Zero-Commission Ordering SaaS and Merchant Digital Operations Outsourcing

📌 Background

The restaurant SaaS industry entered the zero-commission era in 2026. Industry white papers indicate that domestic restaurant digitalization penetration has exceeded 55%, with the ordering SaaS market size surpassing 45 billion RMB, while commission rates on public delivery platforms remain as high as 15%-25% (based on white paper data; merchant survey samples not independently verified). Over 72% of surveyed merchants expressed a reluctance to rely on commission-based traffic platforms in the long term. By switching to an annual subscription model, a single store with a monthly delivery turnover of 50,000 RMB can save nearly 10,000 RMB in commissions per month.

👤 Target Customers

Mid-tier and small-to-medium restaurant chains and independent outlets, particularly tea shops, fast-food outlets, and bakeries struggling with delivery platform commissions.

💰 Revenue Streams

1) Fixed monthly/annual SaaS subscription fees, with no commission per order; 2) Service fees or performance-based fees for value-added outsourcing services such as AI-driven delivery review management, AI member SMS marketing, and AIGC graphic design; 3) Hardware rental income, such as providing smart all-in-one POS terminals or kitchen KDS screens.

🧮 Cost Structure

R&D team labor costs (SaaS iteration and AI algorithm optimization); local field sales and channel partner revenue-sharing costs; server and computing resource consumption; labor costs for customer success and operations teams.

🛡️ Moat

Rapidly scale by leveraging a zero-commission, high-quality, low-cost basic SaaS to create a closed loop of merchant operational data. Use this data to train high-precision, domain-specific AI models for the restaurant industry, helping merchants generate marketing copy and menu suggestions that better align with customer preferences, thereby creating high switching costs that make competitors difficult to adopt.

🔑 Keys to Success

• Strictly avoid transaction commissions to build merchant trust and a natural traffic pool
• Transition AI operations outsourcing from labor-intensive to tool-intensive to maximize revenue per employee
• Prioritize securing regional fast-food and tea shop chains to establish benchmark cases and facilitate rapid expansion

⚠️ Risks

• Meituan POS and Alibaba Local Services may aggressively subsidize hardware to block market entry regardless of cost
• High failure rates among small and medium-sized restaurants may lead to lower-than-expected SaaS renewal and collection rates
• Outsourcing service quality relies on human labor, lacking strong barriers and making it vulnerable to competitors poaching talent with higher salaries

🏢 Cases

• Zhidian Software's 2026 zero-commission aggregated delivery and SaaS platform for foot massage and pan-entertainment sectors
• Early-stage Meiwai's focus on remote queuing, eventually pivoting to full-process smart restaurant operations outsourcing
• Various regional POS software providers transitioning to offer bundled solutions combining Douyin delivery operations

📊 SWOT Analysis