The role of big data Analytics in ecommerce analytics has increased in the recent past. That said, the theoretical and practical research in the domain of ecommerce vis-a-vis big data is not greatly explored. We aim at exploring the growing role of big data analytics in ecommerce by exploring various aspects and characteristics of big data and its relevance for the digital industry. We strive to discuss the broader aspects of the role of big data in ecommerce analytics.
A review of statistics
A study by the BSA software alliance concluded that big data analytics has the potential of expanding the sales of the ecommerce industry by more than 66 percent. According to this study, the ecommerce firms that use analytics improve their value chain experience with more productivity levels than the ones who shy away from analytics. These productivity levels are in the range of 9 to 10 percent. Therefore, it is not a coincidence that the top 90 percent of the Fortune 1000 companies are investing in big data analytics and witnessing higher levels of growth.
Analytics and the ecommerce ecosystem
The ecommerce industry must deal with both structured data and unstructured data in the long run. It is easy to derive insights from structured data due to its relative categorization. Structured data is classified based on age, gender, preferences, demography, and the like. Unstructured data on the other hand deals with the real-time processing of incoming streams of data with the involvement of hidden elements of noise and a high degree of randomness.
The landscape of ecommerce is flooded by big data and customer analytics is the unique answer to find solutions to the most pressing business problems. Customer analytics can act as a savior for the ecommerce industry because of a cost-effective processing capacity and a wide range of analytical tools.
Various realms of big data in the ecommerce industry
There are various categories of big data which we use in the ecommerce industry. The first among these categories is the transaction activity data. We can generate this data due to the exchanges between customer and company over a period. This data is usually structured in nature and gives a picture of the sales transactions for a particular period. It is believed that among the various realms of big data, this realm of big data is indispensable for deriving numerous benefits and supplementing business revenues in the long run. The second category is that of clickstream data. This data is related to online advertisements and digital content like posts and blogs. This data is useful for promotional strategies and aids tactical decisions related to customer analytics. This data is a hotbed of research in the domains of customer preferences and taste. Digital giants like Netflix heavily rely on this type of analytics. The third category is the availability of video data which can be in the form of live images. However, it has been observed that the ecommerce industry is not keen to capture this type of data as it becomes relatively difficult to process. The last type of data is in the form of voice signals. This data has great significance for the business process outsourcing industry.
The personalization factors
Various studies have been conducted to find the impact that personalization can bring to various ecommerce firms. In these studies, it was found that personalization strategies help ecommerce startups to segregate old customers from new customers. Such strategies also help in the effective channelization of promotional campaigns. Personalization strategies can bring up the levels of investment on market expenditures by great amounts.
The dynamic pricing model
The dynamic pricing models help a new ecommerce firm to compete with the established technological giants in the market. A functional dynamic pricing system keeps an eye on the competing values and alerts the company in a stipulated time. This helps in increasing the revenue of an ecommerce firm by giving it the ease to update its prices. Companies like Amazon have witnessed a rise of more than 33 percent in their sales by roping in the dynamic pricing model.
Customer grievance redressal mechanism
Ecommerce firms can make great use of big data analytics in addressing the grievances of the customers. After making a purchase, a customer is prompted to rate various services of the company and a low rating can serve as an alarm to get back to the customer and earn his trust. This is called the proactive maintenance protocol which many digital firms make use of.
Big data analytics has the potential of driving the ecommerce industry to new levels of growth and innovation. The need of the hour is to effectively utilize various processes, technologies and systems which are offered by big data analytics at a nominal cost.
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