How We Automated User Interview Scheduling Using AI & No-Code Tools

Tired of manual user interview scheduling? Learn how we automated this process at Alan using AI and no-code tools, reducing scheduling time by 90%. Discover our step-by-step approach to identifying relevant users, sending personalized invitations, and maintaining data privacy.

As a Product Manager, conducting regular user interviews is crucial for building user-centric products. However, identifying the right users and scheduling interviews can be time-consuming and repetitive. With competing priorities and little time, these small frictions can quickly become an excuse to skip this critical step.

I built an automated workflow that identifies users who have successfully or painfully used a specific part of our product, reaches out to them, and handles interview scheduling - all while maintaining data privacy and security.

First, I needed to identify users who potentially struggled with our coverage table. I used AI to help write a SQL query that finds users who:

This pattern suggests they couldn't find what they were looking for, making them perfect candidates for user interviews.

Here is the prompt I used to craft the query:

I used the prompt with a custom-AI agent that has the context of our data tables, using the great platform Dust.

💡Tip: Any direction you can give to the AI will reduce hallucination! For example, giving the table names can greatly help.

Then, I created a weekly automation flow on activepieces (a self-hosted Zapier alternative, powering automations while preserving security) that:

💡Tip: You can pre-populate the invitee fields in the Calendly scheduling page to remove friction and maximize your conversion rate!

The automation slashed my scheduling time by 90% - turning an hour of weekly busywork into a quick 5-minute check.

By reaching out to members right after they experienced friction with our coverage features, our response rates jumped significantly. Combined with friction-free scheduling, I’m now conducting 2-3 user interviews on a weekly basis, gathering meaningful insights.

The best part? The system maintains the human touch while handling the technological parts. Each message is personalized, secure, and users feel valued – not like they're part of an automated system.

Finally, experimenting, editing, and scaling is made easy with this approach. It takes me only a few minutes to A/B test copies or to duplicate the flow for another use case.

As PMs, embracing AI and automation allows us to focus on what truly matters: understanding our users and building better products.