Case Study Breakdown: AI Content System for Home Service Business
Overview
- Presentation on how AI content system was used to significantly reduce costs for a landscape construction business in LA.
- Key metrics before and after using AI:
- Cost per Lead: Reduced from $50 to $15
- Cost per Booked Call: Reduced from $150 to $30
Importance of Short-form Content
- Short-form content offers a large arbitrage opportunity.
- Creating engaging content can lead to viral distribution without ad spend.
- AI system developed to help clients acquire the skill to create viral content and effective ads.
Application and Success
- AI faceless content and ads used to scale construction businesses.
- Businesses involved are significant in size, making millions annually.
- The strategy is being deployed across various verticals.
Ian's Experience
- Ian runs a digital marketing agency focused on home service contractors.
- Prior methods included Facebook ads and static creatives which were less effective.
- After engaging with the AI system, the cost per lead and appointment significantly reduced.
- The new method involves:
- Placement of a content editor skilled in faceless content.
- Use of viral videos and engaging captions.
Strategic Positioning and Sales
- The AI content approach is marketed as a novel opportunity rather than just an improvement.
- Ian's agency charges $5K and takes a 5% revenue share, with plans to increase charges due to the high value provided.
- The importance of constant testing and having the right editor is highlighted.
Additional Insights
- Building organic pages and leveraging AI content for viral potential are advised.
- Discussion on selling attention, similar to Facebook and Google:
- Build an audience using viral AI content.
- Utilize retargeting ads to sell services or attention.
Conclusion
- AI-driven content and ads offer a scalable and effective solution for acquiring leads at a reduced cost.
- Emphasis on leveraging attention acquisition as a business model.
Note: Engagement in a masterclass is suggested for further learning and application of AI-enabled growth infrastructures.