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5 Ways Big data Analytics Can Help Your eCommerce Business

Gloria Kopp / 3 min read.
April 12, 2017
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The words Big data‘ are thrown around a lot these days, but there is no definition that is universally accepted. The best definition of Big data comes from analyst Doug Laney, who said in 2001 that Big data is defined by  The 3Vs’ “ including velocity, variety and volume. This means that Big data is a large amount of content that is varied and being produced quickly. Here are five ways that Big data analytics can help your online company.

1. Examine Google Trends

Big data analytics can help your business by giving you an opportunity to examine trends on Google. Trend data shows you what kind of terms and keywords have been searched, where they were searched and who they were searched by. This information helps you see what the public is interested in, and allows you to adapt to that specific market. Trends can also help you decide the best direction for your website , – says Jane Reed, Operation Manager at Paper Fellows.

2. Prevent Fraud

Through the analysis of large data sets, you can identify where different kinds of fraud are most prevalent. For instance, you can find out what states or what countries that credit card fraud is most common, or where cash-on-delivery commitments are not honored. This allows you to take steps to ensure that you are not a victim of fraud, by implementing anti-fraud measures in specific areas, or avoiding doing business in these areas totally.

3. Introduce New Products

If your company is in the business of developing and creating products based on new trends, Big data analytics allows you to examine new and upcoming trends. When you use data collected from search engines, social media, surveys, forums and other online networks, you can learn more about what your customers might want.

Carol wise, Big Data Specialist at Boomessays comments: By filtering data by characteristics of customer, you can find out what your target market is interested in, and discover what kinds of new products they may enjoy .

4. Improve Your Customer Service

As well as information about what kinds of products your customers or target audience may be interested in purchasing, you can use Big data to find out what kind of services your target audience may be interested in.


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Using data on each customers, as opposed to noticing general patterns, you can learn extremely valuable things about your customer service. Reading the feedback from customers achieved through surveys, you can learn about problems within your company that are causing a significant problem , – shares Carol Wise, Data Analyst at Essayroo.

If only three of your customers experience the same problem, it does not form a pattern, but it does mean that you can lose those three customers. For this reasons, Big data is valuable both at an individual customer level, and on a general level.

5. Make Big Predictions

Big data analysis makes it possible for you to obtain an in-depth look at the many different channels in your company, from inventory to sales. You can, for instance, use big data analysis to look at the time of year in which certain products of yours sell best. You can then take this information and make sure that you have enough stock available to make the most of this surge in interest.

By using big data to make predictions, you can ensure that your business is always ready for seasonal surges, and make the most out of the products you sell.

Spend Time with Big Data

Big data might seem confusing and complex at first, but once you spend some time learning how to analyze trends, the benefits become quite obvious. Spend some time exploring big data and your business will soon see the benefits. 

Categories: Big Data, Strategy
Tags: analysis, analytics, bad data, ecommerce

About Gloria Kopp

Gloria Kopp is a big data analyst and a business consultant from Manville city. At present time she works as a business writer at Assignment Writing Service. Besides, she is a regular contributor to such websites as Engadget, UK Writings Service, Huffingtonpost etc.

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