Client: Myntra.com -
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, so much so that it can create disruption to the existing user flow as it is difficult to get users out of their comfort zone. Other than that, chat application with fashion context presented its own share of interesting problems that were fun to solve.
As Myntra had more than 10 million users and 8 million active users, I knew my action would impact millions of users and therefore I had to justify each design decision based on research data. The research was very crucial to the project. Each assumption I had was tested upon a sample group.
Explore various solutions
Based on my research I crafted some user scenarios, so as to help me mold solutions suitable for these unique 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."
"Bhosle wants to surprise his spouse with a watch, but has no idea about women’s watches."
"Tanvi, Aditi and Payal wants to shop together for the farewell."
"Liya is planning her sister’s wedding, she wants her cousins to wear shades of blue."
Myntra has a forum called “style forum” to ask fashion advice to the public. It is accessible from the menu on the left side within the app. Here 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.
A chat application inbuilt within the Myntra app, is accessible from the left menu. 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.
Solution II was chosen after some user testing. Users found this solution most apt as it gave the feeling of an instant messaging application. The other solution gave a forum like experience in which, as compared to option 1, the users didn't feel like opening up as much.
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.
With the advancement in natural language processing (NLP) and machine learning, it is possible to develop an AI-driven chatbot 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 such a system is built, it would be possible to integrate the bot with any messaging system, i.e. Slack, Facebook, Whatsapp etc. The user then, would not even require having the Myntra app installed to place an order.