How to Use Data Science and Machine Learning to Revolutionize Customer Views?

AretoveTechnologies
2 min readNov 24, 2019

The common intent of all businesses spread across the globe is generating revenues by winning customers. And today, the best way to gain customers and to ensure their loyalty is by providing them with a superior experience with the help of Data Science & Machine Learning.

Today, companies like MapR Professional Services are employing advanced Big Data applications for business insights that help companies gain a deeper understanding of customer views by finding new data sources and applying Machine Learning principles.

How can customer views be revolutionized?

Earlier, MapR was assisting enterprises who wanted to do more with their data than just solve business problems. But currently, MapR uses its customer’s 360-degree revolution program to help businesses predict the next behavior of their customers. If companies can find out the next move of their customers, it will certainly work in their favour.

Similar to MapR’s Customer 360-degree Revolution program, to transform customer views, the following tasks need to be performed:

  • Finding more information about individual customers
  • Adapting the new findings with the business knowledge
  • Utilizing the new information to transform business for better profits

To achieve these, the role and proficiency of an experienced data scientist cannot be overlooked. To aid in predicting the possibilities of future customer behaviour, data scientists help in

  • Identifying new data sources, since traditional databases have certain limitations mostly due to size and format
  • Collecting, correlating and analyzing data extracted from multiple data sources
  • Applying Data Science and machine learning to get the value from such data

An example of using revolutionized customer views

Consider a mobile banking website, where advertisements are displayed of products that were previously bought by customers. Using Google analytics with machine learning, companies can now control what their customers see on the website. They can control the display of adverts; that is, decide which ads to display to which customer.

Advertisers have now joined hands with card-to-link companies to generate new leads for their business and to further increase their customer base. Without employing Data Science and Machine Learning, it would not have been possible to do so much with the existing warehouse data.

In a nutshell, the many Applications of Data Science can help companies to target customers better by collecting customer behavioral data. It then becomes easier to create customer groups which share similar behavioral attributes. It allows properly streamlined business marketing that ultimately boosts their revenues.

References:

How To Invest In Industrial IoT For Data Analytics?

Evaluating The Influence Of Data Analytics In Customer Service

5 Significant Effects Of Big Data In Today’s HR Industry

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