All industries and government organisations alike are awash with data in this pro-tech age. Be it the University of Tasmania developing a Learning and Management System using data based on students’ study habit, or the Wimbledon Championship utilising data to analyse the sentiments of the viewers in real-time; data has found its usage across varied industries.
Here are 10 industries that make effective use of their data, and how!
Banking sector is always at the risk of fraudulent practices. Monitoring financial markets and use of network analysis helps in detecting and curbing malpractices. Data Science is also used in auditing to detect irregularities, and also manage the customer data and to mitigate financial risks. All of this above and beyond improving customer’s regular banking experience.
Cross-selling, re-marketing, packaged services, customised offers, or personalised products; the additions brought by Data Science to the e-commerce industry are endless. Customer data is being hounded like never before, and products and offerings are hurled on them from all direction possible, depending upon their buying patterns, search histories, and behavioural analysis.
This industry is on a surge and so is the amount of data it is collecting. The products have a relatively short life span while user experience is critical. So the study of consumer behaviour data holds the key for greater user satisfaction and offering of personalized products. However, as a repository of sensitive personal information, the industry is always at risk against data loss and crimes like personality hack.
Financial market is always as fluid as it gets. Integration of mobile feeds, real-time market insights, customer sentiment analysis, transaction details with the historical data is on an all-time high. This is helping the industry in running real-time analytics and automating risk credit management. It is also helping in fighting financial frauds, and predicting market disasters.
For an industry suffering with unusable data and rising costs, Data Science appears as an obvious rescue. Apart from helping analyse large amount of genomic data, it enables leveraging public health data and processing records of past treatments. Coupled with effective use of technology, it further helps in conducting predictive analysis, identifying chronic disease trends, offering personalised treatments, and eventually slashing costs.
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This sector has taken a step ahead to combine Data Science with social media, CCTV footages, electoral rolls, and even satellite data to grid the consumer information and behaviour. It helps them in predicting trends, improving their pricing policies, offering personalised products, and thus furthering better customer relationship and loss prevention.
High failure rate of products, medically as well as financially, has marred this industry for ages. Low ‘discovered compound’ to ‘approved drug’ ratio, even lower returns from the approved drugs, and the high costs of research blemishes the revenues of this industry. However, effective use of Data Science has helped reducing this risk by predicting future trends, improving sales and marketing practices, and bettering research.
Data Scientists of the telecom industry spend a lot of time creating sophisticated 360-degree customer profiles. Using demographic as well as behavioural data, the companies are able to strike the chords with their customers. They are also able to optimize their individual network solutions.
Almost every other industry is using customer data for personalised product offering. However, travel takes it further to an ultra-personalised product and service offering. In depth 360-degree view of the customers, as well as a multi-layered data analysis across touch-points helps the companies identify most-valuable customers, cross-sell partner products, and advance highly customised products and services to its customers.
Not particularly an industry, but it does find a place in this list due to large amount of available data, and increased use of technology for better governance in the recent times. Data Science spans across varied purposes such as improving defence systems, preventing cyber-crimes, safeguarding sensitive information, making better financial decisions, and predicting natural disasters.
The list is obviously expandable. Entertainment, energy, retail or biotechnology; all other industries are also realising the importance of data and the science to derive knowledge out of it. Growing competition, technological advances, and an ever-reducing world is paving exciting roads ahead for Data Science.
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