Chris Pasquier, CEO of Slite and Super, dives into the challenges of selling AI products, specifically why free trials are often ineffective. He discusses the evolution of Slite as a documentation platform and introduces Super, which optimizes workplace efficiency. The conversation highlights strategies for effective customer onboarding, the importance of clear use cases, and overcoming skepticism in AI adoption. Pasquier also explores future trends in AI within business, emphasizing the need for companies to adapt to shifting buyer behaviors.
Free trials are ineffective for AI products because their implementation requires tailored support and proper data setup, unlike traditional SaaS solutions.
Effective onboarding is crucial for AI adoption, as it involves extensive collaboration to demonstrate how the technology can specifically address client challenges.
Deep dives
Challenges of Free Trials for AI Products
Free trials are not effective for AI products due to their complexity and the extensive preparation needed for implementation. AI requires quality data, which varies across organizations, making generic trials insufficient for demonstrating value. Businesses are often willing to invest in AI despite recognizing that the technology is still evolving and may not deliver immediate results. This necessitates a tailored approach, wherein companies must spend significant time helping clients set up their data and systems properly to realize the benefits of AI solutions.
The Role of Customer Onboarding
Onboarding for AI solutions involves extensive interaction between the service provider and the customer to ensure proper setup and understanding. This process helps clients realize how AI can address their specific challenges, providing them with clear demonstrations of its value. For example, by analyzing a week's worth of Slack conversations, an AI tool can highlight key topics, showcasing its immediate usefulness. Achieving this requires ongoing communication and support, often taking weeks for teams to fully acclimate to the new technology.
The Necessity for Customized Solutions
Unlike traditional SaaS products, AI tools require careful adaptation to individual organizations' data environments, which makes consulting work vital. Customers must build specific use cases to harness AI's capabilities effectively, which involves modifying their existing practices. The insights gained from detailed evaluations guide the development of tailored solutions, demonstrating how AI can streamline processes and enhance productivity. This collaborative work ensures that the technology aligns with customer needs, making adoption smoother.
Navigating Changes in Buying Behavior
Decision-makers in organizations are increasingly skeptical about new AI tools, often stemming from concerns about data integration and the effectiveness of the technology. They seek concrete proof of how AI can work with their existing data, requiring vendors to demonstrate clear ROI. This transition necessitates vendors to establish structured onboarding processes that showcase the technology's practical applications and benefits, ultimately driving habit changes within teams. As organizations recognize the potential of AI, they become more open to investing, provided vendors can navigate their hesitations effectively.
Free trials don't work for AI products - so... what do you do?
That's what we asked Chris, CEO and founder of Slite.
(00:00) - Introduction
(03:36) - Challenges in Selling AI
(04:53) - Introduction to Slite and Super
(06:31) - AI Implementation and Use Cases
(08:50) - Customer Onboarding and Trials
(10:15) - Why can't we just do freemium
(13:10) - Overcoming AI Adoption Barriers
(22:15) - Future of AI in Business
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