Use Case – Reaching Investors with AI Calls

The Challenge: The firm needed to initiate a high volume of calls to potential investors and present exclusive real estate investment opportunities, all while ensuring a professional, personal touch. Traditional cold calling is time-consuming, often yielding low success rates. In fact, research suggests that only about 0.3% of cold calls result in an appointment, with the vast majority of calls going unanswered or to voicemail​. The company wanted to outperform these benchmarks by using automation without sacrificing quality.

The Solution: Using Awaz.ai’s AI voice agent, the firm automated outbound calls to prospective investors. The AI agent would call investors, introduce the firm and a new investment opportunity, and engage the prospect in a brief conversation. If the prospect showed interest, the agent would seamlessly warm transfer the call to a human investment advisor for detailed follow-up. If the prospect wasn’t interested or had objections, the AI was trained to handle common objections and gracefully conclude the call or offer to call back later.

Key Objectives:

• Efficiently scale outreach to hundreds of potential investors in Dutch, the local language.
• Qualify interested investors through conversation before involving human agents.
• Reduce the time human sales reps spend on unanswered calls and voicemails, focusing their efforts on high-intent leads.

Automation Setup: How the AI Voice Agent Was Configured

Setting up the Awaz.ai voice agent was a structured process. The team created a custom calling campaign in Awaz.ai with specific configurations to meet their outreach goals:

1. Language – Dutch: The AI agent’s voice was configured to speak Dutch fluently, ensuring that potential investors felt comfortable and understood. All dialogues and scripts were created in Dutch to suit the local audience. Awaz.ai’s text-to-speech engine supports multi-language deployment without coding, so the team easily set the agent’s language to Dutch.
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2. Custom Script & Training: A tailored call script was developed to identify investor intent and handle objections. This script guided the AI through an introduction, opportunity pitch, and questions to gauge interest. The AI was trained with Awaz.ai’s Agent Builder to follow this script closely while allowing natural conversation flow. For example, if a prospect said, “I’m not sure I have time,” the AI was prepared with a polite, persuasive response to address the concern. The prompts were fine-tuned so the AI would stay on script, use a friendly professional tone, and not drop the conversation when facing objections.
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3. Logic Flow & Lead Qualification: The call flow included intelligent branching logic. The AI asked questions to qualify the lead’s interest and investment profile (e.g., “Are you interested in opportunities in commercial or residential real estate?”). Based on the responses, the AI applied a logic tree to decide next steps:
   • If the prospect expressed strong interest or positive intent, the call would progress toward connecting them with a human advisor.
   • If the prospect was unsure or had questions, the AI provided additional information or reassurance.
   • If the prospect clearly was not interested, the AI politely ended the call on good terms.
     This logical framework ensured that only qualified, interested prospects were escalated.
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4. Warm Transfer to Human Expert: Upon detecting a genuinely interested investor, the AI agent would initiate a warm transfer – effectively placing the prospect on hold and dialing a pre-set number of a live investment expert at the firm to take over the conversation. The transfer was done seamlessly so that the prospect could immediately continue the discussion with a human without needing to repeat information. This step dramatically improved the handoff quality compared to a simple “we will have someone call you back” approach. (Awaz.ai’s system is designed for such smooth handoffs in real-time.)
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5. Voicemail Detection & Retry Rules: Not every call reached a live person on the first try. The AI was configured to automatically detect voicemails. If it hit a voicemail, the agent would:
   • Leave a brief, tailored voicemail in Dutch introducing the opportunity and providing a callback number.
   • Log the call outcome as voicemail and schedule a callback attempt according to pre-set retry rules. For example, it would try calling back at a different time of day or the next business day. This helped increase the chance of eventually connecting, as multiple touchpoints are often needed (industry data shows 80% of cold calls go to voicemail​, so intelligent re-dialing is crucial).
   • Ensure no prospect was overwhelmed – the retry logic capped the number of attempts (e.g., 3 attempts per contact at different times) to avoid annoyance.
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6. CRM Integration & Automatic Logging: A critical part of the setup was integrating Awaz.ai with the firm’s CRM system (HubSpot) for seamless data syncing.
   
