Dec 09, 2019

Release Notes: September 30, 2019

Using Custom Payment Methods to Track Lost Revenue

There are so many Payment Methods already available in Limo Anywhere – including all kinds of credit cards, vouchers, cash, check, donation, refund, trade, even barter! How could you possibly want more? The truth is, custom Payment Methods can be used in many ways, and we’ve seen some great creative options from Limo Anywhere users. A couple of our favorites are ways to help you track and quantify “lost” revenue:

Service Failure – When the unthinkable happens, and it DOES happen (even to the best of us!), do you know how it affects your bottom line over the course of the month, the quarter, the year? A great way to quantify this lost revenue is to use “Service Failure” as a payment method. Rather than changing the value of the trip, create a payment method called “Service Failure” (or something similar) and use it to record a ‘payment’ for the affected trip. We’ve seen this used as one blanket payment method, or broken out into types of service failures, such as “SF – Late,” “SF – Reservation,” “SF – Vehicle,” and so on.

Bad Debt – There comes a time when an overdue payment might need to be written off as bad debt (I’ll refer you to your Accountant for that decision). To get that past-due amount off your LA tracking, you could zero it out. But for better tracking, you might consider using “Bad Debt” as a payment method to keep a handle on the dollar amount you are losing to unrecoverable debt.

By using custom Payment Methods in this way, you have the ability to track these “lost” dollars in Limo Anywhere. Using the new Reporting & Analytics make it easy to filter out (hide) these Payment Methods in your Sales Revenue report, so you can still pull a report showing actual revenue taken in. And you can run a separate report, showing only these Payment Methods, to get a handle on where your lost revenue is going. By identifying not only these trips, but also the lost dollars involved, you’ll be able to make better, data-informed course corrections.