Candidate sourcing on WhatsApp
JD push to talent pools, referral campaigns, alumni re-engagement and one-tap interest capture \u2014 fill the pipeline 4\u00d7 faster.
- JD push
- Referral
- Alumni
- Interest capture
Key things to know
JD push at scale
Referral campaigns
Alumni re-engagement
One-tap interest
People also ask
Q.Compliance?
Opt-in required.
Q.Bulk push?
Yes — with rate-limiting.
Q.ATS sync?
Yes.
Q.Multi-language?
Yes.
Q.Pool segmentation?
Skill, location, CTC.
Q.Pricing?
See /pricing.
Naukri InMail and email die at 8% open
Sourcing on email + InMail is dead — 92% of candidates never open it.
WhatsApp JD push hits 85% read in 5 minutes — 4× more responses, 60% lower cost-per-lead.
Built for serious growth teams
JD push at scale
Referral campaigns
Alumni re-engagement
One-tap interest
ATS sync
Sourcing dashboard
Get live in days, not months
- 1
Build talent pool
- 2
Push JD via WhatsApp
- 3
Candidate opts in
- 4
Routed to screening bot
What teams ship with this
Active req push
Referral drive
Alumni mining
Campus
Frequently asked questions
Why Candidate sourcing on WhatsApp is the highest-leverage move for growth teams
WhatsApp is where growth teams customers actually reply. Open rates sit at 85–98% inside 15 minutes versus 18–22% on email and sub-2% on SMS, and the medium is conversational — a customer can ask a follow-up, share a photo, or pay without leaving the thread. That is the entire premise behind candidate sourcing on whatsapp: stop losing the conversation to slow channels and let intent convert while it is warm.
Most growth teams teams treat WhatsApp as a broadcast megaphone. The teams that win treat it as a workflow surface — every notification is also a decision point where the customer can act. The capabilities below are wired to do exactly that: each one collapses a multi-step off-platform detour into a single in-thread reply.
The impact numbers on this page — 4× pipeline speed, 85% read rate, 3× response rate, -60% cpl — are pulled from LandinChat customers running this workflow for at least 90 days. They are directional; your mileage depends on list quality, template approval speed, and how aggressively you route qualified conversations to a live agent.
Each capability, in plain terms
JD push at scale
JD push at scale is delivered as a native LandinChat module — no external plug-ins, no separate dashboard. It ships pre-wired to the growth teams data model, so the first working version is minutes of setup, not a sprint. You can override defaults per campaign, per agent, or per customer segment. In practice this means the growth teams operator running candidate sourcing on whatsapp does not need to compose the logic themselves; they pick the trigger, review the copy, and let LandinChat handle rate-limits, template compliance, and retry behaviour.
Referral campaigns
Referral campaigns is delivered as a native LandinChat module — no external plug-ins, no separate dashboard. It ships pre-wired to the growth teams data model, so the first working version is minutes of setup, not a sprint. You can override defaults per campaign, per agent, or per customer segment. In practice this means the growth teams operator running candidate sourcing on whatsapp does not need to compose the logic themselves; they pick the trigger, review the copy, and let LandinChat handle rate-limits, template compliance, and retry behaviour.
Alumni re-engagement
Alumni re-engagement is delivered as a native LandinChat module — no external plug-ins, no separate dashboard. It ships pre-wired to the growth teams data model, so the first working version is minutes of setup, not a sprint. You can override defaults per campaign, per agent, or per customer segment. In practice this means the growth teams operator running candidate sourcing on whatsapp does not need to compose the logic themselves; they pick the trigger, review the copy, and let LandinChat handle rate-limits, template compliance, and retry behaviour.
One-tap interest
One-tap interest is delivered as a native LandinChat module — no external plug-ins, no separate dashboard. It ships pre-wired to the growth teams data model, so the first working version is minutes of setup, not a sprint. You can override defaults per campaign, per agent, or per customer segment. In practice this means the growth teams operator running candidate sourcing on whatsapp does not need to compose the logic themselves; they pick the trigger, review the copy, and let LandinChat handle rate-limits, template compliance, and retry behaviour.
ATS sync
ATS sync is delivered as a native LandinChat module — no external plug-ins, no separate dashboard. It ships pre-wired to the growth teams data model, so the first working version is minutes of setup, not a sprint. You can override defaults per campaign, per agent, or per customer segment. In practice this means the growth teams operator running candidate sourcing on whatsapp does not need to compose the logic themselves; they pick the trigger, review the copy, and let LandinChat handle rate-limits, template compliance, and retry behaviour.
Sourcing dashboard
Sourcing dashboard is delivered as a native LandinChat module — no external plug-ins, no separate dashboard. It ships pre-wired to the growth teams data model, so the first working version is minutes of setup, not a sprint. You can override defaults per campaign, per agent, or per customer segment. In practice this means the growth teams operator running candidate sourcing on whatsapp does not need to compose the logic themselves; they pick the trigger, review the copy, and let LandinChat handle rate-limits, template compliance, and retry behaviour.
