How Data Science increased the profitability of the e-commerce industry?
Data Science helps businesses provide a richer understanding of the customers by capturing and integrating the information on customers web behaviour, their life events, what led to the purchase of a product or service, how customers interact with different channels, and more.
By Khushbu Shah (DeZyre).
Data Science in E-commerce
With the world immersed in data from disparate sources, every time you click your mouse to purchase something, the information trail (data ) is captured and stored which is used in future by retailers to attract you to make more purchases. For example, if you are a customer looking to buy a new phone, mobile websites or apps have information of what products you viewed, Google has information about what products you searched for and GSMArena (a popular smartphone reviews website) knows what mobile phone reviews you read. You also happened to share these reviews via tweets or Facebook updates. All the millions of Tweets, Facebook likes, Instagram and Pinterest Photos can be organized in a manner to help e-commerce businesses discover what customers want and when they want it. Collecting, storing, sorting and analysing data to draw meaningful and productive insights is an integral part of data science and this comparatively new kind of job in the field of data science is fulfilled by experts known as “Data Scientists”.
“The past does not repeat itself, but it rhymes.”- said Mark Twain
Even though future events have distinct circumstances or conditions, they characteristically follow similar patterns. The “Big Data Revolution” has brought technological advancements in data storage, cloud computing and data science which helps businesses identify these similar patterns. Today, data science algorithms can predict everything from flu outbreaks to mortality to crimes.
Consider a retailer that sells electronic gadgets. Let’s suppose that generally they have been doing great business due to the quality of their product and on-time deliveries. As the global trend shifts and competition grows, there is a need for ecological products. This slowly shifts company’s perfect customers to their competitors – which probably will go unnoticed by the company if they manually examine the market. Such small shifts can be identified by data scientists who write algorithms to continuously monitor the bygone sales cycles of the company by cross referencing the sales with external sources like news articles, social media updates – discussing these trends that help find correlations with the inclination to buy the products. Data science helps retailers discover new ways to understand how to retain their “core” customers rather than merely acquiring new customers.
According to EMC statistics report, the amount of digital data will exceed 44 zettabytes by end of 2020 that is close to 5,200 GB for every woman, man and child on earth. The amount of digital data produced is expected to double every year. As the saying goes “Data is the new gold”! Competition among e-commerce businesses is faster and fiercer. Customer habits change with the blink of an eye and every e-commerce business wants to win over that extra edge when it comes to fulfilling customer demands. Common sense, intuition and gut feelings are useful but definitely not enough to make predictions. Data science algorithms help businesses understand products, services, processes and customers effectively.
Data Science is not only for web companies-
- L’Oreal, the popular cosmetic company employs data scientists to find out the effect of various cosmetic agents on different skin textures and compositions.
- Rolls Royce employs data scientists to analyse data from airplane engines for scheduling maintenance.
- Feedzai uses data science algorithms to detect fraud.
- Fruition Sciences, an online decision tool for wine maker’s uses data science algorithms to accurately determine how much to water grapes and when to water grapes to produce better quality wine.
Data Science in ecommerce helps businesses provide a richer understanding of the customers by capturing and integrating the information on the web behaviour of the customers, the events that occurred in their lives, what led to the purchase of a product or service, how customers interact with different channels, etc.
Some data trends observed in the ecommerce industry are-
- 60% of people research and engage with brands on various channels like mobile, social media, in-store, websites, etc.
- People who search for a product using different channels spend 1/3rd more than people who don’t.
- 43% of retail sales in US are inclined towards the web.
- A survey by eCommera found that only 23% of UK retailers can make sense of data to take informed decisions.
- 50% of retailers in UK consider the shortage of business intelligence tools as the cause to harness the power of data science whilst only 16% are confident about their analytics solutions.
These trends show the rising boom for ecommerce industry and data science holds the promise of enhancing the shopping behaviour of customers that can provide ecommerce businesses with an improved marketing mix and enhanced profitability.