Executive Summary
A two-office brokerage in the Mountain West had more than 14 000 “likely-to-sell” homeowner records drawn from predictive-analytics vendors, expired listings, and neighborhood farming. Agents manually cold-called these owners, reaching fewer than 6 % and booking only 11 listing appointments per month.
We deployed an outbound AI voice-dialer powered by our proprietary “SELL” script and a CRM-driven cadence workflow. In the first 90 days the brokerage:
- Reached 68 % of targeted homeowners (vs 6 % before).
- Converted 38 % of reached owners into listing consultations.
- Booked 248 seller appointments—a 462 % increase.
- Cut agent cold-call time by 73 % and reduced cost-per-listing appointment by 65 %.
1 Introduction
Background of the Client
- Industry: Residential real-estate brokerage
- Size: 55 licensed agents, 2 offices
- Location: Denver & Colorado Springs, CO
- Founded in 2010 with a specialty in mid-price suburban listings.
Context of the Problem
A record-low listing inventory made outbound prospecting essential. Yet manual cold-calling during business hours produced minimal conversations and high agent burnout. Meanwhile, analytics indicated nearly 18 % of contacts planned to sell within 12 months—an untapped goldmine if reached promptly and persistently.
Purpose of the Case Study
Demonstrate how AI voice agents—driven by an exclusive seller script and fully automated workflow—can revive dormant homeowner lists, multiply listing appointments, and free agents for high-value activities.
2 Challenges and Objectives
| Challenge | Impact |
|---|---|
| Low live-answer rate (6 %) | Few listing conversations; wasted lead spend |
| Agent time drain (15 hrs/wk cold-dialing) | Lower productivity & morale |
| Inconsistent messaging | Variable data quality; compliance risk |
| Slow follow-up cadence | Leads cooled before second attempt |
Objectives & KPIs
- Reach ≥ 60 % of outbound seller list within 4 contact attempts.
- Convert ≥ 30 % of reached homeowners to listing consultations.
- Reduce agent dialing time ≥ 60 %.
- Book ≥ 200 seller appointments in 90 days.
3 Solution
Strategy Development
- AI Outbound Dialer — Cloud voice AI initiates calls at optimized times with multi-day cadence.
- “SELL” Script — Four-stage framework: Spark rapport, Establish motivation, Leverage market data, Lock appointment.
- Automated Workflow — Real-time CRM updates, instant calendar blocks, SMS/email confirmations to homeowner & agent.
Implementation Timeline
| Week | Key Activities | Stakeholders |
|---|---|---|
| 1 | Data cleanup & DNC suppression | Operations, Compliance |
| 1 | Script localization (market stats, broker USP) | Sales Enablement |
| 1 | LLM training & objection-handling tuning | AI Engineers |
| 1 | Integrations (Our Own CRM, Calendly, Slack) | DevOps |
| 2 | Pilot on 2 000 records; live QA monitoring | RevOps, QA |
| 2–3 | Full rollout to 14 000 leads; daily dashboard reviews | Project PM |
| 2-3 | Optimization & hand-off | Customer Success |
Tools & Technologies
- Twilio Programmable Voice – High-volume outbound dialing.
- Custom LLM + LangChain – Dynamic conversation & context memory.
- LangSmith – Prompt experiments, analytics, compliance audits.
- Zapier Webhooks – CRM status changes, Slack alerts, automated SMS recap.
- Google Looker Studio – KPI dashboards for leadership.
4 Results and Outcomes
Quantitative Results (First 90 Days)
| KPI | Before AI | After AI | Δ |
|---|---|---|---|
| Live-answer / reach rate | 6 % | 68 % | +62 pp |
| Consultation conversions | 19 % | 38 % | +19 pp |
| Listing appointments | 44 / quarter | 248 / quarter | +462 % |
| Agent cold-call time | 15 hrs/wk | 4 hrs/wk | −73 % |
| Cost per appointment | $128 | $45 | −65 % |
Qualitative Results
- Homeowner Experience: 4.6 / 5 satisfaction (“informative, not pushy”).
- Agent Feedback: More time for CMAs, staging, negotiation; morale boosted.
- Brand Perception: Social mentions of “proactive, tech-forward brokerage” up 29 %.
Comparison to Objectives
- Reach: 68 % (goal 60 %).
- Conversion: 38 % (goal 30 %).
- Dial time reduction: 73 % (goal 60 %).
- Appointments: 248 (goal 200).
- Unexpected win: pipeline predictability—CRM stages auto-updated, enabling accurate 90-day revenue forecasting for the first time.
5 Conclusion
Summary
Outbound AI voice agents armed with a specialized seller script and robust workflow transformed a stagnant homeowner database into a pipeline of ready-to-list clients, quadrupling appointments while slashing agent dialing time.
Key Takeaways
- Persistence at scale—AI can execute perfectly timed multi-touch cadences 24 / 7.
- Script precision—A market-tested script builds trust quickly and surfaces motivation.
- System integration—Seamless CRM and calendar sync drives agent adoption and data accuracy.
Long-Term Impact
- Estimated $3.4 M incremental gross commission income annually.
- Sustainable advantage in low-inventory conditions.
- Scalable model ready for expansion to new farming territories.