It sees opens, clicks and app events. It cannot see the chat where she said her child is vegetarian, that the last delivery was late, or that she is asking about a size you ran out of. Querygen reads those conversations, turns them into attributes and segments, and pushes them into the platform you already run.
My baby just turned 10 months. Can you suggest travel food? Also please no onions, we're vegetarian.
Attributes written
Pushed to her WebEngage profile
2sAdded to 9–12 months — travel recipe series sends before she travels.
Works alongside the stack you already run
The blind spot
Both of these are things you already have about the same person, on the same day.
What your platform recorded
Accurate, and it tells you almost nothing about what to send her next.
What she actually said
Do you have this one in size 8?
My kid is vegetarian — no onions please.
The last delivery was two days late. Again.
I'll send the payment tomorrow morning.
Every one of these should change what she gets next. Today, none of them do.
Behavioural + conversational
Behavioural data tells you what someone did. Conversational data tells you why, and what they want next. Segments built on both are the ones worth sending to.
Ananya S.
+91 •••• ••4821
From your app & website
From her conversations
Lands in Parents · 9–12 months · at risk
Skips the promo blast, gets the recipe series
What gets extracted
You define which of these matter to your business. Querygen reads every conversation against that list and writes only what you asked for.
Intent
Ready to buy, comparing options, chasing an order, or about to churn. Read from how the conversation is going, not from a form they never filled in.
Preferences
Vegetarian, allergic to nuts, prefers evening delivery, size 8, buys for a ten-month-old. Said once in a chat, then normally lost forever.
Objections
Too expensive, needed a size you were out of, wanted a feature you do not have. Aggregated across conversations, this is your roadmap and your pricing feedback.
Sentiment & risk
Repeat complaints, cooling tone, an unresolved issue. The people your next promo blast should skip — and your support team should call.
Lifecycle facts
A baby's age, a lease renewal date, a wedding month. Facts that should move a customer between segments on their own, without anyone remembering to update them.
Product interest
Every out-of-stock question and unmet request becomes a segment you can re-engage the day it lands back in the catalogue.
Conversation-triggered journeys
Today your journeys wait for a click or an app event. These fire on what the customer told you.
| What she said | Attribute written | Journey triggered |
|---|---|---|
| “My baby is 10 months old now.” | baby_age_months = 10 | Moves into the 9–12 month segment; the age-appropriate recipe series starts. |
| “The last delivery was late. Again.” | complaints = 2 | Held back from the next promo blast and routed to support instead. |
| “Do you have this in size 8?” | wanted_variant = size 8 | Back-in-stock alert fires the day that size returns. |
| “I'll send the payment tomorrow.” | payment_pending = true | Reminder sequence starts, and cancels itself when the payment lands. |
Where you are today
Worth being straight with you: Querygen is usually not a replacement for one of those platforms. It is the layer they have never had. Which of these you are depends on what you already run.
This is the common case
Keep it. Your team keeps building campaigns exactly where they do today. Querygen sits underneath as the layer that reads conversations and writes what it finds onto the customer profiles your platform already holds, over webhook. Nothing migrates, nobody learns a new campaign builder.
Also fine
Then you may not need a six-figure platform to start. Querygen already segments customers from their conversations and runs the follow-ups and campaigns itself. Plenty of teams begin here, and connect a bigger engagement platform later once the volume justifies it.
Running today
Happy Eaters runs parenting communities on WhatsApp where parents ask about recipes, milestones and travel food. Querygen was already answering those questions. The same conversations now update each parent's WebEngage profile — a baby's age, the milestone being asked about, the topics she keeps returning to.
A parent mentions her baby is ten months old. She moves into the 9–12 month segment and the travel recipe series reaches her before she travels. Nobody on the team tagged any of it.
Read the Happy Eaters case study192
parent questions answered
6
WhatsApp communities covered
16
approved content collections
91%
of normal chatter left alone
How it works
Link the WhatsApp Business number and Instagram account your customers already message. History stays where it is.
~10 minutes
Define the attributes worth capturing — dietary needs, lifecycle facts, product interest, complaint counts. Querygen reads every conversation against that list.
One working session
Attributes sync to WebEngage, CleverTap, MoEngage or Braze over webhook, and your existing journeys start firing on them.
Same day
Get started
The fastest way to judge this is on your own chats. Tell us what you run and we will show you the attributes Querygen would pull out and how they would land in your platform.
Message us directly. Ask about your specific stack, the webhook contract, identity matching, or how this holds up under your data-protection review.
Chat with us on WhatsAppStep 1 of 3
Three quick questions so the walkthrough uses your stack and your data, not a generic demo account.
Prefer to just talk to a human?
Message us on WhatsApp insteadNo, and we would rather you did not. Querygen is not another campaign builder — it is the layer that reads conversations and writes what it finds onto the profiles your platform already holds. Your team keeps sending campaigns from the same place they always have.
Over webhook. When Querygen extracts an attribute from a conversation, it pushes it to the matching customer profile in WebEngage, CleverTap, MoEngage or Braze — the same way an app event or a purchase would arrive. From there it behaves like any other attribute in your segments and journeys.
Matching is done on the phone number, which is the one identifier a WhatsApp conversation always carries and most customer databases already store. Where a profile does not exist yet, Querygen can create one rather than dropping the signal.
It reads the conversations your business is already a participant in — the ones arriving on your own business number and Instagram account. WhatsApp's end-to-end encryption stays intact: messages are decrypted on your device, not on our servers, and stored data is encrypted with access limited to your authorised team.
The attributes come from customers messaging your business directly, and you decide which ones are captured and retained — the extraction list is yours to define and change. Deletion requests can be honoured immediately. Bring your DPO or legal team to the walkthrough; this question comes up often and we would rather answer it early than late.
Sentiment scoring gives you a number on a conversation that already ended. This writes specific, usable facts onto a customer profile — a baby's age, a wanted size, a repeat complaint — where they can move someone between segments and start a journey on their own.
Signup starts at ₹9,900 + GST or $99 per month and includes one personal WhatsApp number, with credits at ₹1 / $0.01 each. Each additional personal number is ₹3,000 per month. No per-seat fees — which is usually the line item that makes enterprise engagement platforms expensive.
It is all sitting in conversations nothing in your stack has ever read. That is a reporting gap you can close this week.