Technology is revolutionizing the way that many companies do business. From cutting the costs of supply chains to improving the way that automation fuels different aspects of your marketing campaigns, technology is helping many businesses of all sizes better spend their time, money, and staff resources. Thanks to advancements in technology, you have a variety of exciting ways to improve your business in a cost-effective manner that opens the door to brand new possibilities and markets for your business.
Perhaps no area of business has been more positively impacted than the role machine learning is beginning to play in data analysis. Data is already powering many enterprises, and with advancements, in predictive analytics (not to mention prescriptive analytics) there are a variety of ways that data analysis can benefit from machine learning.
Machine learning and artificial intelligence have become powerful tools for improving the way that big data can provide important insights in real-time, and analytics platforms that can use predictive models are likely to continue rising in popularity due to the way that these tools help business leaders manage predictions big and small. Read on to learn more about how predictive analytics is changing the game, and how it can help your brand grow in the coming years.
Especially in the world of data, it’s easy to get bogged down in the nitty-gritty of how something works. That’s especially true with more complicated concepts, of which predictive analytics tools certainly fit the bill when you get into machine learning and predictive models.
That being said, answering the question “What is predictive analytics?” is actually much simpler than you’d think. Put in layman’s terms, predictive analytics involves more accurately forecasting future events, trends, and outcomes based on a set of historical data. By leveraging machine learning and artificial intelligence, predictive analytics is able to rapidly go through multiple decision trees to help you better understand the possibility of certain things happening.
Traditional data analytics is rather limited in the insights it can offer you about your business. For example, you may be able to report back on what happened and infer why it happened, but in terms of business intelligence, it’s hard to make better decisions when your current data and statistical models aren’t better at predicting possible consumer behaviors.
Predictive analytics goes beyond these limitations by using past data and outcomes to enable you to not only figure out what may happen but determine through the predictive analytics process and prescriptive analytics what is most ideal for your business to have happen in the future, too.
So, now that you know what predictive analytics is, you probably want to know what the best ways are to utilize it to your company’s advantage. When it comes to using predictive analytics data modeling to come up with actionable insights and an accurate forecast, there are all kinds of ways you can leverage predictive analytics in your existing business process. However, one of the most common times you’ll be looking to the real-time insights predictive analytics tools provide is when you’re determining whether or not you want to create additional products or not.
By using predictive analytics, it’s possible to more accurately forecast consumer demand and how customers may respond to your marketing campaigns, which can help you engineer a particular set of conditions and maximize your revenue in the process. It’s also worth noting that by using predictive analytics you can also steer clear of making costly errors, which, especially in the wake of COVID-19 and the coronavirus pandemic, can be particularly important to sustaining and even boosting your brand’s growth in the long term.