How this actually rolls out
Step 1. Build talent pool
Build talent pool is the foundation of the candidate sourcing on whatsapp workflow. On day one, an onboarding specialist walks a growth teams operator through this step live; on subsequent campaigns, the team runs it themselves from the LandinChat console. Expect this step to take between 15 minutes and an afternoon depending on how clean your existing data is.
Step 2. Push JD via WhatsApp
Push JD via WhatsApp is the next unlock of the candidate sourcing on whatsapp workflow. On day one, an onboarding specialist walks a growth teams operator through this step live; on subsequent campaigns, the team runs it themselves from the LandinChat console. Expect this step to take between 15 minutes and an afternoon depending on how clean your existing data is.
Step 3. Candidate opts in
Candidate opts in is the next unlock of the candidate sourcing on whatsapp workflow. On day one, an onboarding specialist walks a growth teams operator through this step live; on subsequent campaigns, the team runs it themselves from the LandinChat console. Expect this step to take between 15 minutes and an afternoon depending on how clean your existing data is.
Step 4. Routed to screening bot
Routed to screening bot is the final lock-in of the candidate sourcing on whatsapp workflow. On day one, an onboarding specialist walks a growth teams operator through this step live; on subsequent campaigns, the team runs it themselves from the LandinChat console. Expect this step to take between 15 minutes and an afternoon depending on how clean your existing data is.
How different teams put this to work
Active req push
Active req push teams deploy candidate sourcing on whatsapp to compress the gap between intent and action. The common failure mode we see is over-templating — sending the same broadcast to every segment. The teams that outperform run at least three variants keyed to recency, spend tier, and language, and they measure reply-rate not open-rate.
Referral drive
Referral drive teams deploy candidate sourcing on whatsapp to compress the gap between intent and action. The common failure mode we see is over-templating — sending the same broadcast to every segment. The teams that outperform run at least three variants keyed to recency, spend tier, and language, and they measure reply-rate not open-rate.
Alumni mining
Alumni mining teams deploy candidate sourcing on whatsapp to compress the gap between intent and action. The common failure mode we see is over-templating — sending the same broadcast to every segment. The teams that outperform run at least three variants keyed to recency, spend tier, and language, and they measure reply-rate not open-rate.
Campus
Campus teams deploy candidate sourcing on whatsapp to compress the gap between intent and action. The common failure mode we see is over-templating — sending the same broadcast to every segment. The teams that outperform run at least three variants keyed to recency, spend tier, and language, and they measure reply-rate not open-rate.
Buyer’s checklist
- • Official Meta Tech Partner — templates approve faster and account is not at ban risk.
- • Native growth teams data model — no glue-code to import contacts, orders, or bookings.
- • Green-tick support with a clear submission checklist and Meta-side follow-up.
- • Conversation-based pricing that matches WhatsApp’s own billing model, not per-message surcharges.
- • Human handoff with unread routing, so qualified replies never sit in a bot loop.
- • Audit log & role-based access — required for regulated enterprise buyers.
Common pitfalls
- • Broadcasting cold lists — quickest way to a quality-rating downgrade and eventually a template ban.
- • Skipping opt-in capture — makes every future utility template harder to approve.
- • Treating WhatsApp as a one-way channel — the platform penalises accounts with low reply-rate.
- • Running only one template variant — you leave 20–40% of lift on the table.
- • Not routing hot conversations to a human within 5 minutes — kills conversion by up to half.
What to measure after launching candidate sourcing on whatsapp
Week 1 signal
Track template approval time, first-reply latency, delivered-rate, and the first 100 customer replies. For growth teams, the fastest warning sign is not low opens; it is customers replying with confusion because the trigger, offer, or handoff promise was not specific enough.
Month 1 signal
Compare reply quality across JD push at scale, Referral campaigns, Alumni re-engagement, One-tap interest. The best-performing growth teams teams keep the highest-intent replies visible to managers, then rewrite templates around real customer language instead of internal terminology.
Scale signal
Once Build talent pool → Push JD via WhatsApp → Candidate opts in → Routed to screening bot is stable, scale by segment rather than volume. Add new audiences only when opt-in source, template intent, agent ownership, and conversion tracking are all mapped.
Search-quality notes for this workflow
This page is intentionally built around candidate sourcing on whatsapp rather than a generic WhatsApp marketing overview. The content references the actual workflow, the growth teams audience, implementation steps such as Build talent pool, Push JD via WhatsApp, Candidate opts in, Routed to screening bot, and use cases like Active req push, Referral drive, Alumni mining, Campus. That specificity helps buyers, internal teams, and search engines understand why this page deserves to exist separately from broader WhatsApp CRM, broadcast, chatbot, and automation pages.
Fill the pipeline 4\u00d7 faster
JD push, referral, alumni \u2014 one platform.