   Using Awaz.ai’s integration capabilities, the AI agent was connected to the CRM via a webhook (through Zapier). This meant that every call result was automatically recorded:
   • If a call resulted in a warm transfer and a successful connection to a human agent, the CRM lead status was updated (e.g., marked as “Engaged – Warm Lead”) and a task for follow-up was created.
   • High-intent leads were flagged for the sales team. For instance, the AI could tag contacts who responded with explicit interest or requested more info, ensuring the sales team prioritized these for personal follow-up.
     This integration eliminated manual data entry. One of the advantages of Awaz.ai is that it automatically logs call outcomes and conversation details into CRM systems​.
   • Call outcomes (interested, not interested, voicemail left, etc.) were logged under each contact’s profile in the CRM immediately after the call​

By following this setup, the company essentially had a virtual sales caller working through their investor list methodically,  24/7 if needed, without fatigue. Human agents became involved only when a prospect was ready to engage, making very efficient use of the team’s time.

Tool Stack and Integration Details

Implementing this AI-driven calling campaign required coordination of several tools, seamlessly integrated:

• Awaz.ai Voice Agent Platform: The core engine powering the AI calls. This no-code platform handled the call dialing, speech recognition, and conversation flow logic. Awaz.ai’s system made it easy to create the agent and define its behavior using an intuitive interface (no programming needed).
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• Telephony Service: Awaz.ai connects with telephony providers under the hood to place calls. In this case, the calls were made over VoIP with local Dutch phone numbers to maximize answer rates. The AI could dial multiple contacts in parallel and use features like local presence dialing to improve pickup rates.
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• CRM (HubSpot): The firm’s CRM was integrated so that contacts (potential investors) and call outcomes sync automatically. As noted, Awaz.ai can connect to CRMs like HubSpot or Salesforce via Zapier or direct API integration​ In this deployment:
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  • The contact list of investors was imported from the CRM into Awaz.ai as call targets.
  • After each call, Awaz.ai pushed the result (pickup, voicemail, interested lead, etc.) back to the CRM.
  • Lead Routing: If the AI flagged a contact as high-intent (for example, someone who said “yes, I’d like to know more”), the CRM would automatically assign that contact to a senior investment advisor and put them in a high-priority call queue for human follow-up.
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• Workflow Automation (Zapier): The team used Zapier to glue the systems together. For example, a Zap was set such that whenever Awaz.ai finished a call and labeled it as a “positive conversation,” Zapier would update the CRM and also notify the sales team on Slack. This ensured no hot lead ever fell through the cracks. The integration allowed real-time data sync – as soon as the AI call was done, everyone had up-to-date information.
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• Analytics Dashboard: Awaz.ai provided a dashboard tracking key metrics like call completion rates, conversation durations, and conversion rates. The company monitored this to refine their approach (for instance, tweaking call scripts or call times). Because the data was automatically logged, they could easily analyze how the AI agent was performing versus expectations.

This tech stack enabled a smooth, end-to-end solution: from dialing a prospect to logging an interested lead in CRM without human intervention in between. The AI voice agent effectively became an extension of the sales team, operating at a much larger scale.

Results and Performance Metrics

The AI-driven campaign yielded impressive results, far outpacing typical cold calling benchmarks. Over the course of the campaign, the following metrics were recorded:

Key calling campaign outcomes recorded by the Awaz.ai voice agent.

