NPS

June 2022

Objective

Develop a consistent framework for measuring NPS and democratize access to the data to identify trends of satisfied customers and provide services teams viability into customer health.

Challenges

  • Inconsistent Capture - there was not a consistent cadence where NPS was being measured

  • Biased Data - we were primarily surveying happy customers for marketing purposes

  • Limited Personas - NPS was sent via email to solution owners, not our end users

Way Forward

  • Ongoing Capture - Create a consistent cadence for measuring NPS

  • Accurate Data - Create a measurement framework that randomly samples users for non-biased data

  • Reaching All Personas - Develop in-app process, so we can reach end users

Process

Stakeholder Alignment - In order to kickoff this new process, I had to get all cross-functional stakeholders aligned. I communicated with the Director of Services, VP of Account Management, & VP of Customer Marketing about the new process of quarterly NPS pulses, random sampling process, and communications to their team about when pulses will occur. Meeting with them and sharing the process gave them more confidence about the plan and generated excitement that there’s user-data they would be able to use to keep pulse of customer satisfaction overtime.

Building & Launching NPS - I utilized the tool Chameleon to build the in-app NPS pulse and needed to integrate it with Amplitude to create targeted segments to send the NPS to.

Building NPS Dashboard via Tableau - I developed a Tableau dashboard to provide people across the company visibility into our NPS scores. I created multiple cuts to view the data, for example: license type, company size, industry, and by domain. The results + deep dive of the data (e.g. why did we see a rise or fall in NPS for a given segment?) is shared with the C-Suite + Leadership across the company every quarter.

Deeper Analysis - Regression

Multi-Regression Analysis

I utilized qualitative coding to categorize the comments we received to run a multi regression analysis in order to understand the predictors of customer satisfaction.

Results

From the regression analysis we were able  to uncover the drivers of NPS and found that UI/UX was statistically significant. This means that improvements in UI/UX can increase NPS scores 3-4 points, making detractors and passives to become promoters. 

Impact

  • The results of the regression analysis led to investments in improving UI/UX and led to a UX Refresh of our whole platform. When comparing NPS of those who adopted our UX Refresh vs. those who remained on the Original UX, we found there was a +12 point increase in customer happiness for those utilizing the New UX

  • NPS data is utilized by various teams throughout Highspot to keep pulse on customer health

  • NPS was the first introduction to utilizing in-app surveying and has paved the way for an initiative I’m leading, called “Guided Experience” where we are using in-app product tours, announcements, etc. to guide users on how to utilize different features across the platform

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