Step-by-Step Process to Analyze Your Data From Start to Finish

analyzing credit union dataContained inside the massive volumes of data that your credit union is creating on a daily basis is the insight you need to better understand your members. It contains valuable insights about the individuals, including their wants, needs and dreams. Being able to properly analyze your credit union's data puts you in the best possible position to serve them with personalized services and better experiences. Let's explore five essential steps to unlock this invaluable insight.

 

1. Extract

Data extraction is the process of collecting different types of data from a variety of sources. One of the more prominent of these sources will undoubtedly be your core processing platform. But other sources can include the tools being used by your marketing department, software that is utilized by front-end employees, and anything else that contains personal member information in some way.

 

2. Cleanse

Next, you'll need to cleanse your data, which means editing, correcting mistakes, and restructuring it in a more useful way. Begin by removing any irrelevant data from what you've extracted. Do the same for duplicate data as well. Address any structural errors that you uncover, manually fill in the missing data gaps, and validate everything to make sure you have the most complete and accurate record to work from.

 

3. Analyze

Next, you can start analyzing your credit union's datawhich is another way of saying that you'll begin to make sense of it all. Start by first defining your overall goals and how you'll measure them. Are you trying to reduce membership turnover? Are you trying to increase revenue per member? Define your goals and let your data analysis act as a guide to accomplish them.

Throughout this time, you can use data analytic tools like Google Looker Studio or Microsoft Excel, along with techniques like predictive or prescriptive analytics, to further work towards your goals.

 

4. Export

Transferring your data through exporting involves converting it from its existing format to the required format of the application you will use for reporting purposes. Note that many credit unions find success by making data exporting a part of their larger backup strategy. They get to extract specific data into a more versatile, useful format and create a backup copy of critical information for safety as well.

 

5. Report

Finally, you can report on your credit union's data in a way that helps to visualize it and that makes it easier to derive the right insights from it. Here, you're taking complex information and making it as easy as possible to understand. Be sure to review and finalize your report before sending it to the rest of your credit union's leadership to act upon.

 

Future-Proofing Your Credit Union: Harnessing the Data Flood for Member Empowerment

In the end, don't forget that the "data flood" that all industries are currently a part of shows no signs of slowing down anytime soon. As we become more connected via the Internet, and as more credit unions begin to offer innovative digital solutions, we'll soon have more insight to draw from than ever. It's really important for you to establish a solid foundation that enables you to analyze your credit union's data the right way. Doing so will allow you to continue to empower the experiences of members moving forward.

To find out more information about how you can start analyzing your credit union's data today, click the button below. Otherwise, contact FLEX today to get answers to any questions you might have. 

 

Data Visualization

 

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