Brian Schiff: AI is revolutionizing customer support, automation can reduce call volumes by 90%, and pricing models are evolving for accessibility | SaaS Interviews

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Key takeaways

AI is revolutionizing customer support, becoming a key technology in modern business environments.
Automation in customer service can significantly reduce call volumes, particularly in industries like transportation.
Deep integration and handling edge cases are crucial for successful enterprise software development.
Offering software without upfront costs can make advanced technologies accessible to companies of all sizes.
The pricing model for AI services ranges significantly, reflecting the complexity and scale of customer needs.
Automating 300 million phone calls demonstrates the significant impact and scalability of AI technologies.
The acceptance of AI in automating conversations is becoming widespread and is seen as inevitable.
Companies must develop a strategy for AI to remain competitive in customer experience.
B2B applications should leverage the latest technology to deliver measurable value to customers.
AI technologies are better suited for large consumer businesses with high contact volumes.
The shift in perception towards AI automation indicates a strong trend that could influence future business strategies.
Understanding pricing models and customer profiles is essential for navigating the competitive landscape in enterprise software.
The necessity for businesses to engage with AI reflects the growing importance of technology in customer interactions.
Strategic decision-making is crucial in determining the applicability of technologies in specific market segments.

Guest intro

Brian Schiff is the co-founder and CEO of Flip, a verticalized AI voice assistant that automates customer service calls for over 250 brands in transportation, retail, and healthcare, recently reaching $12M ARR. He pivoted the company’s original Cornell ridesharing app—banned on campus—into voice AI after recognizing its dead end, now handling 300 million calls and raising a $20M Series A at a $100M valuation.

AI’s transformative role in customer support

AI is a transformative technology with significant applications in customer support.

— Brian Schiff
The current landscape of AI applications in business highlights two major use cases: AI coding and AI customer support.
AI’s role in customer support is part of a broader trend towards automation in business environments.
I think when people write AI is the technology of our lifetimes…

— Brian Schiff
The importance of AI in modern business is underscored by its potential to enhance efficiency and customer satisfaction.
Companies are increasingly focusing on AI to streamline operations and improve customer interactions.
The transformative potential of AI is evident in its ability to automate routine tasks and free up human resources.
AI’s impact on customer support is part of a larger shift towards digital transformation in various industries.

Automation in the transportation industry

We automate somewhere between eighty five and ninety percent of the calls that transportation companies receive.

— Brian Schiff
Automation significantly reduces call volumes, allowing companies to focus on more complex customer needs.
The scalability of automation in transportation demonstrates its effectiveness in handling high volumes of routine inquiries.
We’re able to automate all of those routine calls…

— Brian Schiff
Automation helps transportation companies stay at the cutting edge by improving efficiency and customer service.
The success of automation in transportation highlights the potential for similar applications in other industries.
Understanding the scale of automation is crucial for appreciating its impact on customer service.
Automation in transportation is part of a broader trend towards leveraging technology to enhance operational efficiency.

Challenges in enterprise software development

Building enterprise software with deep integrations and handling edge cases is extremely complex.

— Brian Schiff
Successful enterprise software development requires experience in managing integrations and anticipating issues.
Deep integration is essential for providing seamless customer experiences and addressing potential challenges.
It’s one thing to have enough of an integration with Shopify…

— Brian Schiff
Handling edge cases is a critical component of enterprise software development, ensuring reliability and performance.
The complexity of enterprise software development underscores the importance of expertise and experience.
Integrating various software systems poses significant challenges, requiring careful planning and execution.
Anticipating and navigating issues is crucial for delivering effective enterprise software solutions.

Accessibility and pricing models in AI solutions

Their software can be implemented without upfront costs, making it accessible for companies of all sizes.

— Brian Schiff
Offering no-cost setup and integration makes advanced AI solutions more accessible to a wider range of companies.
The accessibility of AI solutions can disrupt traditional pricing models in enterprise software.
One of the beauties is this works for companies of all size…

— Brian Schiff
The competitive landscape in enterprise software is influenced by pricing models and accessibility.
Making AI solutions accessible to smaller companies can drive innovation and adoption across industries.
Understanding pricing models is essential for navigating the competitive landscape in enterprise software.
The accessibility of AI solutions reflects a broader trend towards democratizing technology.

