What is the Customer Experience Improvement Program?

The Customer Experience Improvement Program is an optional program where anonymous information on how you use TurboLaw® Time and Billing is collected and transmitted to us periodically, without interrupting you. This information helps us identify which features to improve.

Other Questions

How does the program work? Will I have to answer questions? Will I be interrupted?

The program silently records statistical information on what options, features, and buttons you use most often in the program. It then sends this anonymous statistical data back to our servers and then clears the data that was sent to us from your computer.

It will never interrupt you or ask you any questions after you make your initial choice to either enroll or not enroll in the program.

Will I be contacted?

No. You will never be contacted because of or in relation to this program.

What data is being collected?

Only anonymous, statistical information on how you use the program is collected - what buttons you press most often, for example. A timestamp is also included so that we can chart usage over time, as is a random, unique number that is used simply to identify the data in our database.

How is the program "anonymous?" How is my privacy assured?

We take our customers' privacy very seriously. No personally-identifiable information about you, your computer, your license, or your software is ever transmitted. The program generates random, unique numbers to identify the data for our database, but these numbers cannot be traced back to you or your computer.

Is any of my client data transmitted?

No - your client data is never transmitted.

What if I change my mind?

The Updates tab of the Settings window allows you to change your enrollment in the program.

What is the purpose of the program?

The purpose of the Customer Experience Improvement Program is to allow us to see exactly how people are using the program - what buttons they click on most often, which features they use frequently, etc. A statistical analysis of this data is very helpful in identifying which features to improve, based on which features people use most often.