Net Promoter Score (NPS)
Customer feedback is one of the most valuable things a business can get, but making sense of it can be tricky.
At Entteri, we help our customers collect feedback through something called Net Promoter Score (NPS). It’s a simple survey. After using a service, customers rate their experience with a number and can also leave a short comment. The numbers are easy to track, but the real treasure often lies in the comments and that’s where things get complicated.
Since the start of the year, we have a talented trainee, Samuli Ronni, join us to tackle exactly this challenge. At first, the idea was to forecast NPS numbers over time but after digging deeper, we realized:
➔ Numbers alone don't tell the full story.
➔ To really help our customers, we needed to understand why people give the feedback they do.
So, the project shifted focus:
1️⃣ Analyzing the written comments using machine learning.
2️⃣ Finding the main topics customers talk about like staff behavior, prices, or booking experiences.
3️⃣ Understanding the sentiment behind the comments whether people felt positive, negative, or neutral.
In simple terms: instead of just looking at the score, businesses can now quickly see what’s driving customer happiness (or frustration). This means they can focus their improvements exactly where it matters most.
💬 To bring this idea to life, Samuli also built an early version of an interactive tool that visualizes these insights:
📊 Topic distribution : what customers talk about most.
📈 Sentiment distribution : the overall mood behind the feedback.
🧠 Categories by sentiment : which topics are linked to positive, neutral, or negative experiences.
These visual insights help businesses easily spot where things are working well and where there’s room to improve. It’s a prototype for now but it shows how feedback could become a lot more powerful and actionable.
In patient management systems like AssisDent, NPS feedback can be seen as just the tip of the iceberg. There’s a huge amount of untapped potential to use machine learning and data analytics more broadly. For example, we are currently planning a comprehensive analytics and prediction view for the fiscal side of AssisDent, helping practices manage not just patient satisfaction, but also their business performance.
🚀There’s a lot more to come and we’re just getting started!
👏 Big thanks to Samuli, who is about to graduate from Häme University of Applied Sciences, HAMK with a Bachelor’s degree in Business Information Technology, specializing in data analytics and machine learning.
Your work has already made a difference!