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Several people have asked me for tricks on how to artificially boost their NPS score. That question immediately sends off red flags that scare me. Why would you want to artificially boost your own NPS score and data? If so then your NPS data is meaningless and has turned into nothing more than a vanity metric.
The value of NPS data does not come from the “pat yourself on the back because we have a good score” but rather from being able to understand and quantify your customer feedback. Understanding this feedback allows you to improve it over time. Companies that have seen the most value (and thus received the greatest increases in their NPS scores) are those that strive to understand why they received a certain score, rather than focusing on the score itself.
Let’s put it a different way. Let’s assume we have two different companies in the same industry selling the same product. Company A has an NPS score of -5. Company B has an NPS score of -15. Both have the goal of getting to Positive 10.
Now let’s assume that these companies put action plans into place. Company A changes how their NPS survey is delivered so that their oldest and most frequent customers are queried. They falsely assume that since these customers have been around the longest and use their product the most they will have the best feedback. The opposite is actually true. These customer are often very complacent with how things are going otherwise they would not be around. These customers are incredibly important to your business, but they are not the ones who will provide the most valuable information on what improvements need to be made. After Company A changed their survey to target their older customers they saw an increase in their NPS score to positive 12. Company A falsely assumes this is a more accurate representation of their product. They focused more on increasing the score rather than understanding the reasons behind the score.
Company B however took a different approach. They decided to break their score down into user retention groups. Group 1 was new users (shown the survey within 24 hours of using the product), Group 2 was users who returned within 1 week of install date, group 3 was users who have been around for more than 1 month. Their results had dramatic differences. Here was their breakdown.
Group 1 had an NPS score of -40
Group 2 had an NPS score of 3
Group 3 had an NPS score of 26
Using this data Company B was able to realize that there oldest users were very happy with the product. However there was an issue in their value proposition to new users. There was opportunity at the start of their traffic funnel to convert more potential users into customers. As they dug deeper into the data they found that the majority of customer prospects found the service too expensive and the setup process too cumbersome. As a result Company B worked to streamline the setup process and provided a longer trial period. This in turn converted more users and their NPS score increased to a positive 14.
In both examples the NPS scores increased and met their goals. However the fundamental difference is that Company B used the NPS score to understand customer frustrations. With that data they changed their product and are now receiving more business. Company A however simply made the choice to ignore a portion of the customer base.
If you want to game your NPS score then you will find ways to do it. However it offers you little to no value. Instead strive to understand the data behind the score. Use the NPS score as a measure to show that your improvements are providing positive returns, rather than a score that is treated like pass/fail grading system.