The key component of any AI program is information (input). AI feeds off information and its key function is processing this data to produce useful insights, which is information that performs a useful function (output). 90% of the world’s data has been produced in the past two years, that’s a lot of information for anyone to be able to sort, analyze and process to drive business strategy. One of the ways AI does this is by applying techniques like predictive analytics. Wikipedia defines predictive analytics as a technique which encompasses a variety of statistical techniques from data mining, predictive modelling and machine learning, that analyze current and historical facts to make predictions about the future or otherwise unknown events. This method has been used by a lot of firms in finance, retail and logistics.
In finance, firms like Hedge funds have been using this technique by feeding past financial data into a program, running back tests and using this past data to produce trading strategies that can predict future market performance.
In retail, online retailers use predictive analytics to predict which product a customer is likely to buy after they’ve bought say, a cashmere sweater based on what previous customers bought after purchasing the sweater or predicting potential security threats based on how a user purchases an item, fills out a cart or enters their credit card information. based on the past behavior of hundreds of thousands of customers.
In marketing, predictive analytics helps drive business performance by evaluating the quality of leads based on past data. This approach helps marketers target customers that are most likely to convert by focusing on the quality instead of the quantity of metrics. As an analyst you’re able to increase conversions by organizing thousands of quality data points to decide which leads to focus on. If you know which leads are more likely to convert, then surely you will know which products are likely to sell and so you will make sure that you will have enough inventory in stock which then trickles down to increasing the efficiency of your supply chain.
To grow your business by using AI and predictive analytics you will rely on the following key points:
You need to ask the right questions, what is your business goal? What problem are you trying to solve or what future behavior are you trying to predict?
You cannot be able to produce accurate forecasts or be able to predict your business’s future performance without the right information. AI depends on data quality and so organizing your data is critical to generate dependable business insights.
You need to be able to work with people that know which questions to ask, where to find the information they need and most importantly, people that know what to do with that information.