How can a company maximize revenue? How can it go above and beyond what it already earns? How can it make sure that its product/service sells vastly and quickly among the masses? When asked these questions, we may be inclined to suggest the traditional routes: lowering prices, decreasing production costs, widening the target demographic, etc, etc. Sure, sure, a company can do all of that, but the time period needed to implement such changes isn’t a short one. Say, a business that sells organic products suddenly decides to lower the price of its fruits from $2.00 per pound to $1.50 per pound. Of course, new customers will be drawn to the fifty cent drop, and daily customers will buy even more fruit, largely due to the income effect.
But, a change in price is practically useless if the product/service doesn’t generate sufficient demand. The decreased price for organic fruit is certainly tempting, but not to those who don’t even want organic fruit to begin with. In other words, a company will have the highest chance of maximizing its revenue when the factor of demand is on its side. But, how can a business truly know if its product/service is in demand? How can it infiltrate the minds of countless consumers and discover what they really want?
For many businesses nowadays, big data is turning out to be a very popular answer. Big data, essentially, is a term for a massive amount of data, both structured and unstructured, that is difficult to process using baseline software techniques. This includes the online footprints of the thousands of people that use social media, engage in web transactions, and have some record of general online activity. If successfully captured and organized, such data can give companies some strong clues about the preferences of the public. For example, let’s say Person A is on the hunt for a new car. During his search, he posts on Twitter: “Looking for a ride with class and a lot of safety features! #safetycomesfirst.” Big data analysis actually picks up on these little details, and the Audi dealer a few streets down can make sure to offer a model with multiple safety features if Person A happens to come by. How’s that for acquiring more revenue?
Not only that, but big data analysis also provides insight on how a company can go about changing its product/service for the better. Again, with unstructured social media posts in which consumers express their true sentiments about the things they purchase, companies can see what aspects of their output make people unhappy and alter these aspects for the better. Going off the previous example, let’s imagine Person A again, this time driving the new Audi he bought from the local dealer. Person A is happy with his overall purchase, but is dissatisfied with one key element: the heating system. Hence, he writes a blog post saying, “This Audi is nice… but wish I didn’t have to freeze for the first ten minutes while it heats up.” With big data, the Audi dealer can now see that Person A is discontent with the heating system, and then go on to investigate if others across the nation are reporting the same problem online. If so, the Audi company as a whole can take steps to improve this apparent defect by addressing individual concerns, upgrading current production, and/or releasing new and improved models.
So, indeed, big data analysis has the power to completely change the course of a company. Businesses who have not yet invested in this technology should do so immediately. With big data at their side, they can stop the guessing games and actually know what consumers want – the biggest advantage of all.