Featured case study · Retail · Delhi NCR

Urban Thread Retail turned WhatsApp into their #1 sales channel — in Hindi, English, and everything in between.

How a 12-store Delhi NCR retail chain used Go4whatsup's AI + auto-translate to drive +47% return customers, ₹32 L of monthly WhatsApp GMV, and cut support-call volume by 60%.

Womenswear retail · 12 stores · Delhi NCR · 85k customer base

1,500+businesses live
MetaBusiness Partner
4.4· 400+ reviews on G2
99.9%uptime SLA
GDPR · DPDPcompliant
"The auto-translate was the unlock. Half our customers message in Hindi, half in English, some mix both — Go4whatsup's AI handles it. FAQ answers go out instantly, my agents only see the real conversations. We shifted 40% of support off phone calls in the first month."
RM
Ritika Malhotra Head of Customer Experience · Urban Thread Retail
The story, in three parts

What changed — and why it worked.

Challenge

  • One support line across 12 stores was drowning — 450+ calls a day, most repeating the same "What's in stock at the Saket branch?" question.
  • Customer base is ~55% Hindi-first, ~45% English-first — existing chat tools forced agents to reply in one language or type both.
  • Repeat-customer rate was flat at ~28% despite strong in-store loyalty — no digital channel was bringing them back.
  • Marketing campaigns went out on email and SMS — open rates under 12%, conversion sub-1%.

Solution

  • AI auto-reply trained on Urban Thread's FAQ (stock, sizing, store hours, returns). 80% of incoming messages resolved without an agent.
  • Auto-translate — incoming Hindi messages auto-translate to English in the agent inbox; agent replies auto-translate back to Hindi. One team, two languages.
  • AI-drafted replies for the 20% that reach an agent — counsellors edit and send instead of typing from scratch.
  • Segmented broadcasts for repeat buyers — new drops, festive collections, store-specific offers — with AI-generated copy in both languages.

Results (90 days)

  • Return-customer rate jumped from 28% → 41% — a +47% lift quarter-over-quarter.
  • WhatsApp became the #1 sales channel, generating ₹32 L in monthly GMV (overtook walk-in and Instagram DMs).
  • Median reply time dropped from ~38 min to 4 min. CSAT went from 3.9 to 4.7 / 5.
  • Support-call volume fell 60% — one agent now handles what three used to.
What the real flows look like

The three templates doing the work.

Pulled from Urban Thread's live account. Customer names changed — numbers and copy are real.

1 · AI auto-reply · FAQ Resolves ~80% of messages · 0 agent time
HindiSaket branch mein saree collection hai kya? Aaj khula hai?
🤖 AI auto-reply Ji haan! Saket branch aaj 11 AM – 9 PM khula hai. Nayi saree collection (Diwali special) ab stock mein hai — photos bhej rahi hoon. 📸
📍 Get directions🛍️ Book fitting
HindiBook kar do 6 PM ke liye
✅ Fitting slot booked — 6:00 PM at Saket. See you soon!

Handled end-to-end without an agent. Booking syncs to the store's CRM.

2 · Auto-translate · Agent inbox One team · Hindi + English in parallel
Customer sent
Sunita: "Return kaise karoon? Packet kal aaya lekin size bada hai."
EN → "How do I return this? Package arrived yesterday but the size is too big."
Agent drafts
Priya (agent): "Hi Sunita, return ka pickup book kar doongi. Size exchange chahiye ya refund?"
HI ← Auto-sent to customer in Hindi
Agent sees English. Customer sees Hindi. Zero manual translation.

Agents don't need to speak Hindi — auto-translate handles both directions in real time.

3 · Broadcast · AI-written copy 14,200 repeat buyers · 41% click-through
Ritika typed →
"Announce new Diwali saree collection, 20% off early-bird for repeat buyers, valid till Oct 28."
↓ AI drafted in seconds
✨ Diwali Edit is live
Your favourites — new silk sarees in deep jewel tones. Repeat customers get 20% off until Oct 28. Walk in or browse here 👇
🛍️ Browse collection📍 Find a store
Hindi variant auto-translated and scheduled for Hindi-preference segment ✅

Ritika's team writes one prompt. AI produces the message in both languages, segmented and scheduled.

Week-by-week

How Urban Thread went live in 30 days.

Week 1

Meta Business verification + green-tick filing. Go4whatsup account provisioned. First 12 FAQ templates submitted to Meta for approval.

Week 2

AI auto-reply trained on Urban Thread's FAQ doc (stock, sizing, store hours, return policy). Auto-translate enabled — agents started seeing translated incoming messages.

Week 3

Agent inbox rolled out to 4 support staff. AI-drafted replies went live. First Instagram-to-WhatsApp click-to-chat campaign launched.

Week 4

Broadcast segmentation wired up (by store, purchase history, language preference). First festive broadcast sent — 41% CTR, ₹9.4 L GMV in 72 hours.

Week 5–6

Measurement dashboard wired to Go4whatsup analytics. Ritika's team reviewing a weekly report pinned to Slack. Return-customer rate climbing.

+47% return customers · ₹32 L monthly GMV
We had evaluated four WhatsApp platforms before Go4whatsup. The others could send broadcasts. Only Go4whatsup could read a Hindi message, auto-reply in Hindi from our FAQ, translate Hindi to English for our agents, and generate campaign copy in both languages — out of the box. We went from a flat 28% return-customer rate to 41% in one quarter. It's our #1 channel now.
RM
Ritika MalhotraHead of CX · Urban Thread Retail · Delhi NCR
Stack used

What powered the story.

WhatsApp Business API Go4whatsup AI Auto-translate Shopify (store catalog) Instagram click-to-chat

Want numbers like Urban Thread? Start this week.

Ritika's team shipped their first flow inside 2 weeks. Bring one metric — return-rate, GMV, CSAT, reply time — we'll show you the exact flow on the call.

We only onboard 30 new customers a month · This week has 8 slots left
📊Pick one metric. We'll show you the exact flow Urban Thread used to move it.
Meta Business Partner. Your WhatsApp API onboarding runs under our official Partner status — no six-month waiting room.
🎯Outcome, not onboarding. We stay on until your first number moves — at no extra cost.

💬 Or WhatsApp us the metric you want to move — we'll reply with a plan.