Real Estate Case Study: −67% CPL with an AI Voice Agent | PrimexAI
AI Real estate · Speed-to-lead, database reactivation, qualification

AI voice agent for a real estate brokerage

A high-volume real-estate brokerage: 41,280 calls, −67% CPL. The AI answers inbound inquiries in seconds, reactivates your CRM database, qualifies buyers and sellers against your criteria, and hands agents only the hot leads. Integrates with Follow Up Boss, HubSpot, kvCORE and Salesforce.

40,000+
calls a month per AI agent — with no extra hires on the sales floor
24/7
lead follow-up and database reactivation, never gated by how busy your agents are
−90%
cheaper than a human ISA at the same conversion into qualified interest
Where real estate loses leads

4 leak points between the lead and the deal

In real estate a lead costs $8–17. If it never makes it to a showing, that spend is gone. The AI closes the gaps on response speed, aged-database reactivation, and qualification.

Scenario 01

The lead goes cold within an hour

Reality
An inquiry on a listing comes in:
  • in the evening, on a weekend, during peak hours
  • the agent calls back the next day
  • the lead already booked a showing with a competitor
The AI answers in seconds, qualifies the interest, and books the showing before the lead walks.
Scenario 02

The old database sits idle

Reality
Your CRM has piled up:
  • leads that never made it to a showing
  • clients who toured but never bought
  • "let me think," "buying in six months" — then silence
  • people who passed on specific listings
5,000–50,000 contacts sitting idle. Meanwhile you keep buying fresh leads at $8–17 each.
The AI works the old database 24/7 and pulls a share of those leads back into the active funnel.
Scenario 03

Agents are buried in busywork

Reality
Agents burn time on:
  • "did you submit an inquiry?" calls
  • first-pass questions about listings
  • qualification (budget, area, financing)
  • booking and rebooking showings
Agents should be closing deals — instead they're chasing leads who already passed.
The AI takes first-touch calling and qualification. Agents work only the hot leads.
Scenario 04

Weak first-pass qualification

Reality
Showings get booked with:
  • buyers out of budget range
  • people who can't get financing
  • "maybe in a year" browsers
  • fake contacts
Agents lose hours on showings that should never have been booked.
The AI asks the qualifying questions, screens out the wrong-fit leads, and books showings only for the right ones.
🎙 Real call recording Inbound lead
Take a listen
The AI sales agent on an inbound lead about a property listing
0:00
🎙 Real call recording Database reactivation
Take a listen
The AI sales agent reactivating an aged lead from the CRM
0:00
How it works

The AI works inside your CRM, like a member of the team

It follows your playbook and scripts, logs tasks in the CRM, and transcribes every conversation. No migrations, no retraining your team, no switching systems.

🧩

Inside your CRM

We connect to Follow Up Boss, kvCORE, HubSpot, Salesforce and any other system via API. No migrations, no moving your leads and listings.

📋

On your scripts

Scripts are signed off with your sales lead. The AI asks the qualifying questions (budget, area, financing) and hands off to an agent for closing and booking the showing.

🎙️

Transcripts and tasks

Every call is transcribed, the key moments are highlighted, and hot leads are handed to an agent with a ready brief and a showing time.

Case study

A high-volume brokerage
41,280 calls and +690% buying interest
at a 67% lower cost per lead

A real project with a resort-real-estate brokerage. The AI sales agent worked 3.4× more contacts, surfaced 7.9× more buying interest, and cut cost per lead from $8 to $2.50. The team shrank from 12 people to 3.

Database reactivation + inbound flow

How the brokerage got 7.9× more interest from the same database

Client
A brokerage selling resort and second-home real estate
Goal
Work the database systematically and cut the cost of a qualified lead
Solution
AI sales agent on high-volume calling 24/7 + qualification + reactivation of the old database
Metric Before · 12 reps After · AI sales agent + 3 agents What it means
Call volume 12,018 41,280 +243% ↑ 3.4× more contacts dialed with no extra headcount
Conversations 2,617 17,370 +564% ↑ More first-touch contacts = more shots at a deal
Buying interest surfaced 137 1,083 +690% ↑ 7.9× more qualified leads from the same database
Conversion to interest 5.24% 6.2% +0.96% ↑ A systematic script holds conversion above a human's
Cost per interest $8 $2.50 −67% ↓ Same budget — a qualified lead 3.2× cheaper
Team size 12 reps 3 agents −75% ↓ 9 fewer seats = a major cut in payroll
Bottom line: 7.9× more interest from the same database and −67% cost per lead. The team went from 12 people to 3, and the three left work hot leads only.
+690%

High-volume calling

41,280 calls a month — a volume a team of human callers simply can't reach.

Reactivating the old database

210 leads pulled back into the active funnel — people who'd looked at listings but never closed.

Systematic qualification

The AI asks the scripted qualifying questions: budget, area, financing. Only the right-fit buyers get a showing.

Freeing up the agents

Routine calling goes to the AI. Agents focus on hot leads and closing deals — not "did you submit an inquiry?"

Benefits

Take the human factor out of your calls

100% of leads get called

Every inquiry and the entire old CRM database goes to work. No "didn't get to it in time," no "forgot to follow up."

No sick days, no weekends off

24/7, no mood swings. At 9:30 on a Saturday night it calls back exactly the way it does at 11 on a Wednesday morning.

No extra agents to hire

The AI handles high-volume calling and qualification. Agents work only the hot leads — showings and deals.

💰 −67% cost per lead on the same budget — it pays for itself on the very first database-reactivation campaign.
Deployment process

Simple onboarding in 4 steps

From the first call to fully automated lead flow — with no extra hires and no switching your system of record.

Step 01

Define the goal

With your sales lead we map the script: which leads the AI takes, the qualification criteria (budget, area, financing), and when to hand off to an agent.

Step 02

Connect the sources

Integration with Google Ads, Zillow, Realtor.com, Follow Up Boss, HubSpot, and Twilio telephony. No migrations, no switching systems.

Step 03

Run the pilot

We test on one lead source or one service line, review the conversations, tune the script, and run the numbers.

Step 04

Scale

Once it's validated, we connect every source plus old-database reactivation campaigns. A stable 24/7 calling operation.

FAQ

What brokerages usually ask

On most calls, no. The AI holds a conversation at the level of an experienced agent: it asks the right qualifying questions and talks listings and financing. If you want to disclose it's an AI up front, we can — it doesn't hurt conversion.

The AI closes for the showing — that's its job. A human agent closes the deal in person after the showing. The AI works the top and middle of the funnel: qualification, booking showings, database reactivation.

Yes. Integration via webhooks with Zillow, Realtor.com, Follow Up Boss, HubSpot, kvCORE and other real-estate CRMs. Leads drop into the AI's call queue automatically.

2–3 weeks for one segment (new construction / resale / commercial). Several segments plus markets — 4–6 weeks: time for script sign-off and integrations.

On the diagnostics call we run the numbers on your own data: lead volume, current cost per lead, conversion to showing and to deal. In our experience, payback lands within 1 month at a flow of 1,000+ leads/mo.

A basic deployment starts at $1,500. Full projects with high-volume calling (like the brokerage case above) run up to $22,000. We give you an exact number on the free diagnostics call.

We'll show you how an AI sales agent fits your brokerage specifically

30 minutes on Zoom. We run the payback and potential upside on your own numbers and give you a step-by-step plan to cut cost per lead and reactivate your database.

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