How to Use AI to Reduce Customer Churn

Using AI to Fix Churn

Insight from Eli Weiss

In a previous role, customer retention was a major problem for one of our ancillary products.

If we could figure out how to stem the bleeding, we could increase revenue to meet OKR goals.

Understanding the root causes of customer churn was akin to deciphering a complex puzzle. It's not just about 'fixing' retention; it's about comprehending the layers beneath it.

Take NPS (Net Promoter Score), for instance.

It was our initial compass, yet its limitations soon became clear. Low response rates and its nature as a lagging indicator often left us chasing shadows rather than addressing current issues.

But it wasn't all gloom.

NPS, while basic, offered us a glimpse into our customer's pulse.

I recall a significant revelation: many detractors rated us poorly due to our customer response time. This insight led us to introduce expanding staffing, gradually reducing dissatisfaction.

Then there were the endless hours I spent combing through customer conversations in Zendesk. The tool held a treasure trove of insights, but I only knew one way to review these tickets.

Enter AI and Natural Language Processing (NLP). Imagine a tool that could sift through the chaotic sea of customer feedback, extracting pearls of wisdom with precision and speed.

It's like teaching a computer to decode the intricacies of human language - a task as complex as it sounds.

Tools now can allow you to dive deep into the emotional states, pain points, and areas needing improvement.

We prioritized these insights. We ensured they were not just confined to reports but were a catalyst for cross-departmental collaboration. Regular meetings with the product, operations, and marketing teams became forums for brainstorming.

Collaboration was key.

We broke down silos, encouraging a free flow of information and ideas. Our approach was iterative; we refined our strategies based on ongoing customer feedback.

By combing through our customer tickets, we reduced churn enough to reach a healthy MRR for the rest of the quarter!