In this article we’ll look at how leveraging Average Revenue and Average Orders Per Store leads to better profits. You’ll read about…

  • What Average Revenue Per Store is and why it matters
  • Targeted promotions and customer experiences
  • Performance benchmarking and resource allocation
  • What Average Orders Per Store is and why it matters
  • Operational efficiency and customer engagement
  • Optimising staff and streamlining operations

Two crucial metrics you need to really own for when you have 2 or more QSR outlets are Average Revenue Per Store and Average Orders Per Store. Here’s how analysing these metrics can provide actionable insights to help with your overall performance.

Why it matters:

  • Performance benchmarking: By comparing the average revenue across different locations, you can identify high-performing stores and those that may need improvement. For instance, if Store A consistently outperforms Store B, understanding the factors behind this difference (e.g.: location, staff performance, marketing efforts) can help replicate successful strategies across other stores.
  • Resource allocation: Stores with higher average revenue might warrant additional investment in staff or inventory, while underperforming stores might need strategic adjustments or targeted support.
  • Targeted Promotions: Analyse sales data across stores to identify which promotions drive the most revenue. If a special menu item boosts average revenue significantly at one store, consider rolling out similar promotions at your other stores.
  • Customer Experience: Store-specific data can reveal whether certain locations have a more effective customer service approach or ambiance. Use these insights to standardise best practices across all stores.

Why it matters:

  • Operational efficiency: This metric helps gauge how well each store is handling order volume. Stores with higher average orders may indicate effective processes, while lower figures might suggest inefficiencies or service problems.
  • Customer engagement: High average order numbers often correlate with strong customer engagement and satisfaction. By monitoring this metric, you can identify stores that excel in attracting repeat business and those that may need improvements in customer relations.
  • Optimise staffing: Use order data to ensure staffing levels match demand. Stores with high order volumes may need additional staff during peak times, while those with lower volumes might benefit from a streamlined workforce.
  • Streamline operations: If some stores are handling more orders efficiently, analyse their operational processes and see if they can be implemented elsewhere. This could involve better inventory management, faster service times, or improved training programs.