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Customer Segmentation: 5 remarkable things that have happened in the Big Data era

Customer Segmentation

Published on Feb 20, 2020

Customer Segmentation has created a breakthrough for businesses not only in revolutionizing marketing strategies but also in optimizing inventory management, decision making, and revenue. 

Below is a succinct overview of the five remarkable things that have happened in customer segmentation in the times of Big Data.  

Need-based Segmentation to Behavior-based Segmentation 

Traditional customer segmentation comprises four basic attributes – geographic, demographic, psychographic, and behavioral. With digital disruption, marketing has shifted from product-centricity to customer-centricity, and with customers demanding individual recognition, need-based segmentation has changed to behavior-based segmentation to characterize their buying persona and purchasing power.   

Growing granular with big data technologies 

The internet is a plethora of data most of which comprises consumer insights. By leveraging data analytics and customer segmentation techniques to this behemoth data, companies were able to map underlying patterns granularly and identify overlooked factors that may be a value add-on or potential risk. All the more, companies are able to perform hyper-personalization with big data to deliver tailor-cut and real-time solutions. 

Targeted Marketing and Enhanced RoI 

Companies invest millions in advertising and marketing. Identifying profitable and non-profitable customers has become essential in a competitive digital world. Big data combined with customer analytics enables businesses to recognize and segment profitable and non-profitable customers and build a targeted marketing strategy. This not only helped boost revenue but also avoid faulty investments. 

Selling made simple 

Customer segmentation fueled by big data has made it simple to explore new markets and demographics, and track product performance in line with customer needs and satisfaction. Also, businesses are able to understand customer retention factors and also formulate suitable selling strategies to improve sales and reduce product returns. 

Make better decisions  

The advancement of data analytics has empowered businesses to fuse descriptive, prescriptive, and predictive analytics to map historical data with actual data and predict customer decisions and actions. Though in the evolutionary stage, predictive analytics is one of the much-awaited technological advancements which will enable businesses to predict their customer and make well-informed futuristic decisions. 

Wrapping Up

Market research and customer Segmentation are completely revamped by big data. Amazon, Walmart, and Time Warner are certain real-time paragons that have implemented customer segmentation successfully in the big data age. Considering emerging advancements in technology, businesses are looking forward to achieving more benefits of big data with customer segmentation in the forthcoming decade. 

References

  1. https://www.forbes.com/sites/teradata/2016/09/29/is-there-a-role-for-customer-segmentation-in-a-big-data-world/#366c1c8c7680 
  2. https://www.bmmagazine.co.uk/in-business/customer-segmentation-big-data-hand/ 

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