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Big Data and Smart Data: Big Drivers for Smart Decision Making

Data Analytics is swiftly taking over every sector and business owners are notanymore dependent on vague, intuitional choices.

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DQC Bureau
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Authored By: Dr. Dakshinamurthy V Kolluru, President, INSOFE,  PhD & MS – Carnegie Mellon University, BE – NIT Trichy. 

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Data Analytics is swiftly taking over every sector and business owners are not anymore dependent on vague, intuitional choices. They have moved on to smart data-driven business decisions to capture the market requirement and strategically upsurge their sales figures. E-commerce is one of the major sectors where big data played a serious role as a game changing differentiator and India is one of the fastest growing markets for e-commerce with several small and big players stepping in every year. All the e-commerce giants and start-ups are adapting big data to analyse customer behavior, understand market trends and sales with the target focus points being customer satisfaction and retention. We can dive in further to understand the broader role of analytics in e-commerce:

Customer Requirement Analysis:

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Right from the site navigation to personalized shopping experience, data analytics plays a very important role in the way e-commerce sites operate today. Predictive analytics is used to understand consumer behavior and predict requirement for a certain product. This miraculously guides the business owners on what is further ahead next quarter or what to look out for. Forecasting the requirement not only helps increase sales but also helps better manage situations like stock management, inventory costs and many others.  Based on extensive research and analysis, e-commerce companies make decisions while venturing into a new market or bringing in new product launches and also in product pricing.

Pricing:

With heavy competition from other ecommerce sites and small vendors, pricing becomes a key differentiator. Dynamic pricing based on data from sources like customer behaviour, competitor pricing, current scenario, reginal factors etc.  gives a competitive advantage. The insights from data analytics shows optimal pricing that the consumer is willing to pay. For each customer segment and product this may vary and can be an essential factor in closing sales.

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Fraud Detection:

Well known is the fact that, running an ecommerce company comes with a lot of shortcomings and risks as well. Fraud can be quite common and can be a major setback in customer retention. Ecommerce companies make sure that every vendor strictly abides by the registration process to ensure fraud management. Even though, very often the fraud occurred may not have anything to do with the ecommerce company itself, it directly impacts the reputation and the sales figures inevitably. Real-time management is done using predictive algorithms to avoid any such situations.

Supply Chain Management:

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Although supply chain has always been supported by statistics and quantifiable indicators, today Ecommerce industry uses data analytics extensively to optimise transportation, inventory management and delivery pricing. Analytics also comes into the picture as it is essential to track the availability and order status of products.  Since there are several factors that impact supply chain management and there is a lot unstructured data involved, predictive analysis and forecasting is sure a game changer. Hence making the entire process more structured and smoother, use of analytics results in customer satisfaction and retention.

Customer Satisfaction and Retention:

The very well-known fact is that, it all boils down to this single most important factor for any business.  Including all the above stated factors and many others play as key to customer satisfaction and retention. Starting from consumer behaviour, customer segmentation, promotional activities purchasing patterns, most active period of purchase, traffic on the site, transaction patterns to delivery of the products, key insights can be derived using data analytics to improvise sales and retain customers.

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