5 Amazing Ways Data Science Will Transform the eCommerce Business
Business + ManagementGuest contributorecommerceposted by Gaurav Belani September 30, 2019 Gaurav Belani
Data science has become a go-to term for every industry, starting from eCommerce to healthcare and transportation. And each sector uses data science in eCommerce for different purposes.
For instance, Amazon, the eCommerce giant, uses data for improving eCommerce experience. Among all industries, data science has had a significant impact on the eCommerce industry. It has helped businesses gain insight of the customers by gathering and integrating the information on the customers’ web behavior, the events that occurred in their lives, what led to the purchase of a product or service, how customers interact with different channels, and so on.
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There are several ways data science has and will revolutionize the eCommerce businesses. With the help of data collected, businesses can make personalized product recommendations, leverage on predictive forecasting, determine customer behavior and shopping patterns, improve customer experience, and prevent fraud among others.
This article will run you through those 5 amazing ways in which data science will transform eCommerce businesses.
5 Amazing Ways Data Science will transform eCommerce Businesses:
Make personalized product recommendations:
Enabling personalized product recommendation is one way in which data science is transforming eCommerce businesses. Popular eCommerce websites like Amazon and Netflix are leveraging on it.
For instance, using Amazon Personalize developers can easily create individualized recommendations for customers to improve customer experience and boost sales. 35% of Amazon’s revenue is generated by its recommendation engine.
If you take a look at Barilliance reports, personalized product recommendation account for nearly 31% of the revenues in the global eCommerce industry. The percentage of the conversion rate for customers who are not recommended products stands at only 1.02%, while that percentage rises to 288% after the first interaction.
In another report made by Salesforce, it is revealed that online shoppers are 4.5 times more likely to add items to the shopping cart and buy them after clicking on any product recommendation. Another Salesforce study showed that 52% of online shoppers are willing to share their personal data to get more personalized product recommendations.
Leverage on predictive forecasting
As per Salesforce, using its predictive intelligence an online furniture retailer, Room & Board was able to increase its return on investment by a massive 2900% simply by predicting and recommending additional purchases to its shoppers.
Predictive forecasting uses different data sources to make predictions, including the history of previous sales, economic indicators, customer searches, and demographic data.
In addition to predictive forecasting, AI-powered predictive intelligence technology is utilized to predict and deliver what online shoppers need even before they look for a product.
Even B2B analytics companies such as Lattice Engines merge customer data with individual activities on social media and websites to accurately spot sales prospects for their customers.
Determine customer behavior and shopping patterns
Data science can be beneficial in determining customer behavior and shopping patterns. Studying consumer behavior is essential as it enables marketers to understand what influences consumers’ buying decisions.
It will help to fill in the gap in the market and identify the products that are required and the products that are outdated. Studying consumer behavior also assists marketers to present their products in a way that generates maximum impact on consumers.
In new research on social media preferences and buying preferences conducted on early 2019 by HubSpot Research partnered with SurveyMonkey, it was found that consumers ages 18 to 29 are nearly eight times more likely to discover new products from Instagram, compared to consumers aged 61 or older.
Online shopping patterns, on the other hand, can help you manage your eCommerce operations, including supply chain, inventory, marketing channels, and product pricing more efficiently.
Improve customer experience
As per Salesforce reports, 80% of customers state that the experience a company provides is as relevant as its products and services.
And in a new study conducted by PwC, about two-thirds (65%) of respondents in the US cited that a positive experience with a brand is more influential than great advertising.
Earlier, customer service used to rely on product or service feedback from customers to make improvements in their products or services. Or they reached out to customers through phone or email. But today, with data analytics, online retailers can gain valuable insights to help them provide better services.
There are tools such as Sentiment Analysis to help you derive valuable insights from a large number of online customer reviews and ratings about a given product or brand. With data analytics, eCommerce businesses can identify and resolve issues in products or services and enhance the overall customer experience.
Cybercrime such as identity thefts, phishing or account thefts, shipping, and billing-related scams are on the rise. In fact, in 2018, consumers reported losing about $1.48 billion related to fraud complaints. The fraud complaints saw an increase of $406 million from 2017.
Providing good products and exceptional customer experience is not enough for eCommerce businesses to prosper. They must ensure customers’ security.
Online fraud can not only cause loss of revenue but also mar the reputation of your business, thus losing your traffic and customers’ trust. To help resolve this issue, eCommerce businesses can use a combination of data science and machine learning to detect suspicious behavior online.
Different shipping, and billing address, large value orders, using multiple modes of payment for the same shipping address, and international orders can be some indicators of suspicious behaviors.
Data science is transforming and benefitting eCommerce businesses immensely. And the good news is that it is ever-evolving. Tech experts are constantly trying to find new innovative ways to leverage the data collected.
Thus, data science technologies are driving the phenomenal growth of the global E-commerce industry. This article outlines only 5 of the vital areas where data science is making an impact – there are even more avenues where it works to transform eCommerce businesses.
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If you own an eCommerce business, investing in data science technologies can drive your business growth. Ensure to keep yourself updated on the newest data science trends and developments and leverage on them.
About the author:
Gaurav Belani is a senior SEO and content marketing analyst at Growfusely, a content marketing agency that specializes in data-driven SEO. He has more than seven years of experience in digital marketing and loves to read and write about education technology, AI, machine learning, data science, and other emerging technologies. In his spare time, he enjoys watching movies and listening to music. Connect with him on Linkedin and Twitter @belanigaurav.