Revenue models and customer profiles

The average customer pays between $50,000 to $500,000 per year for our services.

— Brian Schiff
The pricing model for AI services reflects the complexity and scale of customer needs.
Understanding customer profiles is crucial for tailoring AI solutions to specific business requirements.
It’s usually somewhere between 50 500,000…

— Brian Schiff
The revenue model highlights the target customer base for AI services, focusing on established companies.
The pricing model underscores the value and impact of AI solutions in addressing complex business challenges.
The diversity in customer profiles reflects the adaptability and scalability of AI solutions.
Understanding the revenue model is essential for appreciating the business potential of AI technologies.

Scale and impact of automation

We have automated 300,000,000 phone calls to date.

— Brian Schiff
Automating 300 million phone calls demonstrates the significant impact and scalability of AI technologies.
The scale of automation achieved by the company highlights its technological capabilities and industry significance.
We just announced our $20,000,000 series a…

— Brian Schiff
The company’s operational scale reflects its ability to handle large volumes of customer interactions.
The impact of automation is evident in its ability to streamline operations and enhance customer service.
The scale of automation underscores the transformative potential of AI technologies in various industries.
Understanding the scale of automation is crucial for appreciating its impact on customer service and business operations.

Imminent acceptance of AI in customer service

The widespread acceptance of AI for automating conversations is imminent and inevitable.

— Brian Schiff
The acceptance of AI in customer service reflects a significant shift in industry perception towards automation.
The inevitability of AI adoption highlights its growing importance in business strategies and operations.
I think that the world has realized…

— Brian Schiff
The shift in perception towards AI automation indicates a strong trend that could influence future business strategies.
The acceptance of AI is driven by its potential to enhance efficiency and customer satisfaction.
Understanding the current landscape of AI adoption is crucial for anticipating future trends and opportunities.
The acceptance of AI in customer service is part of a broader trend towards digital transformation in various industries.

The necessity of AI strategies for businesses

Every company and customer experience leader needs to have a strategy for AI.

— Brian Schiff
Developing a strategy for AI is essential for companies to remain competitive in customer experience.
The necessity for AI strategies reflects the growing importance of technology in customer interactions.
Every company every cx leader out there needs to have an answer…

— Brian Schiff
Companies must engage with AI to stay relevant and effective in a rapidly evolving business landscape.
The urgency for AI strategies underscores the transformative potential of technology in customer service.
Understanding the competitive landscape in customer experience is crucial for developing effective AI strategies.
The necessity for AI strategies highlights the importance of innovation and adaptation in business operations.

Leveraging technology in B2B applications

B2B applications must leverage the latest technology to deliver value to customers.

— Brian Schiff
Leveraging advanced technologies is essential for B2B companies to remain relevant and effective.
The competitive landscape in B2B technology is influenced by innovation and technological advancement.
Ultimately I think the purpose of a B2B app is to deliver measurable value…

— Brian Schiff
Adopting the latest technology is crucial for delivering measurable value and enhancing customer satisfaction.
The necessity for innovation in B2B applications underscores the importance of staying ahead of industry trends.
Understanding the importance of technology in B2B applications is crucial for driving growth and success.
Leveraging technology in B2B applications reflects a broader trend towards digital transformation and innovation.

Applicability of technology in different market segments

The technology is particularly suited for large consumer businesses due to high contact volumes, but less so for B2B environments.

— Brian Schiff
Certain technologies are more applicable in specific market segments, highlighting strategic decision-making.
The applicability of technology in different market segments is influenced by customer interaction volume.
I think the first sort of realization is that this technology is great for large consumer businesses…

— Brian Schiff
Understanding the differences between B2B and B2C environments is crucial for strategic decision-making.
The strategic decision-making process involves determining the applicability of technologies in specific market segments.
The applicability of technology reflects the importance of tailoring solutions to specific business needs and environments.
Understanding the applicability of technology is essential for making informed business decisions and driving success.