• Total Dials: 1,828 – The AI agent made 1,828 call attempts to potential investors. This high volume was handled effortlessly by the AI over a short span, something that would have taken a human team significantly longer. (For context, an average human sales rep might make 40-50 calls a day, so 1,828 dials could equal weeks of work for one person. The AI handled it in a fraction of that time.)
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• Pickups (Connections): 1,090 – Out of those dials, 1,090 calls were actually answered by a person. This is a remarkably high connection rate of about 60%. In traditional cold calling, reaching even 20-30% pickup is challenging due to voicemails and call screening​.
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• The high pickup rate here can be attributed to the timing and retry strategy and possibly using local numbers – tactics that improved the odds of prospects answering the phone. Essentially, the AI agent’s persistence and smart timing paid off in getting more people on the line.
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• Voicemails Left: 383 – Approximately 21% of calls went to voicemail (383 cases). In each of these, the AI left a tailored voicemail. These voicemails provided a call-back number and brief information about the opportunity. While industry stats show about 80% of cold calls often end in voicemail​, the campaign’s rate was much lower due to its multi-attempt logic. Still, each voicemail was treated as another touchpoint – some prospects did call back after hearing the message, effectively turning voicemails into leads.
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• Failed/Busy Calls: 150 failed, 62 busy – A number of calls (around 8% combined) failed to connect due to technical reasons or encountered a busy line. The system automatically retried these after a short interval. Busy signals were re-dialed according to the rules set, often successfully connecting on a later attempt. Failed calls (e.g., disconnected numbers) were logged and removed from the rotation.
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• No Answer (missed): 120 – These were calls that rang but were not answered and did not go to a voicemail (for example, ringing until timed out). The AI treated them similar to voicemails by rescheduling them for later attempts. By having 120 such “no answer” instances, the AI again showed diligence in follow-ups, ensuring multiple call attempts to maximize engagement.
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• Positive Conversations (Results): 23 – 23 calls led to positive investment conversations, meaning the prospect engaged in a meaningful dialogue about the investment opportunity and was interested in learning more. In most of these 23 cases, the AI successfully live-transferred the call to a human investment advisor, or scheduled a follow-up meeting. This figure — 23 warm leads — is where the true business value lies. While 23 might seem modest out of over a thousand connections, in cold calling terms this is a strong outcome. The conversion rate here is roughly 1.26% of total dials resulting in an engaged lead. Compare this to typical cold call campaigns where conversion to a meaningful result is often below 1%. In other words, the AI campaign performed 4x better than the 0.3% appointment rate found in Baylor University’s study on cold calling. It even surpassed many industry averages (commonly ~1% to 2% conversion) for cold calls, demonstrating how effective the AI agent was at not only connecting calls, but converting them into real opportunities.
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• Total Spend: $275.15 – This was the cost incurred for using the Awaz.ai voice agent and telephony minutes for the entire campaign. Breaking it down, the spend included the voice AI service usage and call charges (Awaz.ai’s pricing model and telephony fees). Automating calls proved extremely cost-effective. With $275 spent to reach out to 1,828 contacts, the average cost per dial was about $0.15. A traditional approach would have required paying staff for call hours; by automating, the firm dramatically reduced labor costs.

• Cost per Result: $11.96 – Perhaps the most telling metric for the business: on average, it cost under $12 to generate one positive investor conversation. This cost-per-acquisition is impressively low for the real estate investment industry, where leads can be expensive. For example, real estate leads via online ads often cost $20-$100+ each, depending on the channel. Here, each interested investor lead was acquired for a fraction of that cost. AI voice automation slashed the cost per lead while maintaining quality. It’s also far cheaper than hosting seminars or events to attract investors (which can cost thousands for a handful of prospects). The firm effectively got 23 high-quality investor engagements for just ~$12 each, which is a tremendous ROI given the potential deal size in real estate investments.

Performance Analysis: The campaign’s success can be attributed to the synergy of technology and strategy:

• High Efficiency: The AI dialer reached a large volume of contacts quickly. There was no downtime – calls were made back-to-back, and voicemails were handled instantly. Humans would require breaks and have off-hours, but the AI could even make calls in early evenings when investors were more likely free, thus boosting pickup rates.
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• Effective Script & Qualification: The carefully crafted script meant that when someone did pick up, the conversation was relevant and compelling. The AI quickly identified if the person had interest. Those not interested were politely filtered out, saving the company’s sales team time. The 23 results indicate that the script successfully hooked the right prospects.
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• Better than Average Conversion: Achieving over 1% conversion of cold calls to engaged leads is significant. Many companies see <1% conversion from cold outreach​. By comparison, this firm’s campaign – with ~1.26% conversion – outperformed common benchmarks. It suggests that AI can match or exceed human-led call outcomes, likely because the AI never forgets to follow the playbook, responds consistently to objections, and ensures every potential opportunity is pursued (multiple call attempts, etc.).

• Low Cost, High Output: The cost per result being only $11.96 is a breakthrough. Considering the lifetime value of a potential investor or the size of an investment they might make, spending $12 to get that opportunity is almost negligible. This hints at a future where AI voice agents can massively reduce customer acquisition costs in industries like real estate. Other companies report that AI call agents can be “80% cheaper than call centers with 20x the output”, and this case aligns with that trend – more output for less cost.

