---
title: "Using Intercom to design Intercom - The Intercom Blog"
description: "A designer at Intercom explains how the team uses their own product to gather data-driven insights for design decisions, replacing intuition with evidence from real customer interactions. Support team members tag feature requests and confusing conversations, which the research team organizes by topic for easy access. In one example, the designer analyzed 120 conversations about multi-person messaging and found only 33% actually wanted that feature, while others needed handoff or transfer capabilities. In another, an automated message targeting users who sent one-to-one messages via the fully featured editor revealed within hours that the ability to duplicate messages was the missing feature. This approach ensures design solutions are based on real customer needs rather than surface-level requests."
---

# Using Intercom to design Intercom - The Intercom Blog

[Intercom](https://yomu.fyi/company/intercom) · Oct 9, 2026

**Type:** Explainer

## Summary

A designer at Intercom explains how the team uses their own product to gather data-driven insights for design decisions, replacing intuition with evidence from real customer interactions. Support team members tag feature requests and confusing conversations, which the research team organizes by topic for easy access. In one example, the designer analyzed 120 conversations about multi-person messaging and found only 33% actually wanted that feature, while others needed handoff or transfer capabilities. In another, an automated message targeting users who sent one-to-one messages via the fully featured editor revealed within hours that the ability to duplicate messages was the missing feature. This approach ensures design solutions are based on real customer needs rather than surface-level requests.

## Approach / What changed

Using Intercom’s tagging and automated messaging features to collect and analyze customer feedback and user behavior for design decisions.

## Takeaways

- Customer feedback should be analyzed for underlying problems, not taken at face value; only 33% of requests for multi-person messaging actually wanted that feature.
- Automated messages triggered immediately after a user action can provide timely insights into why users behave in certain ways.
- A significant portion of users may use a feature in unintended ways (30% of messages through the fully featured editor were 1:1), revealing unmet needs.

## FAQ

### How can designers understand customer feedback beyond feature requests?

By analyzing tagged conversations and reaching out to users for clarification, designers can uncover the underlying problems behind feature requests, as shown in the multi-person messaging example where only 33% actually wanted that feature.

### How can designers learn why users use a feature in a certain way?

By setting up automated messages that trigger immediately after the user performs the action, designers can ask users about their reasoning while it's fresh in their minds, as demonstrated with the 1:1 message editor usage.

### What is a common mistake in product design according to the post?

Basing design decisions on assumptions and intuition without data from real customer interactions, which can lead to solving the wrong problems, as the post emphasizes with its data-driven approach.

**Tags:** [Customer Feedback](https://yomu.fyi/topic/customer-feedback), [Intercom](https://yomu.fyi/topic/intercom), [Product Design](https://yomu.fyi/topic/product-design)

- Source: [Intercom](https://www.intercom.com/blog/using-intercom-design-intercom)
- Source URL: https://www.intercom.com/blog/using-intercom-design-intercom
- Ingested by Yomu: 2026-10-09T12:01:23.179Z

[Read original post](https://www.intercom.com/blog/using-intercom-design-intercom)