9 Nov 2020, 13:26 — 7 min read
Technology is evolving at a rapid pace and is faster than ever. You won’t believe, one of the top trending technologies: Big data, led Germany to win its FIFA world cup in 2014. Surprisingly, in soccer’s history, it was perhaps the first time that any team did extensive research before finals to win the trophy.
And all the credit goes to the miracle of these technologies, which have made our life more comfortable. Coming to data science has changed almost every industry and redefined the way companies have embraced its potential.
The market size of data science is expected to grow from $37.9 billion in 2019 to $140.9 billion by 2024. The rising adoption of data science shows how various businesses use it to extract in-depth insights from voluminous data to achieve a competitive advantage.
Data science engineer works on machine learning and AI and builds models that automatically learn from its mistakes. Be it the healthcare industry, sports, logistics, or any other verticals, its algorithms have helped organisations enhance their customer service in every aspect.
In this article, I will explain how data science has emerged as a trending technology used by software development companies to help various industries improve customer experience and drive more customer loyalty in today’s competitive market.
It is one of the easiest and best marketing strategies that any eCommerce website follows to take the money out of buyer's pockets.
Let's understand this will help as an example. Suppose you are purchasing an Apple iPhone 11 from Flipkart. The marketer knows that there is a high probability that a person buying a smartphone will also be interested in its relevant associated products like apple iPod or back covers.
All they need to do is to put these products at the right place, just below the add to cart option. It makes the user's shopping experience more comfortable and, at the same time, pumps money into the account of Flipkart.
In short, it will accelerate the number of customer purchases per visit.
Now, let's verify how data science gives suggestions to this aspect. Data science allows eCommerce businesses to have an insight and understanding of the product associated with previous purchases.
It analysis the buying pattern and behavior of the buyers who have already bought the same or similar product earlier. Thanks to the data-backed insights, a powerful feature of data science helps build authentic products and in-store design associations.
Companies are loaded with tons of data, and it is common for them to have too much data in today's digital landscape. It becomes challenging for them to separate, organise, and prioritise the data to speed up the marketing strategy.
Firms make decisions based on data, and these data are scattered across various departments within a company, which makes it confusing for the businesses to have a decision.
Role of data science in optimising the data - Data science algorithms provide more in-depth insights about customer relationships, past purchase history, buying behavior, and their preferences. It draws information from these parameters and helps companies understand the data to use it correctly.
Companies use data analytic tools so that they can have a qualitative and quantitative view. Additionally, data analytics enables companies to understand what is happening within their company and overall trends within their market.
With this, the company can build customer loyalty by tracking meaningful trends.
Data science helps in fixing and minimising the issues before they occur. As a human being, no one can foresee the consequences of any issues; it is better to solve them before they create any problem.
With the help of data science and machine learning, you can track small issues and fix them as soon as you can. It is also applicable in manufacturing units where data science can track which machinery is working and which one has broken down.
It alerts the technicians to fix that particular machinery and deliver enhanced customer service before they happen.
Customers prefer to shop in the personalised digital mall these days rather than visiting the shopping malls. With the help of data science, online retailers customise and tweak their page layouts, spotlighted products, and many other things.
They self tailor the web storefronts by looking into the data of the previous buyers. Also, they adjust the prices as per the data they analyze, and this technique is known as personalised pricing.
Big Brands are using data science to harness their data for better customer insights, and it’s the time to watch how data revolutionise more industries at a monstrous rate.
Our very own Instagram applies data science to target sponsored posts. It keeps its hawk eyes on everything that the customers wish to shop. It extracts data of its users from Instagram and then builds algorithms accordingly.
It determines what other apps the user is using, check their web history, and then makes predictions about the products they might buy. This eases the process for both the parties hence delivering a delightful experience to its users.
Data science adds value to organisations that use their data well. With the help of statistics and insight inside the workflow, companies can make better-informed decisions and streamline business processes.
Whatever be the industry type, this cutting edge technology predicts everything and helps you analyse whatever comes next.
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Image source: shutterstock.com
Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views, official policy or position of GlobalLinker.
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