Don't Sell N8N Workflows, Sell AI Infrastructure - Here's How (Massive Opportunity)

Summary

In this video, the speaker advises against focusing on single-use case AI systems and instead recommends building comprehensive AI applications and infrastructure. Drawing from personal experience, they highlight the importance of delivering results and user experience over flashy AI features. The speaker emphasizes targeting businesses that understand the value of scalable AI solutions, offering customized dashboards, and using tools like Python and no-code platforms. By focusing on delivering tangible outcomes and building a white-glove experience, AI system providers can significantly increase the value they offer to clients, ultimately commanding higher fees for their services.

Takeaways

• 😀 Focus on building comprehensive AI applications and infrastructure instead of single-use case AI automations or agents.
• 😀 Clients care more about the results, outcomes, and user experience rather than the technical details of AI systems.
• 😀 Packaging AI systems effectively can allow you to sell them at a much higher price point than typical automation systems.
• 😀 A custom dashboard and user experience for clients are key to delivering value and ensuring satisfaction.
• 😀 Small businesses with fewer than 25 employees are unlikely to have the budget for complex AI systems, so target mid-sized businesses instead.
• 😀 A system that shows clear insights and results, such as a lead generation dashboard, is more likely to justify a higher price tag.
• 😀 Businesses willing to spend on AI systems should have at least $100K in monthly recurring revenue to be viable clients.
• 😀 The goal is to scale AI systems with custom dashboards and back-end code to create an efficient and repeatable process for clients.
• 😀 Demonstrating a proven system with results from previous clients is more effective than just promising results.
• 😀 Developing a white-glove experience with front-end tools and back-end systems can help justify higher monthly service fees.
• 😀 Testing systems on a few clients and collecting testimonials and proof of success can help attract more clients and build credibility.

Q & A

Why should I avoid single-use case AI automations and agents when building AI systems for businesses?

Single-use case AI automations and agents are often not scalable and fail to provide long-term value. Clients are more interested in comprehensive solutions that deliver measurable results. Instead of focusing on simple workflows, it's better to build entire AI applications and infrastructure that cater to the broader needs of the business.

How does packaging AI systems differently affect their sale price?

By packaging AI systems with a focus on user experience and clear results, you can sell them for much higher prices. Instead of just offering a technical solution, providing clients with dashboards and visible outcomes can justify a higher price point because they understand the value of the service being provided.

What is the importance of providing a 'white glove' customer experience in AI system sales?

A 'white glove' customer experience involves offering clients a hands-on, personalized service where they can directly see the results of the AI system. This builds trust, improves client satisfaction, and makes them more willing to pay premium prices because they feel more involved and confident in the solution's effectiveness.

How does the choice of target businesses influence the success of AI system sales?

Targeting medium-sized businesses that have stable recurring revenue is key to success. These businesses have the resources to invest in custom AI systems and are less risk-averse. Small businesses with fewer than 25 employees typically lack the funds for such investments and are harder to work with.

What are some practical ways to structure a lead generation system for clients?

A practical lead generation system involves automating campaigns that track and display key metrics like outreach, email opens, responses, warm leads, and booked meetings. By offering clients a dashboard that visualizes these results, they can better understand the ROI and justify a higher price for the service.

Why is it beneficial to build custom dashboards for clients instead of just using generic tools?

Custom dashboards tailored to each client’s needs enhance their experience by providing clear, actionable insights. These dashboards allow clients to track key performance indicators (KPIs) in real-time, which increases their satisfaction and willingness to pay for the service.

How can AI systems be packaged for high-ticket pricing?

AI systems can be packaged for high-ticket pricing by focusing on delivering a comprehensive, personalized service. This includes building custom user interfaces, integrating various backend solutions, and providing clients with a dashboard that allows them to see the direct results and impact of the AI system.

What role does backend code and front-end user interfaces play in selling AI systems?

Backend code handles the underlying functionality, while front-end user interfaces (built with tools like Lovable or Cursor) make the system more user-friendly and accessible to clients. This combination allows businesses to scale AI systems while also providing a smooth and engaging client experience.

What is the strategy for getting medium-sized businesses to pay for expensive AI systems?

The strategy involves demonstrating how the AI system can scale their business and produce tangible results. By showing them how the system can help increase sales and revenue, such as generating qualified sales calls, businesses will be more inclined to invest in the system, especially if they can track the outcomes through custom dashboards.

Why is it essential to test AI systems with multiple clients before scaling them?

Testing AI systems with multiple clients helps identify which systems are scalable and effective across different business contexts. Successful case studies provide valuable proof of concept that can be used to convince other businesses of the system’s potential. It also allows for rapid iteration and improvement of the system.