olivia Brookhouse    29 November, 2019

It is often the products that seem to have “come out of nowhere” that suddenly experience rocket sales and have everyone talking. Whether its health fads such as kombucha, trainers as heavy as bricks labelled the ‘chunky trainer’ or shapewear designed to help you resemble a Kardashian, we’ve seen it all. So how do companies know what’s going to sell and how to sell it?

With large supply chains, companies must be able to prove the future demand and therefore success of a product before it goes to market, and this is where Big Data can play an increasingly bigger role in predicting consumer behaviour. This is particularly important for the biggest shopping day of the year, Black Friday.

What is Black Friday?

The first record of the phenomenon of Black Friday began in Philadelphia in the US in 1952, the day after Thanksgiving. It has since evolved into the biggest shopping day of the year worldwide. In the UK in 2018, 64% of the population bought something on Black Friday equating to 42.5 million people and in Spain, 55.7% of the population participated, totalling 26 million people. The top-selling products on Black Friday are clothes, cosmetics, jewellery, shoes and electronics. With the incentive of getting a bargain, spending on Black Friday last year was on average £315 in the UK and €210 in Spain per person. However, the UK is providing better deals; with an average discount of 63% per product compared to 47% in Spain.

Whilst Black Friday began on local highstreets, the use of brick and mortar stores has reduced significantly in recent years. On Black Friday in the UK in 2018, 64% of shoppers made purchases both offline and online, 24% just online and 12% just in shops. In Spain, 43.4% of shoppers made purchases both offline and online, 40.22% just online and 16.3% just in shops.

Brands have had to react as consumer habits have changed. Because of the internet, the 21st century consumer is less loyal to specific brands and led primarily by price. Due to the availability of information online, consumers are more equipped than ever before to compare products across 100’s of brands. Because of this, platforms such as Amazon and ASOS are able to dominate in their respective markets because their platforms are able to showcase many cheap comparable brands.

How does Big Data predict consumer trends?

Previous marketing strategies included monitoring social media or analysing surveys without the ability to store, combine or optimize these data sources together. Big Data and AI allows companies to harness data from thousands of sources that can predict future purchase habits with a high degree of accuracy.

Algorithms are applied to find patterns within the mass of data, to provide insights which inform both internal decision making and improve the customer experience. This means companies are able to harness data from years of Black Friday sales to accurately select products and discount rates which will attract the masses.

Machine learning software is built within recommender systems on websites which, based on customers previous purchases, can predit what customers will want to buy next, offering them more in-tune suggestions. Internal decision making is no longer based on innacurate surveys on small focus groups but instead on human behaviour in real time.

The old methods that were invented before the digital era are not agile, precise or predictive enough

Tim Warner: Pepsico

It is vital that large companies are able to predict the popularity and therefore profitability of new products because large supply chains restrict them from introducing new products quickly. For many, this means deciding Christmas product ranges 9 months before the holiday season has started.

Start Ups like Black Swan are disrupting the way ordinary market research is done, analysing consumer purchase behaviour on a large scale to predict consumer trends for their clients. Unlike before, social media permits the mass spread of consumer trends promoted by influencers and celebrities alike. Some of the most common trends at the moment follow big social movements such as Veganism and Sustainability and there will definitely be an increase in related products this Christmas.

Big Data for Advertising

Whilst Big Data is vital to provide insights to design product ranges, it can also inform Advertising and Sales strategy. At LUCA we help our clients, with the use of anonymised and aggregated data to optimize their decisions and save costs. LUCA Business Insights solutions help locate prime locations for shops and advertisements to target the intended audience. LUCA can also provide insights within the retail location in order to optimize merchandise and displays to attract the desired client. This is particularly important at Christmas where many stores will compete to have the best window displays so companies must be showcasing the correct products for each location. By identifying how people behave in and around the retail points, brands can optimize their offline services.

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