The Challenge

Owner makes it easy for restaurants to operate and scale their business online. When I joined, our growth was capped by the size of our sales team. It was clear we needed to move towards a product-led growth model to scale faster.

Discovery

Research & Customer Insights

Through customer interviews, we validated that Owner increases online order revenue without increasing operational costs. However, we learned that many restaurant operators were trying to find ways to integrate AI into their business. Since Owner makes basic restaurant operations simple, it became clear from these conversations we needed to do the same with how they incorporate AI into their business.

Key Insight:
• Restaurants loved that our product was easy to use, provided immediate value, and required minimal setup and maintenance.
• AI was highly appealing, especially given labor shortages in the industry.

Strategic Ideation

Armed with customer feedback, our CTO and I brainstormed ways to leverage these insights. We envisioned a self-serve onboarding for our website builder, free to use, allowing potential customers to experience the product’s value firsthand.

Key Decision: Integrate product-led growth and AI to create a seamless, automated experience that assists in attracting, qualifying, and onboarding leads.

In-person User Testing & Market Feedback

• Ease of Use: Users appreciated the simplicity and user-friendly nature of the prototypes.
• Skepticism about Free Tools:
  • Initial skepticism was expressed about the value of the website and tools offered for free.
  • Despite empathizing with this concern, leadership decided to keep the tools free.
• AI in Daily Operations: Users shared insights on how they use AI for various tasks:
  • Email campaign copy
  • Layout assistance
  • Website copy
  • Image generation
• Perception of AI: While users admired AI’s capabilities, they felt many businesses were using AI as a gimmick rather than for substantial improvements.
• Domain Switching Concerns:
  • Users were hesitant about immediately switching their domain to our nameservers.
  • This caution was a recurring theme in conversations, but leadership opted to proceed with this strategy.
• Messaging Refinement: Feedback was instrumental in refining our messaging to better communicate the benefits of upgrading.

Key Finding: Users needed clear, tangible benefits to see the value in upgrading to paid features.

Designing the Solution

Narrowing the Opportunity

We scoped a solution to build a website generator. Restaurants could enter their details and instantly receive a preview of their website with real content, images, menu items, and more, aggregated from the web and polished with AI.

Features:

• AI-generated websites with real customer information
• Easy onboarding process to save and customize the generated site
• Simple web and conversion analytics
• High-converting email capture
• Powerful Google SEO optimization

Prototyping & Iterative Design

We created multiple prototypes and iterated based on rounds of feedback, aiming to make the process intuitive and engaging.

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‍Phase 4: Refine and Measure

We used this phase to improve some product areas and get to some things that we wanted to do to make the experience that much better as we measured.

Outcome: A user-friendly onboarding flow that encouraged engagement and showcased the product’s value.

Impact

We launched and made a splash as we saturated our audience with social media ad campaigns from our marketing team.

• Process Enhancements: Streamlined our onboarding process, cutting setup time by 50%
• Product Improvements: Feedback led to significant enhancements in our AI tools and overall user experience

Reflection

This project reshaped our understanding of the market and underscored the importance of aligning product development with market readiness and building brand trust.

Lessons Learned:

• Timing is crucial: Despite how our positioning, the restaurant industry saw AI as a gimmick.
• Trust is everything: Build brand recognition before introducing significant changes.
• Testing isn’t validation: We needed to heed to the cautions of the customers we interviewed rather than assume we know better.
• Perception is everything: Making this free undershot our value. Restaurant Owners are very transactional. They think that if it seems too good to be true, it probably is.