Client: -

Collaborative shopping


Shopping is generally an activity performed together with friends, partners or family members. The fashion shopping experience becomes lively and enjoyable with the presence of our loved ones. They help guide our choice, provide opinions on different looks and help make a purchase decision. The chat feature within the Myntra app will allow users to chat with their friends and family members to discuss fashion, get feedback on products they like and help make a purchase.


As this tool was absent in the application, users had already found alternative paths to achieve this. Hence the proposed solution had to outperform the existing system in both efficiency and simplicity. Other than that, chat application with fashion context presented its own share of interesting problems that were fun to solve.

Myntra had more than 8 million active users, research was very crucial to the project. Each assumption I had was tested upon a sample group.

Research icon
Create a set of research goals, and carry them out one by one.

December 2015

Develop leads icon
Develop leads
Generating leads and insight from the research.

User Stories icon
User Stories
Creating hypothetical scenarios to better understand user needs.

Explore various solutions icon
Explore various solutions
Multiple Iterations and brainstorming sessions.

Develop Workflow icont
Develop Workflow
Drafting ideal user workflow

Prototype icon
Creating quick and rough prototypes to user testing and validation.

Validate icon
Validate the created prototypes with real users.


I crafted some user scenarios, so as to help me mold solutions suitable for those scenarios. Each scenario poses unique use cases.

"Varsha wants to buy a good top that goes with the skirt she bought, she wants to ask her friend."

Scenarios #1

"Bhosle wants to surprise his spouse with a watch, but has no idea about women’s watches."

Scenario #2

"Tanvi, Aditi and Payal want to shop together for the farewell."

Scenario #3

"Liya is planning her sister’s wedding, she wants her cousins to wear shades of blue."

Scenario #4

Solution I

Myntra has a forum called “style forum” to ask fashion advice to the public. Where users can post questions or polls for the public to answer. Users can tag products with questions.

Using the existing infrastructure of style forum, my solution was to add privacy settings within the forum when the user posts a question. From these settings, users can toggle from public access to an invite-only model. The question and the answers are then limited only to the users who get an invite.

Solution II

A chat application built within the Myntra app. App populates contacts from Facebook, the phonebook, and also with the people whom you follow on Myntra. Users can share items, get feedbacks, all without leaving the Myntra experience.

Users can pick the friends that they want an opinion out of, from the list, share products, video, image, Pintrest boards etc with them.

Final Call

Solution II was chosen after some user testing. Users found this solution most apt as it gave the feeling of privacy and users where opening up more.

A lot of time was dedicated to polish and to refine the solution. First, only the most essential features were developed. Then more additional features were introduced to add value to the product. Each new addition was then user tested and the feedbacks were accommodated.

chat ui homescreen
chat ui

The Vision

With the advancement in natural language processing (NLP) and machine learning, it is possible to develop an AI-driven shopping assistant in the near future.

Such a system would be able to give out suggestions to users, give the status of the order, and even more powerful actions which is not possible currently within the Myntra app, like rescheduling orders on the user's behalf. Users would be able to interface the Myntra app through talking with the bot.

If the bot is intergrated with other messaging system, i.e. Slack, Facebook, Whatsapp etc. The user then would not even require having the Myntra app installed to place an order.

chatbot ui