Business Insights and Impact

This success story illustrates several key insights for businesses considering AI voice automation:

• Scalability and Time Savings: By using an AI voice agent, the firm was able to scale their outreach without scaling their team. Reaching nearly two thousand contacts would normally require a team of callers or many days of work; Awaz.ai achieved it swiftly. This freed the human sales experts to focus on closing deals rather than dialing numbers.
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• Enhanced Lead Qualification: The AI served as a first-pass filter, ensuring that human agents spent time only with qualified, interested investors. The built-in logic flow asked the right questions to gauge interest. Automated qualification means your sales pipeline is filled with quality leads, not just any leads. This improves overall sales efficiency and morale (salespeople talk to more warm prospects and fewer dead-ends).
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• Consistent Investor Experience: Every potential investor received a consistent, professional introduction to the company and its offer. The AI agent never had an “off day” – it delivered the pitch perfectly each time, in a friendly tone matching the company’s brand. This consistency in messaging can strengthen brand perception. Prospects likely couldn’t tell the caller was an AI in many cases, since Awaz.ai’s agents are very human-like in speech. (Awaz.ai notes that 95% of users can’t distinguish their AI from a real person in conversation.)
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• Multilingual Outreach: The ability to converse in Dutch was crucial. Awaz.ai’s support for Dutch voice ensured the local investors felt comfortable. For a global investor base, the same approach could be replicated in other languages seamlessly. This opens doors for the firm to use the AI agent for international campaigns, speaking to investors in their native languages just as effectively.
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• Data-Driven Optimization: Because every call and outcome was logged, the firm gained rich data on their outreach. They could see what times of day had the best pickup rates, analyze voicemail response rates, and even review transcripts of the AI conversations to find patterns in objections. This data is a goldmine for continuously improving sales tactics. It goes beyond what a human team might record (since AI logs everything meticulously).
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• Reduced Cost per Acquisition: Perhaps the most tangible business impact is the reduction in cost per investor acquisition. At ~$12 per engaged lead, the firm drastically reduced what they would normally spend to get a similar lead through other marketing channels or through a manual calling approach. Lower cost per acquisition means a higher return on marketing investment and allows the firm to allocate budget to other strategic areas (or simply achieve better margins on their campaigns).
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• Outperforming Traditional Benchmarks: The success of this campaign shows that AI voice agents can not only match traditional cold calling performance but exceed it. By automating the process, the firm achieved conversion rates on the higher end of industry averages, proving that skepticism around AI cold calling can be overcome with the right execution. As one sales study noted, even getting 1-2% conversion is typical; this campaign hitting above 1% in engaged leads is a strong validation of AI-driven calls in a B2B context (high-value investments).

Conclusion: Transforming Investor Outreach with AI

For this Amsterdam-based real estate investment company, Awaz.ai’s AI voice agent has transformed the way they engage with potential investors. The campaign demonstrated that AI-driven outreach can successfully initiate conversations that lead to real business opportunities, all while saving time and money. The voice agent acted as a tireless junior sales caller, enabling the firm’s human team to focus on closing the 23 interested investors it identified.

In a broader sense, this case study highlights how AI voice automation can streamline investor outreach and sales prospecting:

• Businesses can maintain a human touch at scale – using AI to personalize calls and then hand off interested parties to real people at the perfect moment.
• Operationally, companies benefit from faster lead generation, better resource allocation, and insightful analytics.
• Financially, lower costs per acquisition mean higher ROI and the ability to reinvest savings into growth.

The success the Dutch real estate firm experienced with Awaz.ai’s voice agent is a compelling proof-point for the power of conversational AI in sales. Cold calling isn’t dead – it’s evolving. By embracing AI voice agents, businesses in real estate and beyond can rejuvenate their cold calling efforts, turning them into smart, automated campaigns that outperform traditional methods.

In summary, Awaz.ai’s AI voice agent helped an innovative real estate investment company achieve what every business strives for: more results in less time, at a lower cost, with a great customer experience. This sets a new benchmark for investor outreach efficiency in the industry.