Week 20: Using AI to bring Voice of Customer data to life

The Experiment

One of my clients had a common challenge: they were collecting tons of customer feedback (NPS, CSAT, reviews, and surveys), but it was just sitting there; data points in spreadsheets and dashboards that nobody engaged with. The goal was to transform this valuable Voice of Customer (VoC) data from dusty numbers into something the entire organization would actually pay attention to, discuss, and act upon.

I wanted to see if AI could help turn dry customer feedback into engaging content that would spark conversation and build a true culture of listening.

The Process

Here's how I tackled it:

1. Identifying the Key Challenges

• Customer feedback was being collected but not widely shared

• When shared, it was presented in boring, static reports

• Teams weren't engaging with or acting on the insights

• The organization wanted to build a culture around customer feedback

• Change is difficult - people need compelling reasons to adopt new ways of consuming data

2. Developing an Engagement Framework

We developed a three-part approach to make VoC data more alive:

• Tell a Story: Help people understand the big picture

• Engage People: Make it interactive and spark curiosity

• Reinforce the Message: Help teams internalize what they've learned

3. Creating AI-Powered VoC Engagement Tools

Using various AI tools, I developed:

• Customer Courtroom Game: Used Claude to create an interactive game where team members decide what feedback is "guilty" or "not guilty" of being a real issue

• Classification Challenge: Built a web-based game where participants drag and drop 18 actual customer verbatims into correct categories within a 2-minute time limit. Those who reached 80% accuracy could screenshot their results to win Amazon vouchers

• VoC Videos: Generated short video summaries of key feedback themes

• AI Infographics: Used ChatGPT to transform feedback summaries into visually engaging infographics

• Customer Feedback Podcast: Leveraged Notebook LLM to create conversation-style podcast episodes highlighting key customer insights - a surprisingly engaging format that offered a different way to consume the data

4. Collaboration tool Integration

• Explored VoC Copilot Studio to develop a "Fact of the Day" channel in Teams

• Created easily accessible dashboards that update with new insights

• (I didn't do this one yet, but I like this idea of regularly drip feeding information through Slack or teams)

The Outcome

The transformation was noticeable. Rather than customer feedback being trapped in dashboards nobody looked at, it became part of daily conversation.

What surprised me most was how these interactive formats made people actually think about and engage with the feedback rather than just scanning and forgetting it. Its hard to gauge the immediate affects of an intervention like this (its pretty subjective), but people played games and talked about the podcasts and VoC interventions more.

Overall we saw teams starting to internalize customer perspectives rather than just viewing them as external data points.

Key Takeaway

Voice of Customer data becomes powerful when it's transformed from static metrics into engaging, conversation-worthy content. AI tools are great at this; taking the heavy lifting out of analysis and content creation while making feedback more accessible to the entire organization.

Pro Tips for Beginners:

1. Start With Small, Focused Games: Don't try to boil the ocean. Begin with quick, focused activities that highlight specific feedback themes rather than trying to communicate everything at once.

2. Let AI Handle the Boring Stuff: Use tools like ChatGPT to summarize and categorize feedback, then focus your creative energy on presentation formats.

3. Rotate Formats: Mix up how you present customer feedback—videos one week, games the next, infographics after that—to maintain interest and reach different learning styles.

4. Be Patient With Change: These activities take time to implement and adoption can be slow. Incentives (like those Amazon vouchers) help, but understand that building a feedback culture is a marathon, not a sprint.

Want to Try It Yourself?

• ChatGPT is great for summarizing and categorizing large volumes of feedback

• Claude excels at creating interactive game formats and scenarios

• Notebook LLM works well for turning feedback into audio content

The key is not just to collect customer feedback, but to make it impossible to ignore. When people are having fun engaging with VoC data, the insights naturally become part of your organization's DNA. Novelty helps :)