Shubham Sinha

← Work

Live since 10 August 2026As Product Analyst

I went through about 10,000 chats before I built the bot.

My part
Research, workflow design, build
Built on
LimeChat, a WhatsApp chatbot platform
Result
Tickets down 65%

The question

Customers message us on WhatsApp about orders, products and their health. I wanted to know which of those questions a bot could finish on its own, and when a person had to take over.

What I did

I went through about 10,000 conversations in total and sorted them by what the customer wanted. Then I designed the workflow and built it on LimeChat.

The result

Since 10 August 2026, ticket volume is down 65% compared with before the bot went live. 80 to 90% of queries are resolved without an agent.

The next version, as Associate Product Manager

I went back to the contact data. 49% of chats were about orders, 31% were product questions and 24% were about consultations and health.

Share of chats by topic
  • Orders49%
  • Product questions31%
  • Consultations and health24%

Some chats cover more than one, so these add up to more than 100%.

What I decided for it

  1. Route each chat by what the customer wants.
  2. Answer order status from real shipment data.
  3. Give a product question one clarifying question before it goes to an agent.