AI-Powered Outbound Prospecting & Lead Enrichment

CUSTOMER

A U.S.-based security training and learning management company serving security guard companies and organizations with in-house security teams.

The company wanted to expand B2B sales outreach by identifying organizations that employ their own security personnel and connecting with the people responsible for security operations, training, and compliance.

CHALLENGE

The company had already developed a strong prospecting strategy based on job-board activity. By monitoring platforms such as Indeed, the team identified organizations hiring security personnel directly, which provided a strong buying signal for security training services.

However, several operational challenges limited the scalability of this approach:

• Company data was available, but contact information such as direct phone numbers was incomplete.
• Job-board titles were sometimes misleading, making it difficult to identify the correct security decision-maker.
• The same company could appear across multiple job boards, creating duplicate records.
• Companies with similar names created a risk of matching contacts to the wrong organization.
• Manual enrichment and calling required significant sales-team effort.
• Traditional outbound calling produced limited conversations relative to the number of calls made.
• Call transcripts and outcomes needed to become part of the company’s existing HubSpot data.
• The sales team needed a consistent way to identify interested prospects and prioritize follow-up.
• The company wanted to test AI calling without losing visibility into the conversations and outcomes.

The objective was to build an automated outbound engine capable of sourcing contact information, initiating personalized conversations, qualifying prospects, and passing actionable opportunities to the sales team.

COGNIC’S SOLUTION

Cognic designed an AI-powered outbound prospecting workflow combining lead enrichment, automated calling, CRM integration, and human follow-up.

1. Target Company Identification

The process begins with a list of target companies provided by the client. The primary targeting signal is hiring activity for in-house security personnel. The workflow focuses on organizations such as companies hiring security personnel directly, organizations with internal security departments, security companies, and selected industries with a strong likelihood of maintaining in-house security teams. Job-board information is used to identify relevant companies and hiring signals.

2. Automated Lead Enrichment

The target company list is maintained in Google Sheets. The Cognic automation checks new records and sends company information to the enrichment workflow. Clay is used as the primary enrichment platform because of its multi-source contact coverage. The enrichment process searches for: contact name, job title, business phone number, business email, company information, and professional profile information. LinkedIn Sales Navigator is used as an additional source for role and profile verification. The system filters contacts based on the client’s target roles to reduce irrelevant calls.

3. Automated Data Preparation

Once enrichment is completed, the record is updated in Google Sheets. Records move through defined statuses such as: New → Enriching → Ready to Call → Calling → Call Completed. The system also tracks call attempt count, last call date, call outcome, next follow-up date, contact information, and notes. This creates a controlled calling queue for the AI agent.

4. AI-Powered Outbound Calling

Retell AI is used to execute outbound calls. The AI agent uses available prospect information to personalize each conversation, including contact name, company name, job title, industry, and hiring context. Rather than starting with an aggressive sales pitch, the initial conversation follows an exploratory approach. The AI first validates the prospect’s role and security setup, then determines whether the organization manages security personnel internally and whether training is relevant.

5. Conversational Qualification

The AI agent follows an approved conversation flow and identifies outcomes such as: Interested, Qualified, Callback requested, Not interested, No answer, Call failed, and Invalid number. The system records the number of calling attempts for each prospect. This provides visibility into how many times a prospect has been contacted and prevents uncontrolled repeated calling.

6. HubSpot Integration

Qualified and positive conversations are pushed into HubSpot. The system records relevant information such as: contact information, company information, call outcome, call summary, transcript, recording reference, number of attempts, and follow-up requirements. HubSpot becomes the central location for sales follow-up and conversation history. The existing HubSpot environment also allows downstream conversation intelligence through the client’s existing Learno setup.

7. Real-Time Lead Notification

When the AI identifies a positive or qualified prospect, the system triggers an internal notification. The sales team receives the lead details along with the relevant call information. The notification includes information such as: prospect, company, job title, call outcome, qualification details, recommended next action, and call recording and transcript reference. This allows the sales team to focus on prospects showing buying intent instead of manually reviewing every outbound attempt.

8. Continuous Optimization

The project includes an iterative optimization process. Call outcomes, transcripts, objections, and successful conversation patterns are reviewed to improve: opening statements, qualification questions, objection handling, target job titles, industry targeting, calling strategy, and follow-up approach. Weekly reviews provide a structured feedback loop between the client and implementation team.

BUSINESS BENEFITS

• Automated Lead Generation: The workflow reduces manual work involved in finding contact information and preparing prospects for outbound calling.
• Better Contact Targeting: Multi-source enrichment and role validation improve the likelihood of reaching relevant security decision-makers.
• Scalable Outbound Calling: AI handles repetitive outbound conversations, allowing the sales team to focus on qualified prospects and follow-up.
• Personalized Conversations: The AI uses company and contact information to create context-aware conversations instead of generic calling scripts.
• Centralized Sales Intelligence: Call outcomes, transcripts, recordings, and lead information flow into HubSpot for centralized sales visibility.
• Reduced Manual Data Entry: Google Sheets, enrichment tools, AI calling, and HubSpot are connected through automation, reducing repetitive CRM updates.
• Controlled Follow-Up: The system tracks calling attempts and outcomes, helping prevent excessive contact attempts and ensuring prospects follow the defined disposition rules.
• Continuous Improvement: Call data provides feedback for refining scripts, targeting criteria, and qualification logic over time.
• Improved Sales Team Productivity: Sales representatives receive qualified or interested prospects instead of spending the majority of their time on initial prospecting and repetitive outreach.

TECHNOLOGY USED

• Retell AI, AI-powered outbound voice agent
• Clay, B2B contact enrichment
• HubSpot, CRM and sales activity management
• Google Sheets, lead staging and workflow queue
• LinkedIn Sales Navigator, contact and role verification
• Job boards, prospect and hiring-signal identification
• Custom automation and API integrations
• Learno, conversation intelligence through HubSpot