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    What To Look For In a Loyalty Rewards Program Software

    Choosing software can be frustrating. Whether in business or in your personal life you want to enlist software that's accommodating and cutting-edge. For accountants, software choices can make the difference between accurate reporting and estimations based off of unreliable data.

    The correct loyalty rewards program software makes every accountant's job easier. From accurately assessing the liability of your company's loyalty rewards program to reporting on it, employing software will benefit your company greatly. However, you might be wondering how to choose the correct loyalty program software.

    We've put together a checklist to help you make the correct choice and implement the best possible loyalty program software.

    Make sure the software you choose can:

    1. Analyze Loyalty Program Data

    Decipher your program’s transactional data to analyze member behavior including:

    • Member activity
    • Redemption history
    • Earning patterns

    Don't trust your data science team to provide you with the most accurate loyalty program data. You'll want to be able to intensively study your program's transactional data. The loyalty program software you utilize should have a platform that allows you to do so. It should be sophisticated and predictive to help you understand the financial aspects, accounting necessities and economics of your program.

    2. Build a Predictive Model

    This predictive model should provide in-depth insight into expected long-term member behavior. This model will help to:

    Building a predictive model assists your loyalty program in moving forward profitably. This model will allow you to predict a customer's lifetime value. If the customer has potential to be of high value then your predictive model should indicate this so the customer can be further incentivized. On the other hand if a customer is at risk of lapse, the model should indicate this so it can be prevented. Further, the model should estimate the program's liability. Having an accurate liability assessment allows you to report the program's potential risk.

    3. Provide a User-Friendly Platform

    This platform should include:

    • Data necessary to make sound program decisions
    • Predictive and ROI-driving insights
    • Actuarial reporting on program liability

    The platform provided by your loyalty program software will be the basis for your decision making. This platform should be intuitive and user-friendly while providing as much insight as possible. It's important that this software employs cutting-edge actuarial science and machine learning. This is the software that will drive important business decisions regarding your loyalty rewards program.

    4. Have Staff Available for Platform Assistance

    Loyalty rewards program software is, by nature, complex. No matter how intuitive your software may be, you'll want to have your software vendor's staff available for any questions you might have about the platform. Platform assistance can mean the difference between understanding whether your predictive model is accurate and flailing blindly through a software you don't grasp. Make sure the vendor's staff is:

    • Available to assist
    • Understanding of your company's platform utilization
    • Willing to customize your platform

    Choosing the correct loyalty rewards program software may be difficult. However, once you've made a decision the accounting becomes easy.

    Enlist a software that can analyze loyalty program data, build a predictive model and provide a user-friendly platform, all while having a staff in place for assistance along the way. Once you've done this you can enjoy the benefits of a platform that gives you immediate progress. Loyalty rewards program software enables anyone in your organization to do self-service analytics in a sophisticated way.

    Enjoy this advantage and convenience:

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    Len Llaguno

    Founder and managing partner of KYROS Insights. I'm an analytics nerd and recovering actuary. I use machine learning to help loyalty programs predict member behavior so they can identify their future best customers, and recognize and reward them today.


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