Thoughts from a Measured Marketer: Restaurant Technology Edition

Introduction

The food service industry has undergone a significant transformation with the advent of online food ordering systems, third-party marketplaces, and ghost kitchens. The evolution of technology, coupled with a tech-lagging industry, have resulted in a gap between the needs of growth-stage restaurants and the technology available. Here, we will explore the factors leading to this gap and a potential path forward.

The Evolution of Technology

1. The Rise of Low-Cost Development Resources and Lean Development

The global availability of inexpensive development resources has accelerated the adoption of lean development methodologies. Lean development emphasizes launching minimum viable products (MVPs) quickly to gather customer feedback for iterative improvements. While this approach is cost-effective and accelerates time-to-market, it often results in products that lack fully developed user experiences and robust customer service.

In the food service industry, this has led to online ordering systems that are functional but often lack the sophistication and flexibility required for a seamless user experience. According to a survey by Software Advice, 37% of restaurant operators found their online ordering systems to be lacking in usability and integration capabilities (Software Advice, 2023).

2. The Tech Savviness Gap in Small to Growth-Stage Restaurants

Small to growth-stage restaurants often lack the technical expertise and resources to develop or even identify the right technological solutions. This gap is at odds with the lean development principle that relies on continuous iteration based on customer feedback. Restaurants depend heavily on tech companies to provide and maintain these systems, leading to a dependency that can stifle innovation and adaptation.

The mismatch between what tech companies develop and what restaurants need is evident in the high friction of current online food ordering systems. These systems often have limited flexibility for bundling, upselling, and dynamic pricing, which are crucial for maximizing revenue and enhancing customer satisfaction.

3. The Rise of Generative AI and Self-Service Customer Support

Generative AI has revolutionized customer support, enabling self-service options that reduce operational costs. However, for small to growth-stage restaurants, this shift can be problematic. The reliance on AI for customer interaction can exacerbate the existing tech gap, as these systems require sophisticated integration and continuous updates to function effectively. This reliance further alienates restaurants from their customers, as the personal touch is lost in automated interactions.

Comparing Food Ordering and E-commerce Experiences

When comparing food ordering systems to general e-commerce platforms, the former falls short in several areas. E-commerce platforms typically offer high flexibility in product bundling, upselling, and dynamic pricing. They are designed to enhance user experience through personalized recommendations and seamless checkout processes.

In contrast, food ordering systems are often rigid, offering limited customization options. The underlying data structure, primarily derived from Point of Sale (POS) systems, is not conducive to creating dynamic and flexible ordering experiences. POS systems are traditionally designed for in-store transactions and lack the data architecture needed for sophisticated online ordering functionalities.

Friction and Flexibility Analysis

• E-commerce: High flexibility in product bundling, upselling, and dynamic pricing. Seamless user experience with personalized recommendations and efficient checkout processes.
• Food Ordering: High friction with limited customization options. Rigid data structure and less personalized user experience. According to a study by the National Restaurant Association, 45% of consumers reported frustration with the lack of customization options in online food ordering platforms (National Restaurant Association, 2022). Despite 79% of restaurants prioritizing new dining experience prototyping, satisfaction with their technological infrastructure is notably low, at just 22% (Incisiv, 2024).?

Technology Gap and the Rise of Third-Parties

The technology gap has significantly contributed to the rise of third-party marketplaces and ghost kitchens. These entities have optimized user experiences and conversion rates, making them highly efficient and more competitive in the market. Third-party delivery companies, such as Uber Eats and DoorDash, have invested heavily in technology to create seamless ordering experiences, which in turn attracts more customers.

Customers are increasingly using these platforms due to their superior UX and frequent promotions. As a result, restaurant owners struggle to compete for online orders. With third-party delivery platforms taking up to 30% or more of each order, the financial impact on restaurants can be significant, making it a make-or-break factor for many.

Learning from E-commerce:? A Solution

To address these challenges, the restaurant tech industry should look to the e-commerce industry for solutions. The playbook and technology already exist:

1. Develop a Flexible Data Architecture: Create a data infrastructure that supports dynamic pricing, personalized recommendations, and flexible bundling options. This foundation will enable more sophisticated and user-friendly ordering experiences.
2. Collaborate with (The Right) Specialists: Since restaurant owners are often new to the digital space, engage directly with Marketing, UX and Data specialists in the e-commerce space to envision what frictionless and measurable looks like. Also collaborate directly with restaurant operators to understand their needs and challenges.? This collaboration will ensure that the technology developed is aligned with the practical realities of restaurant operations.
3. Iterative and Inclusive Development: While maintaining the principles of lean development, ensure that user experience and customer service are not compromised. Continuous feedback loops should include not only customer feedback but also insights from restaurant operators.
4. Integrate AI Thoughtfully: Use generative AI to enhance, not replace, human interaction. AI should support customer service by handling routine tasks, allowing restaurant staff to focus on high-value interactions that require a personal touch.

Conclusion

The current landscape of food ordering systems is a product of the rapid, lean-driven development cycle, the technological gaps in small to growth-stage restaurants, and the rise of generative AI. To break the downward cycle and create superior food ordering experiences, a new approach is needed—one that prioritizes flexible data architecture, collaboration with end users, and thoughtful integration of AI. By addressing these root causes and looking to the e-commerce industry for guidance, the food service industry can develop more sophisticated, user-friendly online ordering systems that meet the needs of both restaurants and customers.

References

• Software Advice. (2023). Restaurant Online Ordering System Survey.
• National Restaurant Association. (2022). Consumer Frustrations with Online Food Ordering Platforms.
• Restaurant Technology Today. (2022). Challenges in Integrating Traditional POS Systems with Modern Online Ordering Platforms.
• Incisiv.? (2024). 2024 State of the Industry: Future of In-Restaurant Dining