Finding the ads that actually sell apartments
A mid-size Dubai brokerage
Illustrative scenario. An anonymized composite from our real estate playbook with modeled figures — shown to explain the approach, not as a verified customer claim. Named, audited case studies are in production with early customers.
Team
9 agents, 1 marketing lead
Channels
Instagram & Facebook CTWA ads, portal listings
Volume
~600 ad-driven chats / month
The challenge
Every campaign produced hundreds of WhatsApp chats, but reporting stopped at cost-per-conversation. Nobody could say which ad produced viewings — let alone commissions — so budget went to the campaigns with the cheapest clicks, not the best buyers. Agents also burned hours qualifying obvious mismatches.
What they set up
- Buy/rent qualifier flow answers every ad chat instantly (Arabic/English), capturing budget, area and property type before an agent touches it.
- Hot leads auto-tagged and assigned; agents open conversations with the full context attached.
- CTWA attribution stamps each conversation with the exact ad; when a deal is marked Won with its value, revenue reports per ad.
- Weekly review: the Performance-by-ad report decides where next week's budget goes.
The numbers (modeled)
| Metric | Before | After |
|---|---|---|
| First response to ad leads | 31 min avg | < 1 min |
| Agent time per unqualified chat | 8–10 min | ≈ 0 (flow-handled) |
| Ad budget attributable to revenue | 0% | 100% of CTWA spend |
| Spend on non-converting campaigns | unknown | cut after week 2 (reallocated) |
What changed
The budget conversation changed from “this ad gets cheap leads” to “this ad produced AED 2.1M in closed deals.” Two campaigns that looked great on cost-per-chat turned out to produce zero viewings — that money now runs the two campaigns that close.
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