WhatsApp Tenant Support Agent
Post letting tenant support was consuming 130 hours a month in manual WhatsApp responses with inconsistent quality and no triage. a function that could be largely systematised without reducing the quality of complex case handling.
- Timeline
- Five week build with a supervised operation period, all agent responses reviewed by an adviser before sending, before autonomous resolution for category one queries was enabled.
- Scope
- Support inbox audit and query type classification, AI agent design and response library development, escalation protocol definition, CRM integration for tenancy data personalisation, and performance monitoring setup.
- Model
- The supervised operation period was used to validate response quality and calibrate the classification boundary between categories one and two. The autonomous resolution threshold was raised only when the error rate on category one responses had been below 2% for two consecutive weeks.
The outcome
Adviser involvement in standard queries reduced by 70%; average response time improved from hours to under five minutes.
Findings
What we built it around.
First response triage layer
incoming message classification into administrative, standard guidance, and complex/escalation categories
Administrative query resolution engine
pre approved responses for standard query types, delivered in the user's preferred language (English or Turkish), personalised with relevant tenancy details from CRM
Standard guidance response drafting
AI drafted responses for common issue types, routed to adviser for review and approval before sending, not sent autonomously
Escalation routing with context handoff
complex queries flagged immediately to the responsible adviser, with full conversation thread and query classification to enable informed response without re reading history
Interaction logging and query analytics
full audit trail of all conversations, with query type distribution reporting enabling ongoing improvement of the resolution layer
Results
What changed.
Average first response time for routine queries reduced from 4, 6 hours to under 5 minutes, the primary service quality complaint from tenants was response speed, and this was addressed without adding headcount
Adviser involvement in support queries reduced by over 70% for administrative and standard guidance categories, freeing approximately 90 hours per month of adviser capacity previously consumed by routine message handling
Out of hours coverage achieved: the agent responds to routine queries at any hour, eliminating the gap between a tenant sending a message at 10pm and receiving a response the following morning
Response quality consistency improved: standard guidance responses are now drawn from the same knowledge base for every subscriber, rather than varying by which adviser happened to respond
Escalation quality improved: complex cases now arrive at the responsible adviser with full context and classification, rather than as unread messages in a shared inbox, reducing the adviser time needed to orient before responding
Takeaway
Adviser involvement in standard queries reduced by 70%; average response time improved from hours to under five minutes.
Real estate / PropTech
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