Data Completeness for NPS

If you’re currently using NPS®, you may have noticed the “Data Completeness” widget within the related reporting section of your office dashboard.

This article explains what data completeness means, why it matters, and how to improve it.

Data completeness is the percentage of your properties for which we had enough contact information to send an NPS survey.

To send a survey, we need:

If a property is missing both contact methods, we cannot survey that customer. Your data completeness score reflects how often this happens across your office.

If 100 of your properties were eligible for surveying but we only had usable contact details for 55, your data completeness score is 55%.

You can view data completeness three ways:

Most data completeness gaps come from missing customer details at the point of sale. To improve your score:

We cannot retroactively add missing contact information after a survey has gone out for a property. If a property goes through without contact details on file, that survey opportunity is missed.

If you can backfill data before the survey sends, the survey will still go out. Under the new combined flow, that window is shorter than it used to be because surveys now trigger at confirmation of sale rather than settlement.

Low data completeness means a lower response volume, which means your NPS score is based on a smaller sample. The lower your sample, the more each individual response moves the score, and the less representative the number is. Keeping data completeness high gives you a more reliable score and a more honest picture of how customers feel.