Data: It’s a hot topic among business leaders and there are many reasons why. Not only can data reveal what happened in the past, but with new Predictive Analytics tools, a business owner you can begin forecasting what will happen to plan for the future. It may sound a little like fortune telling, but there’s a definite science behind predictive analytics.

In a recent report, Q&A: How to Energize Your Enterprise BI Platform With Integrated Predictive R Models, Forrester Vice President and Principal Analyst Boris Evelson says “top performing companies (with a year-over-year revenue growth greater than 15%) are using predictive analytics almost three times more often (182%) than their low performing peers.” Organizations are inundated with data: customer data, financial data, call center data, market data, third-party data along with many other devices collecting data. The top performing organizations have found a way to manage and combine all of it to identify patterns that allow them to strategically create market opportunities.

Retail giants, including Amazon and Barnes & Noble, use predictive analytics to recommend items and offer special incentives to loyal customers that drive sales. If you’ve ever wondered how those recommendations appear—it’s your data bringing recommendations straight to your inbox or homepage. Financial services companies are also using predictive analytics to address customer churn and fraud concerns. These best practices among Fortune 500 companies can be applied to Indiana’s business of varying sizes.

Here are five tips to help a business owner get started:

Outline Your Goals – Start by asking yourself the important question: what is it that you hope to accomplish with predictive analytics? What problem are you trying to solve? For example, are you trying to develop stronger customer insights in order to improve your marketing ROI? Or are you hoping to create a more accurate budgeting model based upon the seasonality of your business? Start with the end goal in mind.

Lay your groundwork – Ensure you have the proper data points in place in order to capture the data you need for your predictive analytics reporting. For example, if you are trying to better predict your customer’s buying patterns, your data sources may include Google Analytics, email marketing program metrics and data from your CRM software. Use tools such as Microsoft’s Power BI to pull together data from various different data sources into one portal for reporting.

Experiment – Now the fun begins! With your goals and data set, start playing around with the data to create predictive analytics reports. Airline companies may use this data to predict flight delays based upon weather patterns, seasonality and flight head counts. Universities can use key data surrounding GPA and attendance to predict graduation rates. Manufacturers can begin predicting when parts could fail and proactively use data to communicate service reminders to customers.

Get Detailed with Customer Segmentation – Use data to get to know your customers better than ever. For example, banks segment customers based upon their number of accounts the amount of cash in those accounts and the number of meetings held with that customer. These indicators help identify customers with potential to grow the relationship. In turn, these are customers to market to for new services.

Don’t throw your Descriptive Analytics out with the bathwater – While predictive analytics leverages your data through a different lens, traditional descriptive analytics and reports are still crucial. This data set serves as the baseline for see the future and without it, you won’t have the necessary foundation to plan for future trends.

Andy Brockett is channel business development manager at Allegient LLC.

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