Product

Baims Chat

A live messaging product across web, iOS, and Android, shaped by 200+ research participants and adopted by around 50% of instructors.

Role

Product Designer

Team

Five people

Timeline

8 weeks

Platform

Web, iOS & Android

Role

Product Designer

Team

Five people

Timeline

8 weeks

Platform

Web, iOS & Android

Overview

The course ended in Baims. The conversation continued somewhere else.

Baims already handled learning content, but students and instructors moved to WhatsApp or Telegram to ask questions, share materials, and keep class conversations going.

I was the Product Designer on a five-person team. I co-designed Baims Chat across web, iOS, and Android from 0-to-1 in eight weeks. My scope covered user research, UX and UI, prototyping, and usability testing.

We launched Baims Chat inside the live Baims web, iOS, and Android products. Around 50% of instructors adopted it over WhatsApp and Telegram.

50%

Instructor adoption

Approximate post-launch figure

200+

Research participants

Students and instructors

8 weeks

0-to-1 delivery

Web, iOS & Android

Problem

Course messages were scattered across external apps

Students watched lessons in Baims, then left the product to speak with instructors and classmates. Questions, group work, and shared files lived in WhatsApp or Telegram. The course and its conversations were split across different products.

Baims needed its own communication space. It had to cover the chat habits people already knew while supporting learning tasks such as group conversations, shared media, and finding older messages.

Research

More than 200 students and instructors shaped the product scope

I helped survey more than 200 students and instructors. The research set five requirements for the product: real-time messages, group conversations, multimedia sharing, message search, and secure account access.

WhatsApp and Telegram set the baseline. People already understood how to use them. Baims Chat had to feel familiar on first use while keeping course conversations connected to the learning product.

The brief grew beyond direct text messages. Students needed group work and shared files. Both students and instructors needed a way to find an older message without scanning a long thread.

Ideation

Keep familiar chat patterns and bring the course context with them

One option was to keep WhatsApp and Telegram in the workflow and add links or contact shortcuts. We built the conversation into Baims. This added product scope, but it kept students and instructors in the same place as their courses.

A teacher announcement feed would have been easier to control. The research called for student collaboration as well, so I designed for both direct messages and group conversations.

Class conversations included images, video, audio, and other course material. I included multimedia sharing and message search so useful answers and files would not disappear inside long threads.

Designs

The interface had to feel familiar on first use

I designed the experience across web, iOS, and Android around an inbox, direct and group threads, multimedia messages, and search. The interaction model followed chat patterns people already knew, so the product did not need to teach basic messaging behavior again.

The prototype covered entering a conversation, sending a message, moving between threads, sharing a file, and finding an older message. I used usability testing to check those tasks with students and instructors before launch.

Privacy and authenticated access were part of the product model from the start. Chat stayed tied to each Baims account, keeping course conversations inside the signed-in product.

Lessons

Instructors switched when chat became part of the product

After launch, around 50% of instructors moved their course conversations from WhatsApp and Telegram to Baims Chat. The feature shipped across web, iOS, and Android, giving students and instructors the same chat experience wherever they used Baims.

Familiar behavior helped the switch. Direct messages, group threads, file sharing, and search matched patterns people already knew, while keeping every conversation close to the course.