Case studyMarketing & AdTech9 min read

ChatCart: turning WhatsApp from a customer service headache into a D2C brand's best sales channel

A D2C snacks brand had thousands of customers messaging on WhatsApp, answered by hand, and marketing blasts that got the number flagged as spam. We built ChatCart: a WhatsApp catalogue and checkout, segmented and consent-based campaigns, abandoned-cart recovery, an AI assistant for common questions and a shared inbox for the team.

19
Features shipped
4
Apps & platforms
5
Team members
14
Weeks to rollout
ChatCart WhatsApp catalogue and checkout
ChatCart: browse, buy and get support — in WhatsApp.
01

Three thousand unread chats

ChatCart's founder showed us a phone with thousands of unread WhatsApp chats: order questions, delivery updates, 'is this spicy?', and people who wanted to buy but did not want to visit the website. Two team members answered by hand. Occasional broadcast blasts to everyone got the number reported and restricted.

“Our customers already live in WhatsApp. We were making them leave it to buy from us.”

— ChatCart's founder
02

How customers wanted to buy

We read hundreds of chats and interviewed repeat customers. Many preferred ordering in chat, especially for repeat purchases. Most questions were answerable from the catalogue and policies. Customers were happy to receive offers about products they liked — not blasts about everything.

What we found in the chats
  • Many customers preferred to order in chat
  • Most questions answered by catalogue and policy
  • Blasts caused spam reports
  • Carts abandoned on the website could be recovered in chat
Creative workspace with plans
Hundreds of chats showed how customers wanted to buy.
03

Commerce and care in one conversation

Customers browse the catalogue, add to cart and pay by UPI without leaving the chat. An AI assistant answers common questions using only the brand's catalogue and policies, and hands over to a person when needed. Campaigns go only to customers who opted in, segmented by what they bought, with frequency limits.

The team works from a shared inbox that shows each customer's orders alongside the conversation.

04

The team

A small team with an AI engineer for the assistant.

1
Engagement lead

Chat analysis and launch.

1
Product designer

Chat commerce flows and inbox.

2
Full-stack engineers

WhatsApp integration, campaigns and inbox.

1
AI engineer

Assistant grounded in catalogue and policies.

5 people in total, working as one team.

05

Decisions we made

Agreed with the founder and marketing lead.

01

Link out to the website or buy in chat?

  • Send website links
  • Catalogue and checkout in chat

Our call: Catalogue and checkout in chat. Customers who preferred chat bought more when they did not have to leave it.

02

Blasts or segmented campaigns?

  • Broadcast to everyone
  • Opted-in, segmented campaigns with frequency limits

Our call: Opted-in, segmented campaigns with frequency limits. Relevance protected the number's quality rating and customer goodwill.

03

How much should AI answer?

  • AI answers everything
  • AI answers from catalogue and policies; hands over otherwise

Our call: AI answers from catalogue and policies; hands over otherwise. Grounded answers stayed accurate; people handled the rest.

06

Every feature, module by module

Everything that shipped for customers, the support team and marketing.

Customers
Buy in the chat.
  • 01WhatsApp catalogue

    Browse products in chat.

  • 02In-chat cart and checkout

    Order without leaving.

  • 03UPI payment links

    Pay in seconds.

  • 04Order updates

    Confirmation and delivery tracking.

  • 05Reorder in one tap

    Repeat past orders.

Support
Fast answers, human when needed.
  • 06AI assistant

    Answers from catalogue and policies.

  • 07Human handover

    Escalation with context.

  • 08Shared inbox

    Team works from one inbox.

  • 09Customer context

    Orders beside the conversation.

Marketing
Relevant, not spammy.
  • 10Opt-in management

    Consent captured and respected.

  • 11Segments

    By purchases and behaviour.

  • 12Campaign templates

    Approved message templates.

  • 13Abandoned cart recovery

    Reminders for opted-in customers.

  • 14Frequency limits

    Protect customers from overload.

Insight
Chat as a channel.
  • 15Campaign analytics

    Reads, clicks, orders and revenue.

  • 16Assistant analytics

    Questions answered and handovers.

  • 17Store integration

    Catalogue and orders synced.

  • 18Role-based access

    Support, marketing and admins.

  • 19Audit trail

    Campaigns and consent recorded.

ChatCart campaign builder with segments
Campaigns: consent-based, segmented and measured.
07

Launch

ChatCart launched with the catalogue and assistant first, then campaigns once enough customers had opted in. Chat became a meaningful sales channel, especially for repeat orders.

  1. Weeks 1–2
    Discovery

    Hundreds of chats analysed; customer interviews.

  2. Weeks 3–4
    Design

    Chat commerce and inbox flows.

  3. Weeks 5–11
    Build

    Catalogue, checkout, assistant, inbox and campaigns.

  4. Weeks 12–13
    Soft launch

    Catalogue and assistant live.

  5. Week 14
    Campaigns

    Segmented campaigns to opted-in customers.

08

What we learned

Meet customers where they are. Buying in chat removed friction for repeat customers.

Consent and relevance protect the channel. Segmented campaigns avoided spam reports.

Built with
  • Next.js
  • NestJS
  • PostgreSQL
  • WhatsApp Business Platform API
  • LLM assistant with retrieval over catalogue and policies
  • Payment links with UPI
  • AWS Mumbai
CTA Background

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