A big part of our existence is about making choices, and preferably the best one. Evidence- based decision-making matters more than going by rule of thumb. In order to establish evidence-based decision-making as a deep corporate culture, we need to understand the vast potential of data. Data analytics turn to be one of the trusted business methods in this context.
The importance of data analytics is truly amazing. It can make a business bigger and better. If you have the right business, you can be sure enough that you can enhance your business in the right way.
It is more of a trouble for most businesses on how to get the reliable business tool for data analytics. Of late, data analytics tools are making use the software as a service model. It overcomes the mixture of the deployment cycles, IT infra structure, higher expenses and complex upgrade processes. It is easy and simple to set up and easy to use as well. It can deliver quick business value and corporate results.
The advantages of Data Analytics can be summarized as follows;
Cost reduction: Data Analytics helps in identifying unproductive work and bring more productive work on table. Companies can stop unproductive work, get lean and reduce unwanted expenditure and concentrate more on productive works so companies profit increases. Data analytics also helps in analyzing target customer and thereby reduce customer acquisition cost.
Better decision making. With the speed of Hadoop and in-memory analytics, combined with the ability to analyze new sources of data, businesses can analyze information immediately – and make decisions based on what they’ve learned.
New products and services. With the ability to gauge customer needs and satisfaction through analytics comes the power to give customers what they want. With big data analytics, more companies are creating new products to meet customers’ needs.
It’s hard to talk about analytics success stories, and not mention the success of Amazon business model. Amazon was one among the early adopters of data analytics, and it turned to be the only company that has a patent that allows it to ship goods before an order has even been placed. Their ‘customers who bought this…’ feature was revolutionary at the time, but compared to the company’s current offerings, it pales into insignificance. Now, the data points are wide-ranging and far more indicative of what a customer is likely to be genuinely interested in.
Today’s recommendations are based on their wish list, the items they have reviewed and what similar people have purchased – this creates a very rounded profile of a customer and is a great example of predictive analytics being used to its full potential.
