Exec Creates 80% of New Deals with AI-Powered Outreach

Exec, a cutting-edge executive training platform, recently shared how they are leveraging AI-powered workflows to drive an impressive 80% of their new deals. By automating personalized outreach and scaling their sales efforts, Exec has achieved a remarkable 17% conversion rate from email to first meeting booked. Check out the full webinar recording here.

Quick Recap of Key Takeaways

• Exec uses AI workflows to automate personalized outreach at scale
• They've increased personalized outbound by 3x while reducing manual effort by 90%
• 80% of Exec's new deals are now driven by AI-powered outreach
• Exec achieves a 17% conversion rate from email to first meeting booked
• Modular workflow design and leveraging external data sources are key to success

The Challenge Faced

As a bootstrapped talent development agency, Exec initially relied heavily on manual, network-driven outreach to sell their professional services. This approach required significant effort from their small team, as crafting personalized emails for each prospect was time-consuming. When attempting to scale by using generic templates, the results were lackluster, failing to generate the desired meeting bookings and deal flow.

The Results Achieved

By implementing AI-powered workflows with AirOps, Exec has:

• Increased personalized outbound by 3x
• Reduced manual effort by 90%
• Driven 80% of new deals through AI-powered outreach
• Achieved a 17% conversion rate from email to first meeting booked

Workflow Deep Dive

Personalized Outreach at Scale

Exec's AI-driven outreach workflow begins by segmenting prospects into sales and non-sales roles using a simple classification step. This allows them to tailor messaging for each persona.

For non-sales prospects, the workflow scrapes relevant Glassdoor reviews to identify pain points around management, feedback, and culture. An LLM then extracts structured data from the reviews to populate personalized email templates.

Key tips:

• Chunk workflows into modular sub-workflows for easier management
• Provide structured context to LLMs using XML tags for better output

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Best Practices and Key Learnings

Start Small and Iterate

Don't try to build a complex workflow all at once. Begin with a simple version that works, then gradually add complexity and functionality. This iterative approach allows you to test and refine each component of the workflow.

Decompose Workflows into Modular Steps

Break your workflows down into smaller, reusable sub-workflows. This makes the overall workflow easier to understand, maintain, and adapt for new use cases. Exec's Glassdoor scraping sub-workflow, for example, could be repurposed for content generation.

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Google Hacking

• Master Advanced Search Operators to Refine Results:‍
  • Use operators like site:, inurl:, and intitle: to narrow down your search to specific domains or page titles. For example, site:glassdoor.com [company name] reviews will fetch reviews for a company exclusively from Glassdoor.

• Combine Operators for Precise Information Retrieval:‍
  • Chain multiple search operators to hone in on the exact data you need. For instance, using site:example.com inurl:blog "keyword" will search within a site's blog pages containing a specific keyword.

• Use Exclusions to Filter Out Irrelevant Results:‍
  • Apply the minus sign - to exclude certain terms or sites from your search. For example, "[topic]" -site:wikipedia.org will show results about your topic excluding Wikipedia pages.

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Leverage External Data Sources

Identify relevant external data sources that can provide valuable context for personalization. Exec uses Glassdoor reviews to tailor their outreach, but other sources like G2 reviews, LinkedIn data, or Twitter feeds could be used depending on your industry and use case.

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Maintain Human Oversight

While AI can automate much of the outreach process, human oversight is still important for quality control. Review outputs and make adjustments to workflows as needed to ensure the best results.

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Experiment with Prompt Engineering

Effective prompt engineering is crucial for high-quality LLM outputs but developing great prompts is an iterative process. Start with a simple prompt and incrementally add complexity based on the output quality.

Exec uses tools like Anthropic's prompt engineering generator for a strong starting point, then refines the prompts by providing additional context and examples. This results in highly personalized, engaging outreach emails.

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Putting the Insights into Practice

Sean's success story demonstrates the power of AI-driven workflows for scaling personalized outreach and driving growth. By starting small, iterating on your workflows, and leveraging external data sources, you can create highly effective AI-powered processes tailored to your unique challenges.

To help you implement these strategies, AirOps is offering exclusive training opportunities for a limited number of attendees. Don't miss this chance to work with AirOps experts to craft workflows that will take your growth to the next level. Book time with a Growth Expert today!

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