Some organizations today are leveraging big data and winning big. In this article, I will be taking a look at how organizations are using predictive analytics and how they are benefiting from it. This is a high level exploration of predictive analytics so if you are a hardcore data scientist, this will be very basic for you. This article is intended for those that are new to the topic. With that said, I will start by briefly explaining predictive analytics.
Predictive analytics is the process of analyzing historical and current data and applying advanced statistical methods and analytical tools to make reliable predictions about the future. If you take this definition in a business context, then predictive analytics works on the creation of predictive models to learn from historical information, customer data, and other third-party data sources to identify risks and opportunities.
Predictive analytics transforms data into actionable insights. It tells you why things are happening and what is most likely to happen in the future. Often, it can help uncover hidden opportunities or unexpected risks. These insights can help you identify what decisions need to be made and what steps should be taken to achieve a desirable outcome. Ultimately, it allows business owners to make better, more informed decisions with confidence.
To dive deeper into the topic, here are a few scenarios and use cases where organizations are tapping into big data and leveraging predictive analytics to increase revenue, retain customers and protect themselves.
Inaccurate sales forecasts not only lead to improper planning and budgeting of resources, but also have a dramatic impact on top line and bottom line revenue, share price and investor confidence. Business leaders are using predictive analytic to predict insight that will help them stay ahead of the curve. Businesses have a lot to gain by replacing manual forecasting processes with a new set of technologies driven by data science – an approach based on predictive analytics that relies on a combination of statistics, machine learning, data mining and modeling.
Organizations are using predictive analytics to determine customer responses or purchases, as well as promote cross-sell opportunities. It help businesses attract, retain and grow their most profitable customers. Marketers are under pressure to drive effectiveness as well as efficiency – two factors that define marketing productivity. With predictive analytics, marketers have the ability to see trends and outliers, inform key insights and enable better decision-making. It empowers marketers to be better at what they are already doing, to identify individuals who have the highest propensity to buy and to give marketers an advantage in optimizing campaigns, lowering the costs and generating better ROI.
When your customers reduce their usage or completely stop using your products or services, they are leaving your brand and might have gone to your competitor. Using predictive analytics organizations are able to find out what went wrong, why customers are leaving and who were those customers. Analyzing this data gives you a better understanding of your customers behavior. This insight can empower you to resolve issues and ultimately win back your customers.
There are many other use cases for predictive analytics that are being leveraged by businesses in all industries. It’s a growing trend and will be paramount to the success of any big business hoping to win market share in the future.
By: Seyla Seng