Cairo-based quick commerce startup Rabbit has shared early results after launching in Riyadh, Saudi Arabia, in early 2024. Within six weeks, it built a network of dark stores covering half the city.

Rabbit plans to expand to more cities in the next two years and aims to deliver 20 million items in Saudi Arabia by 2026.

Early data shows Riyadh’s weekly reorder rates match those in Egypt, where Rabbit has delivered over 40 million items to 1.4 million users.

The company is adapting to local demand with city-specific strategies and prioritizing local sourcing.

In Egypt, over 60% of products are sourced locally, and Rabbit aims to match or exceed this in Saudi Arabia by featuring more Saudi brands.

Rabbit also uses AI for inventory, logistics, and user personalization.

🔗 Source: Arab News

🧠 Food for thought

1️⃣ Saudi Arabia’s Q-commerce represents a massive untapped opportunity

Rabbit is entering a market with extraordinary growth potential but very low current penetration, creating ideal conditions for rapid expansion.

Online grocery transactions in Saudi Arabia currently sit at just 1.3% of the total $60 billion food and grocery market, representing a massive untapped opportunity compared to more mature markets 1.

This low penetration is expected to change dramatically, with the Saudi Q-commerce market projected to grow from $448 million in 2024 to $2.35 billion by 2033, representing a compound annual growth rate of 20.21% 2.

The potential for growth is supported by Saudi Arabia’s 99% internet penetration rate (36.84 million users as of January 2024) and a mobile-first consumer base, with approximately 90% of online shoppers using smartphones for purchases 3, 2.

Industry projections suggest the Kingdom will see over 850,000 daily online food orders by 2024, highlighting the accelerating shift in consumer behavior toward digital convenience solutions 2.

2️⃣ Hyper-localization is the key differentiator in Saudi e-grocery

Rabbit’s emphasis on local sourcing and Saudi-specific operations reflects a crucial understanding that winning in this market requires deep localization, not just exporting existing models.