They say that those who do not study history are doomed to repeat it. In no form of big data analysis is this phrase more relevant than in ‘predictive analytics’. In simple terms, predictive analytics is the systematic use of data, machine learning techniques and a host of statistical algorithms to identify patterns that forecast the likelihood of future outcomes based on huge chunks of historical data. It is all about keeping a keen eye on what has and is happening to determine the best possible assessment of what might happen in the near future.
Predictive analytics slightly differs from other forms of big data analytics in that it is the only form that gives futuristic forecasts. Others such as prescriptive analytics gives directions on what actions should be taken to remedy various corporate issues; diagnostic analytics determines what happened and shows us why while descriptive analytics tells us what is currently happening.
Why Predictive Analytics is Crucial in the Business World Today?
Where big money is concerned, strategical mistakes can cost companies millions of dollars in revenue and operational costs. To avoid this sort of loss, businesses need to invest in forecasting.
In that entire chain of occurrences, you can already see just how inefficient the system can be. Solving these issues is critical and that’s where learning data science comes in handy. Especially, analytics that can forecast and help in strategic decision-making.Without predictive analytics, how can you tell whether or not the product you come up with will be useful to the masses? Without professional data scientists, how would you know who is most likely to buy your product? Which marketing strategies are most likely to garner you the most market share?
The truth is, the world has been running on an extremely inefficient system. It only takes you looking at the statistics to see just how true this is to date. Up to 90% of all start-up companies fail: marketing tactics include casting a wide net that more often than not does not yield favorable results (out of 80 cold calls made, you would be lucky to get 3 sales), and the list goes on.
Over the last few years, most companies have taken a look at these numbers and realized that something must change. Companies are taking advantage of Big Data analytics, which is nothing but a culmination of Business Intelligence and Predictive Analytics, to attain an edge over their competition.
Here are a few applications of predictive analytics in industries:
The Marketing campaigns have now become more optimized and efficient. Long gone are the days of ‘spraying and praying’ all the while wasting valuable resources trying to capture an unsuitable market niche based on a “hunch”. Today, through specialized predictive analytics, companies across the board can formulate effective strategies to identify, attract and capture markets for their products and services. The dependency on “gut feeling” has reduced.
E-commerce websites like Amazon have been making use of predictive analytics to capture usage patterns and past search data of website visitors to recommend products. A quick look around their website, or for that matter any other e-commerce player, will make you realize how predictive analytics is working so well. Amazon offers choices based on your likes and incites you to buy those products. From insurance companies to real estate, and almost every retail company, predictive analytics is now very much part of every operation.
One of the main reason as to why predictive analytics has come to the forefront of the business world now is because the digital penetration has increased incredibly.
